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From: "paris@powerlearnings.com.my" <paris@powerlearnings.com.my>
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Date: Wed, 3 Feb 2021 12:17:47 +0800
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Subject: ***SPAM*** IN HOUSE-DATA ANALYTICS FOR FASTER DECISION MAKING

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Kindly contact 012-588 2175 for more inquiry

DATA ANALYTICS FOR FASTER DECISION MAKING

This program can be specially tailored and customized to meet your =
training=20
objectives

Kindly find above attached for the full brochure for this programs

We hope you find it informative and interesting and we look forward to =
seeing=20
you soon

(HRDF/SBL Claimable)

2 days In-House =
Program=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=
=A0=A0=A0=A0=A0=A0 By Selvaraj

=A0

INTRODUCTION:

Data Analysis is an ever-evolving discipline with lots of focus on new =
predictive=20
modeling techniques coupled with rich analytical tools that keep =
increasing=20
our capacity to handle big data. However, in order to chart a coherent =
path=20
forward, it is necessary to understand where the discipline has come from =
since=20
its inception=2E

Today, more organizations are using data analysis tools and techniques in =
order=20
to inform=A0 effective decision-making. This module also addresses some of =
the=20
hurdles an organization faces when dealing with data overload and =
suggests=20
some possible solutions to the problem=2E

It is unfortunate that there is such a dearth of data analysts.=20

=A0

OBJECTIVES:

In this course, the participants will learn:

-=A0=A0=A0=A0=A0=A0 Types of data and how to group them=20

-=A0=A0=A0=A0=A0=A0 Basics of data organization

-=A0=A0=A0=A0=A0=A0 Basic statistics

-=A0=A0=A0=A0=A0=A0 Central limit theorem

-=A0=A0=A0=A0=A0=A0 Predict a process performance

-=A0=A0=A0=A0=A0=A0 Comparing between populations

-=A0=A0=A0=A0=A0=A0 Measure any changes in trend

-=A0=A0=A0=A0=A0=A0 Explore ways to measure the performance of and =
improvement opportunities

-=A0=A0=A0=A0=A0=A0 Discuss data distribution including Central Tendency, =
Variance, Normal=20
Distribution, and non-normal distributions=2E

-=A0=A0=A0=A0=A0=A0 Explore different methods and easy algorithms for =
forecasting future=20
results and to reduce current and future risk=2E

=A0

INTENDED AUDIENCE:

This seminar will benefit managers and engineers, designers and quality =
professionals=20
in research, design, development, testing, process and manufacturing.=A0=20

=A0

METHODOLOGY:

-=A0=A0=A0=A0=A0=A0 Activities, discussions, videos and case studies with =
frequent activities=20
& quiz for a deeper understanding=2E

-=A0=A0=A0=A0=A0=A0 Minitab 18 & Microsoft Excel would be the preferred =
softwares to be=20
used

-=A0=A0=A0=A0=A0=A0 Each participant to have their own computer during =
training for hands=20
on application

=A0

DURATION:

2 days=20

=A0

Outline Of Workshop

What is Data Analytics?

i.=A0=A0=A0=A0=A0=A0=A0 Definition of DA

ii.=A0=A0=A0=A0=A0 Data Here, There, and Everywhere!

iii.=A0=A0=A0=A0 Possible solutions to data overflow problems

iv.=A0=A0=A0=A0 Got Data? The Unique Role of the Data Analyst

v.=A0=A0=A0=A0=A0=A0 Role of a Data Analyst

vi.=A0=A0=A0=A0 Skill set required to be an effective Data Analyst

vii.=A0=A0 Exercise

=A0

Fact-Based Decision-Making Process

i.=A0=A0=A0=A0=A0=A0=A0 How to collect & use appropriate data?

ii.=A0=A0=A0=A0=A0 Attributive vs variable data

iii.=A0=A0=A0=A0 Transform data to information

iv.=A0=A0=A0=A0 Means & Standard Deviation

v.=A0=A0=A0=A0=A0=A0 Statistical method for decision making

vi.=A0=A0=A0=A0 Large & small sample theory

vii.=A0=A0 Data from industries : specs, tolerance, variance, process =
capability

viii.=A0 Activity

ix.=A0=A0=A0=A0 The two types of Decision Models Businesses use

x.=A0=A0=A0=A0=A0=A0 The Benefits of Fact-Based Decision Making

xi.=A0=A0=A0=A0 Rational Decision Model: Six- Step Method

xii.=A0=A0 Exercise

=A0

Big Data Anatomy

i.=A0=A0=A0=A0=A0=A0=A0 The Attributes of Big Data

ii.=A0=A0=A0=A0=A0 Definition of Big Data

iii.=A0=A0=A0=A0 The 4 V's of Big Data

iv.=A0=A0=A0=A0 Structured versus Unstructured Data

v.=A0=A0=A0=A0=A0=A0 The Challenges of Big Data

vi.=A0=A0=A0=A0 Exercise

=A0

Getting to Know Your Data

i.=A0=A0=A0=A0=A0=A0=A0 Data Types: Qualitative versus Quantitative

ii.=A0=A0=A0=A0=A0 Taking a Closer Look: Data Measurement

iii.=A0=A0=A0=A0 Four Types of Data Variables

iv.=A0=A0=A0=A0 Definition and examples of Nominal Variables

v.=A0=A0=A0=A0=A0=A0 Definition and examples of Ordinal Variables: Order =
Matters

vi.=A0=A0=A0=A0 Definition and examples of Interval Variables

vii.=A0=A0 Definition and examples of Ratio Variables

viii.=A0 Summary of Statistics/Operations that can be performed on each =
type

ix.=A0=A0=A0=A0 Exercise

=A0

The Fundamental Ways we use data Visualization techniques

i.=A0=A0=A0=A0=A0=A0=A0 The five ways we use data visualization techniques

ii.=A0=A0=A0=A0=A0 Displaying Tabular Data in Excel

iii.=A0=A0=A0=A0 Using Charts and Graphs to Communicate Data

iv.=A0=A0=A0=A0 How to create Pie, Column, and Line charts using Excel

v.=A0=A0=A0=A0=A0=A0 Communicating effectively using different chart types

vi.=A0=A0=A0=A0 How to choose the correct chart to display the correct =
data type

vii.=A0=A0 Exercise

=A0

Using Numerical Descriptives to Summarize Data

i.=A0=A0=A0=A0=A0=A0=A0 Measures of Centrality: Mean, Median, Mode

ii.=A0=A0=A0=A0=A0 Format of Data Values: Grouped Discrete and Grouped =
Continuous

iii.=A0=A0=A0=A0 Formulas for the Mean Examples: Applying 3M's to Grouped =
Discrete=20
and Grouped Continuous Data

iv.=A0=A0=A0=A0 Measures of Spread: Standard Deviation, Range, =
Inter-quartile Range=20
Examples

=A0

Probability: Quantifying Uncertainty

i.=A0=A0=A0=A0=A0=A0=A0 Origin of Probability

ii.=A0=A0=A0=A0=A0 Probability: Examples of Business Applications

iii.=A0=A0=A0=A0 The traditional definition of Probability

iv.=A0=A0=A0=A0 Applying probability to calculate the expected value

v.=A0=A0=A0=A0=A0=A0 Using Expected Value in Decision Making

vi.=A0=A0=A0=A0 Exercise=20

=A0

The Normal Distribution

i.=A0=A0=A0=A0=A0=A0=A0 Characteristics of the Normal Distribution

ii.=A0=A0=A0=A0=A0 Interpreting the Empirical Rule

iii.=A0=A0=A0=A0 Components of the Normal Distribution: Probabilities and =
X values

iv.=A0=A0=A0=A0 Using the NORMDIST function in Excel to calculate =
probability from=20
a normal distribution

v.=A0=A0=A0=A0=A0=A0 Using the NORM. INV function in Excel to calculate X =
values related=20
to a normal distribution

vi.=A0=A0=A0=A0 Exercise

=A0

Correlation and Regression=A0

i.=A0=A0=A0=A0=A0=A0=A0 Definition of Correlation and Regression

ii.=A0=A0=A0=A0=A0 The relationship between Correlation and Regression

iii.=A0=A0=A0=A0 Correlation Coefficient: Values

iv.=A0=A0=A0=A0 Examples of Correlation

v.=A0=A0=A0=A0=A0=A0 Interpretation of a Regression Equation

vi.=A0=A0=A0=A0 Step-by-Step example of How to Do a Regression Analysis

vii.=A0=A0 Exercise

=A0

ABOUT THE FACILITATOR=20

Selvaraj =A0is a highly qualified technical trainer in the areas of =
Continuous=20
Improvement and Quality Excellence. He believes in interactive and fun =
filled=20
training. His method of training is sharing rather than lecturing. With =
23=20
years of experience in the field of Manufacturing Improvement & Quality =
Excellence=20
covering areas of Design, Material Selection, Tooling, Machine & Process =
Engineering,=20
Production and Supply Chain Management, Selvaraj B uses lots of real life =
examples.=20
Selvaraj =A0started his career in 1989 as a Mechanical Engineer and in 23 =
years,=20
has worked in 3 MNC companies that are World Class, i.e. Matsushita =
(Japanese),=20
Robert Bosch (German) and Entegris (American) up to the level of an =
Operations=20
Manager. Selvaraj B is a certified HRDF trainer. His strength is =
combining=20
the intricacies and details of technical training with highly humorous =
anecdotes=20
for maximum training effectiveness.=A0=A0=20

=A0

AMONG HIS NOTABLE ACHIEVEMENTS ARE:

1. Leading Gold Medal winning teams to NPC conventions =96 1995 - 2002

2. Certified MTM and Ergonomics practitioner - 1997

3. Tooling & plastic parts design standardization - 2000

4. Awarded best Six Sigma Champion award in 2006 for promoting successful =
Sigma=20
projects =96 2006

5. Certified Trainer with Napoleon Hill International - 2007=20

6. Certified Lean Sigma Champion=A0 - 2010

7. Competent Communicator & Humorous Speech Division N Champion in =
Toastmasters=20
International =96 2012

8. Certified Six Sigma Master Black Belt - 2016

9. Member of the Society of Plastics Engineers

10. Member of the Institute of Engineers Malaysia=20

11. Certified NLP Practitioner - 2016=20

12. Certified VDI Quality Systems auditor - 1997

13.Certified Industry 4.0 Professional accredited by the US-based

International Institute of Executive Careers=99 (IIEC)

=A0

AMONG HIS NOTABLE IMPROVEMENTS PROJECTS ARE:

1. Consolidating the Plastic Injection Moulding sections into 1 =
department=20
& leading it =96 Bosch Bayan Lepas=20

2. Motivating and guiding numerous scrap reduction & quality improvement =
teams=20
=96 Bosch Bayan Lepas, Automotive Lighting Bayan Lepas=20

3. Reduction of manufacturing lead time from 28 days to 3 days =96 Entegris

4. Cycle time reduction projects =96 Bosch, Entegris

5. Lean improvement projects =96 Signature Kitchen Sdn. Bhd. KL, Anshin =
Precision=20
Sdn. Bhd. Shah Alam, Silverstone Berhad Taiping=2E

6. Starting a new factory of 200 headcount for Silicone Wafer Process =
Carrier=20
comprising of Manufacturing, Maintenance, Engineering, Tooling, =
Production=20
Planning & Continuous Improvement Department =96 Entegris Kulim Hi-Tech=2E

7. Guiding and inspiring numerous quality improvement and cost reduction =
teams=20
to State level and National level competition and recognition.=20

8. Setting up & developing a World Class Manufacturing team for clean =
room=20
fittings manufacturing =96 Entegris Kulim Hi-Tech=20

=A0

We hope you find it informative and interesting and we look

forward to seeing you soon=2E

Please act fast to grab your favourite training program! Please call =
012-588=20
2175

=A0

Do forward this email to all your friends and colleagues who might be =
interested=20
to attend these programs

=A0

If you would like to unsubscribe from our email list at any time, please =
simply=20
reply to the e-mail and type

Unsubscribein the subject area. We will remove your name from the list =
and=20
you will not receive any additional e-mail

=A0

Thanks

=A0

Regards

Paris Oo
Mobile No. : 012-5882175

=A0

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<html>
<head>
<meta content=3D"text/html; charset=3D" http-equiv=3D"content-type">
</head>
<body style=3D"FONT-SIZE: 10pt; FONT-FAMILY: Tahoma, Tahoma">
<span=20
lang=3DEN-MY style=3D"COLOR: #7030a0; mso-ansi-language: EN-MY"><font=20
face=3DCalibri>Kindly contact 012-588 2175 for more inquiry<?xml:namespace =
prefix=20
=3D "o" ns =3D "urn:schemas-microsoft-com:office:office"=20
/><o:p></o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 22pt; FONT-FAMILY: "Times New Roman",serif; COLOR: =
blue; mso-ansi-language: EN-MY'>DATA=20
ANALYTICS FOR FASTER DECISION MAKING<o:p></o:p>
This=20
program can be specially tailored and customized to meet your training=20
objectives<o:p></o:p>
<font=20
size=3D3>Kindly find above attached for the full brochure for this=20
programs<o:p></o:p>
We hope=20
you find it informative and interesting and we look forward to seeing you=20
soon<o:p></o:p>
<font=20
size=3D3>(HRDF/SBL Claimable)<o:p></o:p>
<font=20
size=3D3>2 days In-House=20
Program&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&n=
bsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp=
;&nbsp;&nbsp;&nbsp;&nbsp;=20
By Selvaraj<o:p></o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-ansi-language: EN-MY'><o:p>&nbsp;</o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-ansi-language: EN-MY'>INTRODUCTION<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-ansi-language: EN-MY'>:<o:p></o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-ansi-language: EN-MY'>Data=20
Analysis is an ever-evolving discipline with lots of focus on new =
predictive=20
modeling techniques coupled with rich analytical tools that keep =
increasing our=20
capacity to handle big data. However, in order to chart a coherent path =
forward,=20
it is necessary to understand where the discipline has come from since =
its=20
inception.<o:p></o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-ansi-language: EN-MY'>Today,=20
more organizations are using data analysis tools and techniques in order =
to=20
inform&nbsp; effective decision-making. This module also addresses some of =
the=20
hurdles an organization faces when dealing with data overload and suggests =
some=20
possible solutions to the problem.<o:p></o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-ansi-language: EN-MY'>It=20
is unfortunate that there is such a dearth of data analysts.=20
<o:p></o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-ansi-language: EN-MY'><o:p>&nbsp;</o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-ansi-language: EN-MY'>OBJECTIVES<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-ansi-language: EN-MY'>:<o:p></o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-ansi-language: EN-MY'>In=20
this course, the participants will learn:<o:p></o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Arial",sans-serif; =
mso-ansi-language: EN-MY; mso-fareast-font-family: Arial'><span=20
style=3D"mso-list: Ignore">-<span=20
style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
Types=20
of data and how to group them <o:p></o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Arial",sans-serif; =
mso-ansi-language: EN-MY; mso-fareast-font-family: Arial'><span=20
style=3D"mso-list: Ignore">-<span=20
style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
Basics=20
of data organization<o:p></o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Arial",sans-serif; =
mso-ansi-language: EN-MY; mso-fareast-font-family: Arial'><span=20
style=3D"mso-list: Ignore">-<span=20
style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
Basic=20
statistics<o:p></o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Arial",sans-serif; =
mso-ansi-language: EN-MY; mso-fareast-font-family: Arial'><span=20
style=3D"mso-list: Ignore">-<span=20
style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
Central=20
limit theorem<o:p></o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Arial",sans-serif; =
mso-ansi-language: EN-MY; mso-fareast-font-family: Arial'><span=20
style=3D"mso-list: Ignore">-<span=20
style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
Predict=20
a process performance<o:p></o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Arial",sans-serif; =
mso-ansi-language: EN-MY; mso-fareast-font-family: Arial'><span=20
style=3D"mso-list: Ignore">-<span=20
style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
Comparing=20
between populations<o:p></o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Arial",sans-serif; =
mso-ansi-language: EN-MY; mso-fareast-font-family: Arial'><span=20
style=3D"mso-list: Ignore">-<span=20
style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
Measure=20
any changes in trend<o:p></o:p>
<p class=3DMsoNormal=20
style=3D"TEXT-ALIGN: justify; MARGIN: 0in 0in 0in 20.9pt; LINE-HEIGHT: =
12pt; TEXT-AUTOSPACE: ideograph-numeric; TEXT-INDENT: -20.9pt; mso-list: =
l4 level1 lfo1; tab-stops: list 21.0pt"><span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Arial",sans-serif; =
mso-ansi-language: EN-MY; mso-fareast-font-family: Arial'><span=20
style=3D"mso-list: Ignore">-<span=20
style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
Explore=20
ways to measure the performance of and improvement=20
opportunities<o:p></o:p>
<p class=3DMsoNormal=20
style=3D"TEXT-ALIGN: justify; MARGIN: 0in 0in 0in 20.9pt; LINE-HEIGHT: =
12pt; TEXT-AUTOSPACE: ideograph-numeric; TEXT-INDENT: -20.9pt; mso-list: =
l4 level1 lfo1; tab-stops: list 21.0pt"><span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Arial",sans-serif; =
mso-ansi-language: EN-MY; mso-fareast-font-family: Arial'><span=20
style=3D"mso-list: Ignore">-<span=20
style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
Discuss=20
data distribution including Central Tendency, Variance, Normal =
Distribution, and=20
non-normal distributions.<o:p></o:p>
<p class=3DMsoNormal=20
style=3D"TEXT-ALIGN: justify; MARGIN: 0in 0in 0in 20.9pt; LINE-HEIGHT: =
12pt; TEXT-AUTOSPACE: ideograph-numeric; TEXT-INDENT: -20.9pt; mso-list: =
l4 level1 lfo1; tab-stops: list 21.0pt"><span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Arial",sans-serif; =
mso-ansi-language: EN-MY; mso-fareast-font-family: Arial'><span=20
style=3D"mso-list: Ignore">-<span=20
style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
Explore=20
different methods and easy algorithms for forecasting future results and =
to=20
reduce current and future risk.<o:p></o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-ansi-language: EN-MY'><o:p>&nbsp;</o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-ansi-language: EN-MY'>INTENDED=20
AUDIENCE:<o:p></o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-ansi-language: EN-MY'>This=20
seminar will benefit managers and engineers, designers and quality =
professionals=20
in research, design, development, testing, process and =
manufacturing.&nbsp;=20
<o:p></o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-ansi-language: EN-MY'><o:p>&nbsp;</o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-ansi-language: EN-MY'>METHODOLOGY:<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-ansi-language: EN-MY'><o:p></o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Arial",sans-serif; =
mso-ansi-language: EN-MY; mso-fareast-font-family: Arial'><span=20
style=3D"mso-list: Ignore">-<span=20
style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
Activities,=20
discussions, videos and case studies with frequent activities &amp; quiz =
for a=20
deeper understanding.<o:p></o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Arial",sans-serif; =
mso-ansi-language: EN-MY; mso-fareast-font-family: Arial'><span=20
style=3D"mso-list: Ignore">-<span=20
style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
Minitab=20
18 &amp; Microsoft Excel would be the preferred softwares to be=20
used<o:p></o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Arial",sans-serif; =
mso-ansi-language: EN-MY; mso-fareast-font-family: Arial'><span=20
style=3D"mso-list: Ignore">-<span=20
style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
Each=20
participant to have their own computer during training for hands on=20
application<o:p></o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-ansi-language: EN-MY'><o:p>&nbsp;</o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-ansi-language: EN-MY'>DURATION:<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-ansi-language: EN-MY'>=20
<o:p></o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-ansi-language: EN-MY'>2=20
days <o:p></o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
BACKGROUND: white; COLOR: black; LINE-HEIGHT: 115%; mso-ansi-language: =
EN-MY'><o:p>&nbsp;</o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
BACKGROUND: white; COLOR: black; LINE-HEIGHT: 115%; mso-ansi-language: =
EN-MY'>Outline=20
Of Workshop<o:p></o:p>
<div align=3Dcenter>
<table class=3DMsoNormalTable=20
style=3D"BORDER-COLLAPSE: collapse; mso-yfti-tbllook: 1184; =
mso-padding-alt: 0in 0in 0in 0in"=20
cellSpacing=3D0 cellPadding=3D0 border=3D0>
 =20
 <tr=20
 style=3D"HEIGHT: 270.8pt; mso-yfti-irow: 0; mso-yfti-firstrow: yes; =
mso-yfti-lastrow: yes">
 <td=20
 style=3D"BORDER-TOP: windowtext 1pt solid; HEIGHT: 270.8pt; =
BORDER-RIGHT: windowtext 1pt solid; WIDTH: 521.75pt; BORDER-BOTTOM: =
windowtext 1pt solid; PADDING-BOTTOM: 0in; PADDING-TOP: 0in; PADDING-LEFT: =
5.4pt; BORDER-LEFT: windowtext 1pt solid; PADDING-RIGHT: 5.4pt; =
BACKGROUND-COLOR: transparent"=20
 vAlign=3Dtop width=3D696>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif'>What =
is Data=20
 Analytics?<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">i.<span=20
 style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'>Definition=20
 of DA<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">ii.<span=20
 style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif'>Data =
Here,=20
 There, and Everywhere!<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">iii.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'>Possible=20
 solutions to data overflow problems<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">iv.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif'>Got =
Data?=20
 The Unique Role of the Data Analyst<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">v.<span=20
 style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif'>Role =
of a=20
 Data Analyst<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">vi.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'>Skill set=20
 required to be an effective Data Analyst<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">vii.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'>Exercise<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'>&nbsp;<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'>Fact-Based=20
 Decision-Making Process<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">i.<span=20
 style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif'>How =
to=20
 collect &amp; use appropriate data?<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">ii.<span=20
 style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'>Attributive=20
 vs variable data<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">iii.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'>Transform=20
 data to information<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">iv.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'>Means &amp;=20
 Standard Deviation<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">v.<span=20
 style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'>Statistical=20
 method for decision making<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">vi.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'>Large &amp;=20
 small sample theory<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">vii.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif'>Data =
from=20
 industries : specs, tolerance, variance, process=20
 capability<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">viii.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp; =
<span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'>Activity<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">ix.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif'>The =
two=20
 types of Decision Models Businesses use<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">x.<span=20
 style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif'>The =
Benefits=20
 of Fact-Based Decision Making<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">xi.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'>Rational=20
 Decision Model: Six- Step Method<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">xii.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'>Exercise<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'>&nbsp;<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif'>Big =
Data=20
 Anatomy<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">i.<span=20
 style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif'>The=20
 Attributes of Big Data<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">ii.<span=20
 style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'>Definition=20
 of Big Data<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">iii.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif'>The =
4 V's of=20
 Big Data<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">iv.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'>Structured=20
 versus Unstructured Data<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">v.<span=20
 style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif'>The=20
 Challenges of Big Data<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">vi.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'>Exercise<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'>&nbsp;<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'>Getting to=20
 Know Your Data<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">i.<span=20
 style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif'>Data =
Types:=20
 Qualitative versus Quantitative<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">ii.<span=20
 style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'>Taking a=20
 Closer Look: Data Measurement<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">iii.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif'>Four =
Types=20
 of Data Variables<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">iv.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'>Definition=20
 and examples of Nominal Variables<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">v.<span=20
 style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'>Definition=20
 and examples of Ordinal Variables: Order =
Matters<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">vi.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'>Definition=20
 and examples of Interval Variables<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">vii.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'>Definition=20
 and examples of Ratio Variables<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">viii.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp; =
<span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'>Summary of=20
 Statistics/Operations that can be performed on each=20
 type<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">ix.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'>Exercise<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'><o:p>&nbsp;</o:p></td>
 <td=20
 style=3D"BORDER-TOP: windowtext 1pt solid; HEIGHT: 270.8pt; =
BORDER-RIGHT: windowtext 1pt solid; WIDTH: 507.3pt; BORDER-BOTTOM: =
windowtext 1pt solid; PADDING-BOTTOM: 0in; PADDING-TOP: 0in; PADDING-LEFT: =
5.4pt; BORDER-LEFT: #f0f0f0; PADDING-RIGHT: 5.4pt; BACKGROUND-COLOR: =
transparent"=20
 vAlign=3Dtop width=3D676>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif'>The=20
 Fundamental Ways we use data Visualization=20
 techniques<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">i.<span=20
 style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
COLOR: black'>The=20
 five ways we use data visualization techniques<span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'><o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">ii.<span=20
 style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
COLOR: black'>Displaying=20
 Tabular Data in Excel<span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'><o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">iii.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
COLOR: black'>Using=20
 Charts and Graphs to Communicate Data<span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'><o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">iv.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
COLOR: black'>How=20
 to create Pie, Column, and Line charts using Excel<span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'><o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">v.<span=20
 style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
COLOR: black'>Communicating=20
 effectively using different chart types<span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'><o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">vi.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
COLOR: black'>How=20
 to choose the correct chart to display the correct data =
type<span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'><o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">vii.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
COLOR: black'>Ex<span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'>ercise<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'>&nbsp;<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'>Using=20
 Numerical Descriptives to Summarize Data<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">i.<span=20
 style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
COLOR: black'>Measures=20
 of Centrality: Mean, Median, Mode<span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'><o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">ii.<span=20
 style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
COLOR: black'>Format=20
 of Data Values: Grouped Discrete and Grouped Continuous<span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'><o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">iii.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
COLOR: black'>Formulas=20
 for the Mean Examples: Applying 3M's to Grouped Discrete and =
Grouped=20
 Continuous Data<span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'><o:p></o:p>
 <p class=3DMsoNormal=20
 style=3D"TEXT-ALIGN: justify; MARGIN: 0in 0in 0in 21.25pt; =
LINE-HEIGHT: 12pt; TEXT-AUTOSPACE: ideograph-numeric; TEXT-INDENT: =
-21.25pt; mso-list: l6 level1 lfo7; tab-stops: list 21.25pt"><span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">iv.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
COLOR: black'>Measures=20
 of Spread: Standard Deviation, Range, Inter-quartile Range=20
 Examples<span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'><o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
COLOR: black'>&nbsp;<span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'><o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'>Probability:=20
 Quantifying Uncertainty<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">i.<span=20
 style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
COLOR: black'>Origin=20
 of Probability<span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'><o:p></o:p>
 <p class=3DMsoNormal=20
 style=3D"TEXT-ALIGN: justify; MARGIN: 0in 0in 0in 21.25pt; =
LINE-HEIGHT: 12pt; TEXT-AUTOSPACE: ideograph-numeric; TEXT-INDENT: =
-21.25pt; mso-list: l1 level1 lfo8; tab-stops: list 21.25pt"><span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">ii.<span=20
 style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
COLOR: black'>Probability:=20
 Examples of Business Applications<span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'><o:p></o:p>
 <p class=3DMsoNormal=20
 style=3D"TEXT-ALIGN: justify; MARGIN: 0in 0in 0in 21.25pt; =
LINE-HEIGHT: 12pt; TEXT-AUTOSPACE: ideograph-numeric; TEXT-INDENT: =
-21.25pt; mso-list: l1 level1 lfo8; tab-stops: list 21.25pt"><span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">iii.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
COLOR: black'>The=20
 traditional definition of Probability<span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'><o:p></o:p>
 <p class=3DMsoNormal=20
 style=3D"TEXT-ALIGN: justify; MARGIN: 0in 0in 0in 21.25pt; =
LINE-HEIGHT: 12pt; TEXT-AUTOSPACE: ideograph-numeric; TEXT-INDENT: =
-21.25pt; mso-list: l1 level1 lfo8; tab-stops: list 21.25pt"><span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">iv.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
COLOR: black'>Applying=20
 probability to calculate the expected value<span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'><o:p></o:p>
 <p class=3DMsoNormal=20
 style=3D"TEXT-ALIGN: justify; MARGIN: 0in 0in 0in 21.25pt; =
LINE-HEIGHT: 12pt; TEXT-AUTOSPACE: ideograph-numeric; TEXT-INDENT: =
-21.25pt; mso-list: l1 level1 lfo8; tab-stops: list 21.25pt"><span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">v.<span=20
 style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
COLOR: black'>Using=20
 Expected Value in Decision Making<span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'><o:p></o:p>
 <p class=3DMsoNormal=20
 style=3D"TEXT-ALIGN: justify; MARGIN: 0in 0in 0in 21.25pt; =
LINE-HEIGHT: 12pt; TEXT-AUTOSPACE: ideograph-numeric; TEXT-INDENT: =
-21.25pt; mso-list: l1 level1 lfo8; tab-stops: list 21.25pt"><span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">vi.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
COLOR: black'>Exercise=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'><o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'><o:p><span=20
 style=3D"TEXT-DECORATION: =
none">&nbsp;</o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif'>The =
Normal=20
 Distribution<o:p></o:p>
 <p class=3DMsoNormal=20
 style=3D"TEXT-ALIGN: justify; MARGIN: 0in 0in 0in 21.25pt; =
LINE-HEIGHT: 12pt; TEXT-AUTOSPACE: ideograph-numeric; TEXT-INDENT: =
-21.25pt; mso-list: l8 level1 lfo9; tab-stops: list 21.25pt"><span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">i.<span=20
 style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
COLOR: black'>Characteristics=20
 of the Normal Distribution<span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'><o:p></o:p>
 <p class=3DMsoNormal=20
 style=3D"TEXT-ALIGN: justify; MARGIN: 0in 0in 0in 21.25pt; =
LINE-HEIGHT: 12pt; TEXT-AUTOSPACE: ideograph-numeric; TEXT-INDENT: =
-21.25pt; mso-list: l8 level1 lfo9; tab-stops: list 21.25pt"><span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">ii.<span=20
 style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
COLOR: black'>Interpreting=20
 the Empirical Rule<span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'><o:p></o:p>
 <p class=3DMsoNormal=20
 style=3D"TEXT-ALIGN: justify; MARGIN: 0in 0in 0in 21.25pt; =
LINE-HEIGHT: 12pt; TEXT-AUTOSPACE: ideograph-numeric; TEXT-INDENT: =
-21.25pt; mso-list: l8 level1 lfo9; tab-stops: list 21.25pt"><span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">iii.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
COLOR: black'>Components=20
 of the Normal Distribution: Probabilities and X values<span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'><o:p></o:p>
 <p class=3DMsoNormal=20
 style=3D"TEXT-ALIGN: justify; MARGIN: 0in 0in 0in 21.25pt; =
LINE-HEIGHT: 12pt; TEXT-AUTOSPACE: ideograph-numeric; TEXT-INDENT: =
-21.25pt; mso-list: l8 level1 lfo9; tab-stops: list 21.25pt"><span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">iv.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
COLOR: black'>Using=20
 the NORMDIST function in Excel to calculate probability from a =
normal=20
 distribution<span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'><o:p></o:p>
 <p class=3DMsoNormal=20
 style=3D"TEXT-ALIGN: justify; MARGIN: 0in 0in 0in 21.25pt; =
LINE-HEIGHT: 12pt; TEXT-AUTOSPACE: ideograph-numeric; TEXT-INDENT: =
-21.25pt; mso-list: l8 level1 lfo9; tab-stops: list 21.25pt"><span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">v.<span=20
 style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
COLOR: black'>Using=20
 the NORM. INV function in Excel to calculate X values related to a =
normal=20
 distribution<span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'><o:p></o:p>
 <p class=3DMsoNormal=20
 style=3D"TEXT-ALIGN: justify; MARGIN: 0in 0in 0in 21.25pt; =
LINE-HEIGHT: 12pt; TEXT-AUTOSPACE: ideograph-numeric; TEXT-INDENT: =
-21.25pt; mso-list: l8 level1 lfo9; tab-stops: list 21.25pt"><span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">vi.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
COLOR: black'>E<span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'>xercise<o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 10pt; FONT-FAMILY: "Times New =
Roman",serif'>&nbsp;<span=20
 style=3D"FONT-SIZE: 10pt"><o:p></o:p>
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'>Correlation=20
 and Regression<span=20
 style=3D'FONT-SIZE: 10pt; FONT-FAMILY: "Times New =
Roman",serif'>&nbsp;<o:p></o:p>
 <p class=3DMsoNormal=20
 style=3D"TEXT-ALIGN: justify; MARGIN: 0in 0in 0in 21.25pt; =
LINE-HEIGHT: 12pt; TEXT-AUTOSPACE: ideograph-numeric; TEXT-INDENT: =
-21.25pt; mso-list: l0 level1 lfo10; tab-stops: list 21.25pt"><span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">i.<span=20
 style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
COLOR: black'>Definition=20
 of Correlation and Regression<span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'><o:p></o:p>
 <p class=3DMsoNormal=20
 style=3D"TEXT-ALIGN: justify; MARGIN: 0in 0in 0in 21.25pt; =
LINE-HEIGHT: 12pt; TEXT-AUTOSPACE: ideograph-numeric; TEXT-INDENT: =
-21.25pt; mso-list: l0 level1 lfo10; tab-stops: list 21.25pt"><span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">ii.<span=20
 style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
COLOR: black'>The=20
 relationship between Correlation and Regression<span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'><o:p></o:p>
 <p class=3DMsoNormal=20
 style=3D"TEXT-ALIGN: justify; MARGIN: 0in 0in 0in 21.25pt; =
LINE-HEIGHT: 12pt; TEXT-AUTOSPACE: ideograph-numeric; TEXT-INDENT: =
-21.25pt; mso-list: l0 level1 lfo10; tab-stops: list 21.25pt"><span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">iii.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
COLOR: black'>Correlation=20
 Coefficient: Values<span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'><o:p></o:p>
 <p class=3DMsoNormal=20
 style=3D"TEXT-ALIGN: justify; MARGIN: 0in 0in 0in 21.25pt; =
LINE-HEIGHT: 12pt; TEXT-AUTOSPACE: ideograph-numeric; TEXT-INDENT: =
-21.25pt; mso-list: l0 level1 lfo10; tab-stops: list 21.25pt"><span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">iv.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
COLOR: black'>Examples=20
 of Correlation<span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'><o:p></o:p>
 <p class=3DMsoNormal=20
 style=3D"TEXT-ALIGN: justify; MARGIN: 0in 0in 0in 21.25pt; =
LINE-HEIGHT: 12pt; TEXT-AUTOSPACE: ideograph-numeric; TEXT-INDENT: =
-21.25pt; mso-list: l0 level1 lfo10; tab-stops: list 21.25pt"><span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">v.<span=20
 style=3D'FONT: 7pt "Times New =
Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
COLOR: black'>Interpretation=20
 of a Regression Equation<span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'><o:p></o:p>
 <p class=3DMsoNormal=20
 style=3D"TEXT-ALIGN: justify; MARGIN: 0in 0in 0in 21.25pt; =
LINE-HEIGHT: 12pt; TEXT-AUTOSPACE: ideograph-numeric; TEXT-INDENT: =
-21.25pt; mso-list: l0 level1 lfo10; tab-stops: list 21.25pt"><span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">vi.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp;&nbsp;&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
COLOR: black'>Step-by-Step=20
 example of How to Do a Regression Analysis<span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'><o:p></o:p>
 <p class=3DMsoNormal=20
 style=3D"TEXT-ALIGN: justify; MARGIN: 0in 0in 0in 21.25pt; =
LINE-HEIGHT: 12pt; TEXT-AUTOSPACE: ideograph-numeric; TEXT-INDENT: =
-21.25pt; mso-list: l0 level1 lfo10; tab-stops: list 21.25pt"><span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-fareast-font-family: "Times New Roman"'><span=20
 style=3D"mso-list: Ignore">vii.<span=20
 style=3D'FONT: 7pt "Times New Roman"'>&nbsp;&nbsp;=20
 <span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
COLOR: black'>Exercise<span=20
 style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New =
Roman",serif'><o:p></o:p></td></tr></table></div>
<span=20
lang=3DEN-MY=20
style=3D"BACKGROUND: white; COLOR: black; mso-ansi-language: =
EN-MY"><o:p><font=20
size=3D3 face=3D"Times New Roman">&nbsp;</o:p>
<font=20
size=3D3>ABOUT =
THE=20
FACILITATOR <o:p></o:p>
<font=20
size=3D3>Selvaraj =
<span=20
lang=3DEN-MY style=3D"COLOR: black; mso-ansi-language: EN-MY">&nbsp;is a =
highly=20
qualified technical trainer in the areas of Continuous Improvement and =
Quality=20
Excellence. He believes in interactive and fun filled training. His method =
of=20
training is sharing rather than lecturing. With 23 years of experience in =
the=20
field of Manufacturing Improvement &amp; Quality Excellence covering areas =
of=20
Design, Material Selection, Tooling, Machine &amp; Process Engineering,=20
Production and Supply Chain Management, Selvaraj B uses lots of real life=20
examples. Selvaraj &nbsp;started his career in 1989 as a Mechanical =
Engineer and=20
in 23 years, has worked in 3 MNC companies that are World Class, i.e. =
Matsushita=20
(Japanese), Robert Bosch (German) and Entegris (American) up to the level =
of an=20
Operations Manager. Selvaraj B is a certified HRDF trainer. His strength =
is=20
combining the intricacies and details of technical training with highly =
humorous=20
anecdotes for maximum training effectiveness.&nbsp;&nbsp; <span=20
lang=3DEN-MY style=3D"mso-ansi-language: =
EN-MY"><o:p></o:p>
&nbsp;<o:p></o:p>
AMONG=20
HIS NOTABLE ACHIEVEMENTS ARE:<o:p></o:p>
1.=20
Leading Gold Medal winning teams to NPC conventions =96 1995 -=20
2002<o:p></o:p>
2.=20
Certified MTM and Ergonomics practitioner - 1997<o:p></o:p>
3.=20
Tooling &amp; plastic parts design standardization - =
2000<o:p></o:p>
4.=20
Awarded best Six Sigma Champion award in 2006 for promoting successful =
Sigma=20
projects =96 2006<o:p></o:p>
5.=20
Certified Trainer with Napoleon Hill International - 2007 =
<o:p></o:p>
6.=20
Certified Lean Sigma Champion&nbsp; - 2010<o:p></o:p>
7.=20
Competent Communicator &amp; Humorous Speech Division N Champion in =
Toastmasters=20
International =96 2012<o:p></o:p>
8.=20
Certified Six Sigma Master Black Belt - 2016<o:p></o:p>
9.=20
Member of the Society of Plastics Engineers<o:p></o:p>
10.=20
Member of the Institute of Engineers Malaysia <o:p></o:p>
11.=20
Certified NLP Practitioner - 2016 <o:p></o:p>
12.=20
Certified VDI Quality Systems auditor - 1997<o:p></o:p>
13.Certified=20
Industry 4.0 Professional accredited by the US-based<o:p></o:p>
<a=20
href=3D"https://www.linkedin.com/company/international-institute-of-executi=
ve-careers-iiec-"><span=20
class=3D15>International=20
Institute of Executive Careers=99 (IIEC)</a><o:p></o:p>
<o:p>&nbsp;</o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-ansi-language: EN-MY'>AMONG=20
HIS NOTABLE IMPROVEMENTS PROJECTS ARE:<o:p></o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-ansi-language: EN-MY'>1.=20
Consolidating the Plastic Injection Moulding sections into 1 department =
&amp;=20
leading it =96 Bosch Bayan Lepas <o:p></o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-ansi-language: EN-MY'>2.=20
Motivating and guiding numerous scrap reduction &amp; quality improvement =
teams=20
=96 Bosch Bayan Lepas, Automotive Lighting Bayan Lepas =
<o:p></o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-ansi-language: EN-MY'>3.=20
Reduction of manufacturing lead time from 28 days to 3 days =96=20
Entegris<o:p></o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-ansi-language: EN-MY'>4.=20
Cycle time reduction projects =96 Bosch, Entegris<o:p></o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-ansi-language: EN-MY'>5.=20
Lean improvement projects =96 Signature Kitchen Sdn. Bhd. KL, Anshin =
Precision=20
Sdn. Bhd. Shah Alam, Silverstone Berhad Taiping.<o:p></o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-ansi-language: EN-MY'>6.=20
Starting a new factory of 200 headcount for Silicone Wafer Process =
Carrier=20
comprising of Manufacturing, Maintenance, Engineering, Tooling, =
Production=20
Planning &amp; Continuous Improvement Department =96 Entegris Kulim=20
Hi-Tech.<o:p></o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-ansi-language: EN-MY'>7.=20
Guiding and inspiring numerous quality improvement and cost reduction =
teams to=20
State level and National level competition and recognition.=20
<o:p></o:p>
<span=20
lang=3DEN-MY=20
style=3D'FONT-SIZE: 12pt; FONT-FAMILY: "Times New Roman",serif; =
mso-ansi-language: EN-MY'>8.=20
Setting up &amp; developing a World Class Manufacturing team for clean =
room=20
fittings manufacturing =96 Entegris Kulim Hi-Tech <o:p></o:p>
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size=3D3>&nbsp;
<font=20
size=3D3>We hope you find it informative and interesting and we=20
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<font=20
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Please call=20
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