topic 1 basic statistical concepts.pdf

8/10/2019 Topic 1 Basic Statistical Concepts.pdf

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At the end of this session, each student should be

able to:

1. Define statistics,

2. Describe basic statistical concepts,

3. Understand the four scales of measurements,

and

4. Match statistics to the appropriate scale ofmeasurement


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DATA

As a tool in making decisions:

Research objectives

Research hypotheses

Statistics as a process to:

Make

informeddecisions

Collect

Analyze

Present

Interpret


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Problem Statement

Research Design/

Methodology

Population &

Sample

Instrumentation

Data Collection

Data Analysis &

Presentation

Interpretation &

Reporting


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A collection of tools and techniques that are used

to convert data into meaningful information.

Data

Statistical Tools

Descriptive

Inferential

Role of Statistics

Information


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1. Purpose

DescriptiveInferential

2. Assumption on normality

ParametricNonparametric

3. Number of Variables

UnivariateBivariate

Multivariate

Depends on:


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Population

Sample

Comprises ALL

elementsindividual

or objects

A sub-set of

population

Statistics

Parameters


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Measures Parameter Statistic

Number of cases N n

Mean

Variance 2 s2

Standard deviation s

Correlation coefficient r


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1. Probability samples

Simple random samples

Stratified random samples

Systematic samples

Cluster samples

2. Non-probability samples

Convenient samples Purposive samples


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Characteristics studied that assume different values fordifferent elements

Perceived quality of

ICT facilities

Quality of

work life

Independent

Variables

Dependent

Variable

Job characteristics:

Work condition

Job demand

Job control

Demography:

Gender

Job tenure

Occupational status

Research Conceptual Framework


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Perceived quality of

ICT facilities

Careercommitment Quality ofwork life

Independent

VariablesIntervening

Variable

Dependent

Variable

Job characteristics:

Work condition

Job demand

Job control

Demography:

Gender

Job tenure

Occupational status

OR

Research Conceptual Framework

X Y

M

X Y

M

Mediator Moderator


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1. Quantitative or Continuous Variables

A variable that can be measured numerically

(Numeric)

Can be classified into: Discrete variable

Continuous variable

2. Qualitative or Categorical Variable

A variable that cannot assume a numericalvalue but can be classified into 2 categories

(Alpha numeric)


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Variable Data

Primary

Basic elements used in statistical analysis

Secondary


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1. Experiments

2. Telephone survey

3. Mail questionnaires4. Online questionnaires

5. Direct observation

6. Personal interviews


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Nominal

The lowest scale

Numbers assigned to identify attributes

No order/sequence

Ordinal Numbers assigned in ranking order

Arrange from lowest to highest or vice versa

Interval

Arbitrary zero (no absolute zero)

Zero does not represent absence of the characteristic Ratio

The highest scale

True zero (represents absence of the characteristic)


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Variable

Attributes

Values

Ethnicity

ChineseMalay Indian

1 2 3

(For CategoricalNominal and Ordinal)


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Data

Sequence?Alpha

Numeric

NumericZero?

Nominal

Ordinal

Interval

Ratio

(Two-step questions)

What is thedata type?


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Exercise:

What are the scales of measurement for these

variables?

1. Program of study

2. Speed (km/hr)

3. Motivation scores

4. Income categories

5. Number of SMS received

6. Marital status

7. Quality of work life scores

8. Socio-economic status

9. Perception scores

10. Membership status

Nominal

Ratio

Interval

Ordinal

Ratio

Nominal

Interval

Ordinal

Interval

Nominal


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Major Research

Concerns

T-Test ANOVA

Mann-Whitney

Kruskal Wallis

Comparisonbetween Groups

Describe Phenomenon Frequency/Percent

MCT

MD

Chi-square

Spearman rank correlation

Pearson PM correlation

Regression Analysis

Relationship

between Variables


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Data # Groups/ Inde-

type Question variables Scale pendence Statistics

DATA

Multiple

categories

Differences

Relationships

Two groups

Multiple groups

or variables

Independent

Dependent

Independent

Dependent

Twovariables

Multiple

variables

Metric

Rank

Dichotomous

Non-

metric

Metric

Ind. t-test

Paired t-test

One-way ANOVAFactorial ANOVA

Repeated-

Measure ANOVA

Pearsons r

Spearmans r

Point biserial

Multiple

regression

Chi-Square


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Scales of Measurement

T-Test Interval/Ratio Nominal/Ordinal (k=2)

ANOVA Interval/Ratio Nominal/Ordinal (k>2)

Chi-square Nominal/Ordinal Nominal/Ordinal

(At least one of the scales is Nominal)

Spearman Rho Rank Ordered Rank ordered

Interval/Ratio Interval/Ratio (x Normal)

Pearson Correlation Interval/Ratio Interval/Ratio

Regression Interval/Ratio Interval/Ratio

Statistics Dependent Independent


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topic 1 basic statistical concepts.pdf

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