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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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