CHAPTER 1 : INTRODUCTION TO STATISTICS
What is Statistics?
Process of converting data into useful information
1) Collect
2) Organize
3) Summarize
4) Presentation
5) Intepretation
Types of Statistics
Descriptive Statistics
Inferential Statistics
Traditional approach
Collect -> Interpret data
Prediction/generalization about a population based on sample
Making inferences from data
Types of Variables
Qualitative
Quantitative
when observation fall into separate distinct categories
I.e.
Categorical
Non-numerical
when observations are measurements/numericals
I.e.
Discrete
Continuous
Separated values
Values in range
Scale of Measurement
Ordinal
Interval
Nominal
Ratio
Classify into categories
E.g.
Gender
Race
Religion
Categories that can be ranked
I.e
Education level
Cancer stage
Likert scales
I.e.
Temperature
IQ Scores
I.e.
Weight
Height
Salary
Sources of Data
Primary Data
Secondary Data
Data obtained directly from the respondents
Researcher carried out experiments/surveys
Pro: Accurate, reliable & up-to-date
Con: Time-consuming, costly, manpower
Pro: Save time & effort, cut cost
Con: May not meet objectives
Data obtained from another sources
Data Collection Method
Telephone
Direct Observation
Personal/Face-to-face interview
Questionnaire
Sampling
Method/Techniques
Why need sampling?
When population is large, costly to do research on entire population
So, select a sample to represent the population
Probability sampling
Non-probability sampling
Systematic Random Sampling (SyRS)
Stratified Sampling (SS)
Simple Random Sampling (SRS)
Cluster Sampling (CS)
Judge mantel
Snowball
Convenience
Quota