Please enable JavaScript.
Coggle requires JavaScript to display documents.
CHAPTER 1 : INTRODUCTION TO STATISTICS - Coggle Diagram
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
Traditional approach
Collect -> Interpret data
Inferential
Statistics
Prediction/generalization about a population based on sample
Making inferences from data
Types of
Variables
Qualitative
when observation fall into separate distinct categories
I.e.
Categorical
Non-numerical
Quantitative
when observations are measurements/numericals
I.e.
Discrete
Separated values
Continuous
Values in range
Scale of Measurement
Ordinal
Categories that can be
ranked
I.e
Education level
Cancer stage
Likert scales
Interval
I.e.
Temperature
IQ Scores
Nominal
Classify into categories
E.g.
Gender
Race
Religion
Ratio
I.e.
Weight
Height
Salary
Sources of Data
Primary
Data
Data obtained directly from the respondents
Researcher carried out experiments/surveys
Pro:
Accurate, reliable & up-to-date
Con:
Time-consuming, costly, manpower
Secondary
Data
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
Probability sampling
Systematic Random Sampling (
SyRS
)
Stratified Sampling (
SS
)
Simple Random Sampling (
SRS
)
Cluster Sampling (
CS
)
Non-probability sampling
Judge mantel
Snowball
Convenience
Quota
Why need sampling?
When population is large, costly to do research on entire population
So, select a sample to represent the population