1. Chapter 2 Samples and Populations
Sample vs. Population
Design
Methods
Construction
Errors

2. Population/Target Population
Sample vs. Population
Population – the totality of subjects under consideration
Target Population – consists of all subjects considered in the study
Sample – a portion or a subset of the population for data collection and analysis
Population/Target Population
Sample

3. Young-adults and older
Sample vs. Population
Population
Target Population
Sample
Kalamazoo
Young-adults and older
House
-holds

4. Census vs. Sample Survey
Census – collection of data using all subjects in the population
Sample Survey – collection of data from a representative sample of the population
Population/
Target Population
Sample
Note: Random Samples should be representative of the population

5. Study Design or Protocol Design
Steps involved in solving problems How do I solve this problem? ? ? Study design is done prior to data collection. It involves methods in data collection, analysis of the data and conclusions to be made.

6. Probability vs. Non-Probability Sampling
Probability Sampling – subjects are chosen by chance
Non-probability Sampling – can be used for informal and less scientific studies
Note: Non-probability sampling tend to be less representative of the target population

7. Methods in Probability Sampling
Simple Random Sampling (SRS) – samples are randomly selected from the population
K-in-1 Systematic Sampling – Every kth subject is chosen
Stratified Random Sampling – population is divided into subgroups called strata and SRS chosen from each strata
Cluster sampling – population is divided into subgroups called clusters and clusters are randomly chosen as samples.

8. Example: Household Expenditures in Michigan
Target Population : Households in Michigan
Simple Random Sampling – randomly selecting the sample from a list of households
Systematic Sampling – every 10th household
Stratified Sampling – take samples from each county
Cluster Sampling – selecting counties in Michigan

9. Factors to be considered in a Survey
Money
Time
Content/Information

10. Types of Surveys Type of Survey Advantages Disadvantages
Face-to-face Interview
Explain questions, explore issues, make observations, use visual aids
Expensive, need interviewer training
- at home or
work
Accuracy, better sampling
Expensive
- in public areas
Cheaper, more people in less time
Less representative sample
Telephone Interview
Accurate, cheap
No personal observation
Written Questionnaire
Cheapest per respondent
Bias from low response rate
- by mail
Allows anonymity
Slow
- by
Cheaper, quicker results
- web survey
Quicker data processing
Need computing expertise

11. Construction of Questionnaire
Is the question understandable?
Are you gathering knowledge or attitude?
Are the questions loaded?
Do the questions ask for sensitive information?
Note: An accurate answer leads to a good study and it starts from asking important questions correctly.

12. Types of Survey Errors
Coverage errors – sampling frame excludes some segments of the target population
Non-response errors – can cause bias in survey results
Measurement errors – occurs when respondents answer ‘incorrectly’