1. Turn in the Margin of Error worksheet.
Sampling Methods
Turn in the Margin of Error worksheet.

2. What is meant by “the population of Spud Potato Chips”?
What factors need to be considered when selecting a sample to test the population?

3. Drawing Conclusions
We found that the true mean average of the 28.3 gram bag was undersized.
Is it fair to say “The data shows that all Spud Potato Chip bags are underweight.”? Why?

4. Data Sampling Method
The way you choose your sample is as important as the way you test your hypothesis.

5. Sampling Design and Methods
This leads to another circular relationship.
You want to know something about a population.
You choose a sampling method and obtain a sample.
Collecting data from the sample provides some sort of estimate or conclusion about the population of interest.

6. Read through # 1
What is a census?

7. Census
Census - a study in which every member or unit of a population of interest is a participant.

8. Census
A census is the most accurate however there are some problems with a census.
What type of problems could occur?
Why do we not run a census for every study?

9. Sampling Techniques Simple Random Sampling Stratified Random Sampling
Systematic Sampling
Cluster Sampling
Convenience Sampling
Sampling method refers to the manner in which the sample of a population is selected.

10. Vocab Random - Some sort of system is used for selection.
Random Sampling - a strategy was used to select participants
Random number table - A table of numbers used in statistics.
Random number generator - technology that generates a number.

11. Simple Random Sampling
The researcher chooses the sample from the entire population of interest through a randomization technique
Example - drawing names out of hat, using a random number table or random number generator.
Caution: Random Sampling is not the same as random assignment of treatments (Having a systematic way of assigning treatment).

12. Stratified random sampling
The researcher separates the population into a number of strata (statistical subpopulations) and then takes a random sample within each stratum.
Example - Freshman, sophomores, juniors and senior classes or males and females.

13. Systematic Sampling
The researcher separates the population into evenly sized groups, randomly selects one participant in the first group, and then selects every nth participant.
Example: Number the student roster. Numbers one through 25 are placed in a bag and a number is drawn. Say the number 7 is chosen; every 25th person starting at number 7 will be selected.

14. Cluster Sampling
The researcher separates the population into groups and then randomly selects some of these groups to participate.
Example: the numbers of every classroom in school are placed in a hat, and five classrooms are selected. Every student in those five classrooms participates.

15. Convenience Sampling
Researcher selects participants based on easy accessibility.
Example: Researcher stands in one location at school and selects the first 50 students who walk by.

16. Inference
a conclusion reached on the basis of evidence and reasoning