stats 5.1

Step 1 of a Simple Random Sample

Find the Target Population and sample

Step 2 of a simple random sample

how are sampled individuals different from the population

Step 3 of a simple random sample

talk about it leads to over or under estimation

step 1 of a Stratified Random sample

divide the population into groups that share a common characteristic

step 2 of a Stratified sample

randomly pick people from each group

Step 3 of Stratified Random Sample

Combine all the chosen people from each group into a sample

Step 4 of a Stratified Random Sample

Use the sample to collect data or make conclusions

Step 1: Cluster Random Sample

Divide the population into clusters (groups)
Example: Classrooms, neighborhoods

Step 2: Cluster Random Sample

Randomly choose some of the groups

Step 3: Cluster Random Sample

collect data from all the people in the groups you selected

Step 4: Cluster Random Sample

Use the information from the selected clusters to draw conclusions about the whole population

Step 1: Systematic Random Sample

Put everyone in the population in a list or order
Example: alphabetical list, roster, or any ordered list

Step 2: Systematic Random Sample

Choose a random starting point on the list
(make sure the selection is fair before following the pattern)

Step 3: Systematic Random Sample

After picking the starting point, you go down the list at regular numbers like every 5th or 10th person until you reach the sample size

Step 4: Systematic Random Sample

Gather information from everyone you picked to analyze it to learn about the whole population

Step 1: What is an explanatory variable

A variable that helps explain why or how somethings changes
Example: Hours studied

Step 2: What is an Response Variable

Variable that shows the result or outcome in a situation
Example: Test Score

Step 3: Experimental Unit

The Person, Object, or thing that receives a treatment in an experiment
Example: Plant study, Plant is an experimental unit