Chapter 5- Producing Data
Ap Stats Chapter 5 - Producing Data
Observational Study - Observe, but don’t influence (subjects select their own group/treatment)
Experiment - Deliberately impose a treatment on individuals to observe their response
5.1 Designing Samples
Population - entire group that we want info about
Sample - the part of the group examined
Census - contacts every individual
Sampling - Studying a part to get info about the whole
Voluntary response sampling - people who care strongly will answer (Call-in polls, on-line polls, etc...)
biased by strong opinions
Convenience Sampling - get individuals who are easiest to reach; is biased (ex: interview at the mall)
Bias - systematically favors certain outcomes (unbiased if mean of sample = mean of pop)
Homework: p 333 1 – 8
Simple random sample (SRS) of size n: n individuals from the population chosen in a way that each
set of n individuals has an equal chance to be selected
Techniques: Draw names from a hat
Use computer programs
Use a table of random digits (back cover of textbook)
Using a Random Number Table to choose an SRS: (SRS survey term NOT experiment!!!)
Assign a label to every individual
1) Enter Table B at random
2) Pick numbers until you have obtained the amount of numbers you want
3) List the members of your sample
SRS’s
Probability sample - chosen by chance
Stratified random sample - divide into groups and get separate SRS for each group
Cluster sampling - divide into groups, randomly select a group and then use all individuals in the cluster
Are these SRS’s?
1) 6 picked out of a hat from 36 students
2) 6 students from same row in a classroom
3) every other name from an alpha list
Cautions about Sample Surveys: (doesn’t eliminate bias)
1. Undercoverage - some groups of the population are left out (homeless, those without phones, non-readers of the magazine)
2. Nonresponse - an individual cant be contacted or doesn’t cooperate
3. Response Bias - affected by behavior of interviewer and/or interviewee - sex, race, uncomfortable questions, faulty memories. Anything in the way data was collected that influences response.
4. Wording of questions – can’t be confusing or biased
Until you know the details of a poll, don’t trust it!!! Ex: exact questions used, sampling design, sample size, amount of non-response, data, etc….
Inferring from samples - larger samples = more accurate results to make guesses about the population.
***Samples vary, parameters are fixed!! s, r, mean
Homework: p 341 9, 10, 13, 14 p 347 15 - 20
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