# GATHERING DATA Chapter 4. 4.1 Experiment or Observe?

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GATHERING DATA Chapter 4

4.1 Experiment or Observe?

Population and Samples  Population: Subjects of interest  Sample: Subset for whom we have data  Often want answers about large group but can’t measure all, so a subset is chosen  Use statistical techniques to infer conclusions

Observational Study Merely observe values of response and explanatory variables without doing anything to the subjects Ex. Cell Phone Study 1 (Page 155) Cell Phone Study 2 (Page 155)

Sample Survey  Select sample and interview  Observational study  Census is survey of entire population

Experiment  Assign subjects to certain experimental conditions and observe outcomes of the response variable  The experimental conditions, which correspond to assigned values of the explanatory variable are called treatments Ex. Cell Phone Study 3 (Page 155)

Experiments and Observational Studies  Experiment reduces lurking variables and thus outside influences  Experiments establish cause and effect, unlike observational studies  Some experiments impractical because of ethics, time, money, etc. Exs. # 4.2, 4.8 Page 162

4.2 What are Good and Poor Ways to Sample?

Sampling Frame & Sampling Design  Sampling frame – list of subjects in (hopefully total) population  Sampling design determines how sample is selected

Simple Random Sampling  Random Sampling – best way to get representative sample  Simple Random Sample – each possible sample of set size n has equal chance of being selected Ex. 4 Page 164 Simulate with Calculator/CD

Choosing Random Numbers Pg. A6 of text 1. Number subjects from 1 to n 2. Select numbers from random number table or random number generator (calculator or computer) 3. Include subjects with random numbers selected

Margin of Error for Population Percentages  Margin of Error – how well sample predicts population  For a random sample with n subjects, the margin of error is approximately Ex. A survey result states: “The margin of error is plus or minus 3 percentage points”

Convenience Samples: Poor Ways to Sample  Convenience Sample: survey sample that’s easy to get  Unlikely to represent population  Often severe biases  Results apply only to observed subjects

Convenience Samples: Poor Ways to Sample Volunteer Sample: most common convenience sample where subjects volunteer – not representative

Types of Bias in Sample Surveys Bias: Favoring parts of population 1. Sampling Bias: from sampling method (e.g., nonrandom samples) 2. Nonresponse bias: some subjects cannot be reached or decline 3. Response bias: subject gives incorrect response or question is misleading Exs. # 4.24, 4.29