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 164Simulate with Calculator/CD

Choosing Random Numbers

Pg. A6 of text

1. Number subjects from 1 to n2. 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”

1100%

n

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 population1. Sampling Bias: from sampling method

(e.g., nonrandom samples)2. Nonresponse bias: some subjects

cannot be reached or decline3. Response bias: subject gives incorrect

response or question is misleading

Exs. # 4.24, 4.29