Unit 3: Analyzing One Variable Data

Question 1

placebo

Answer 1

a treatment given to the control group that has no effects

Question 2

control group

Answer 2

does not receive treatment in the study

Question 3

simple random sample

Answer 3

sample selection is completely random

Question 4

systematic random sample

Answer 4

random starting point but then follows a pattern using sampling interval (e.g. randomly selecting a student, then selecting every 3rd student) sampling interval = total pop/sample size

Question 5

stratified random sample

Answer 5

• population divided into strata (groups) and a random sample is taken from each stratum
• strata may be chosen by some criteria (e.g. students organized by grade and random students from each grade is selected)
• % of group of entire population must equal % of group of sample (e.g. 250 grade 9 students out of 1000, so if the sample size is 100, there should be 25 grade 9 students)

Question 6

cluster random sample

Answer 6

population divided into clusters (groups) and entire clusters are randomly selected (e.g. classes are clusters, and a random cluster (class) may be selected)

Question 7

multi-stage random sample

Answer 7

groups selected using simple random method and within each group, simple random method is used again to select the sample

Question 8

destructive sampling

Answer 8

samples are destroyed in the process of testing (e.g. tasting a few cookies from a batch)

Question 9

convenience sample

Answer 9

samples selected based on accessibility and proximity to researcher; samples are selected based on convenience

Question 10

voluntary response samples

Answer 10

samples are self-selected volunteers (biased b/c they likely have a strong opinion on the topic)

Question 11

longitudinal study

Answer 11

study that focuses on a small group over a long period of time

Question 12

cross-sectional study

Answer 12

study that considers a wide range of individuals at the same time

Question 13

double blind test

Answer 13

neither the researcher nor the participant know which group they’re in until the conclusion

Question 14

sampling bias

Answer 14

• sample does not represent population accurately
• when random sampling techniques are not used
• to avoid: use random sampling techniques

Question 15

non-response bias

Answer 15

• bias occurs when not all surveys are returned; sample typically only consists of people who feel strongly about the topic
• to avoid: researchers must make sure sampling process is truly random

Question 16

household bias (aka measurement bias)

Answer 16

• one type of respondent is overrepresented because different size groups are polled equally
• to avoid: use stratified random sampling

Question 17

response bias

Answer 17

• bias resulting from how the questions are designed and asked (e.g. (mis)leading questions)
• to avoid: make sure questions are designed fairly

Question 18

How do you calculate bin width?

Answer 18

Range divided by number of intervals

Question 19

How would you tell which values fall within standard devation?

Answer 19

If it falls within the range of the mean +/- standard deviation