1.1

1 According to our lecture, statistics is the numerical summary of data.

3 An individual.

5 A statistic.

7 Parameter.

9 Parameter.

11 Statistic.

13 Parameter.

15 Qualitative.

17 Quantitative.

19 Quantitative.

21 Qualitative.

23 Discrete.

25 Continuous.

27 Continuous.

29 Discrete.

39 Population: All U.S. teenagers aged 13-17; Sample: The 1028 teenagers contacted by the Gallup Organization.

40 Population:Every bottle of Coca-Cola filled on October 16 in that specific machine; Sample: The 50 bottles randomly selected by the quality-control manager.

41 Population:Every soybean plant planted by the farmer; Sample: The 100 plants he selects to weigh the soybean of each.

42 Population: All households within the U.S.; Sample: The 50,000 households surveyed by the U.S. Census Bureau

43 Population: All women aged 27-44; Sample: 7373 of these women with hypertension.

1.2

9 Observational.

10 Experiment.

11 Experiment.

12 Observational.

13 Observational.

14 Experiment.

17

  1. This type of observational study is cohort because researchers found a group of people (1739) which they observe over an extended period of time to determine whether there is a link between the level of happiness and the risk of heart disease. Their observations don’t interfere or influence how they behave throughout this time.

  2. The response variable is the risk of heart disease, the explanatory variable is the level of happiness.

  3. The common factor (genetics) is considered a lurking variable, meaning it is common to both the level of happiness and the risk of heart disease. This means that it was not initially part of the observations, but can influnce both variables independently.

20

  1. This is an observational study because researchers observed both men and women during an extended period of time (7 years) without changing their behavior throughout the study, making it a cohort study.

  2. The response variable is the how much weight participants gain over 7 years, the explanatory variable is whether they are married or cohabitate.

  3. Lurking variables in this case can be genetics, the culture in which they live in, their consumption behavior, their active life.

  4. No, getting married does not necessarily lead to gaining more weight. It can happen in some cases, but the two are not necessarily associated.