1.1

1 Statistics is the practice of drawing conclusions and answering questions by organizing, summarizing, and investigating numbers and information.

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3 Individual

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5 Statistic & Parameter

6

7 Parameter because it refers to 18% of all of the 50 US governors.

8

9 Statistic because it refers to 32% of a sample of 1300 high school students.

10

11 Parameter because it refers to Ty Cobb’s average of his entire batting career as .366.

12

13 Statistic because it refers to 23% of a sample of 6076 adults.

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15 Qualitative

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17 Quantitative

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19 Quantitative

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21 Qualitative

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23 Discrete

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25 Continuous

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27 Continuous

28

29 Discrete

39 Sample: 1,028 teenagers of the ages 13-17 contacted in the US. Population: All teenagers 13-17 who live in the US.

40 Sample: 50 chosen Coca-Cola bottles filled on October 15th. Population: All Coca-Cola bottles filled on October 15th.

41 Sample: 100 randomly selected soybean plants. Population: All of the farmers soybean plants.

42 Sample: Results of 50,000 household demographics surveyed within the US. Population: All of the household demographics within the US.

43 Sample: 7,373 women surveyed with hypertension of the ages 27-44. Population: All the women ages 27-44 with hypertension.

1.2

9 Observational study because nothing is being manipulated.

10 Experimental study because the explanatory variable is changed between the two groups of rats.

11 Experimental study because the explanatory variable is changed between the two groups of students.

12 Observational study because nothing is being manipulated.

13 Observational study because nothing is being manipulated.

14 Observational study because nothing is being manipulated.

17

  1. Cohort study because the study takes place over a longer period of time.

  2. Response variable: chances of heart disease or no heart disease. Explanatory variable: chances of happiness or no happiness.

  3. This sentence means that there is a lurking variable that is effecting both variables and possibly causing confounding within the experiment.

20

  1. This is an observational study because neither variable is being manipulated to achieve results. This is a cohort study because it is taking place over a longer time period of 7 years.

  2. Response variable: Amount of weight gained. Explanatory variable: Relationship status.

  3. Some lurking variables in this study may include diet and exercise.

  4. We can conclude that getting married increases ones chances of gaining weight because based on the study both men and women who were married gained a more weight than the average single person.