HW1

1.1

• 1.Logic of uncertainty - You answer questions and measure confidence in these answers by looking and analyzing specific data.

• 3. An individual (…)
• 5. . A(n) statistic is a numerical summary of a sample. A(n) parameter is a numerical summary of a population
• 7. parameter
• 9. statistic
• 11. parameter
• 13. statistic
• 15. qualitative
• 17. quantitative
• 19. quantitative
• 21. qualitative
• 23. discrete
• 25. Continuous
• 27. continuous
• 29. discrete
• 39. Population:American teenagers between 13 to 17 years. Sample: 1028 teenagers who are 13 to 17 years of age and live in the United States
• 40. Population:bottles of Coca-Cola that were filled October 15 Sample:the 50 bottles the manager selected
• 41. Population:The farmers total soybean crop. Sample:the soybeans from the 100 randomly sampled plants.
• 42. Population:all households in the US. Sample:the 50,000 households sampled for the survey.

1.2

• 13. Observational
• 14. Experiment
• 15. Experiment
• 16. Observational
• 17. A: Cohort study (over time study of sample/population, prospective) B:Response variable is heart diseases (the risk of getting them). The explanatory variable in this study is the level of happiness. C:The sentence means that the researchers need to moderate the findings of the study, so that the explanatory and response variable can have an association to each other but not conclude a causal relationship. This is due to genetics being a lurking variable that can affect both the explanatory variable and the response variable.
• 18. A:Cross-sectional study (the data is collected over a short period of time and individuals within the sample are compared in order to conclude) B: The response variable is the occurence of skin cancer and the explanatory variable is the daily coffee consumption.
      C: As this was an observational study the researchers could not control the variables. If they consider other variables such as lifestyle and demographic as confunding variables that could affect the explanatory variable or lurking variables that could affect the relationship between the explanatory and the response variable, they have to adjust for these because they could only claim association between the variables they were studying.