Weekly Homework #7

  1. In what sense is the linear correlation coefficient the “statistical essence of science”? Give a specific answer.
  2. Which of the following relationships is likely to be direct and which is inverse? Explain your answer.
    1. Amount of TV viewing per week and college GPA
    2. Age and visual ability
    3. Advertising money and sales volume within a company
    4. Height of parents and height of their children
    5. Economic frustrations and social class
  3. In your own words, describe the relationship between z scores and correlation.
  4. Examine the following data set and answer the questions:

Daughter’s height (y)

Mother’s height (x)

60

62

66

67

65

64

66

66

67

65

63

63

69

65

63

61

61

59

65

67

  1. Draw a scatterplot for these data. Comment on whether or not it looks like there is a linear relationship and, if so, whether it is positive or negative.
  2. Using Excel, find the correlation between the mother’s heights. Do the value and the sign make sense based on the scatterplot.
  3. Using Excel, find the intercept and slope for the regression equation.
  4. The equation you found in part c might be useful for predicting the height before the daughter is fully grown. Use the equation to predict the height of the daughter of a mother who is 63 inches tall.

5. View the following source and answer the questions.

  1. What two variables were measured for each person to provide this result?
  2. Explain what is meant by r = .44.
  3. What is meant by the word significantly as it used in the article?
  4. The authors did not provide a regression equation relating the two variables. If a regression equation were to be found for the two variables, which one do you think would be the explanatory variable?