Simple Linear Regression and Correlation: Exercises 16.1, 16.7, 16.28, and 16.100
Multiple Regression: Exercises 17.2 and 17.5
Directions:
-Submit your answers in a Microsoft Excel workbook, with each problem on a separate worksheet.
-Label each tab in the workbook with the exercise number.
-Highlight the answers in yellow and provide an interpretation in a text box.
-Cite any sources using the APA format on a separate page
16.1
The term regression was originally used in 1885 by Sir Francis Galton in his analysis of the relationship between the heights of children and parents. He formulated the “law of universal regression,” which specifies that “each peculiarity in a man is shared by his kinsmen, but on average in a less degree.” (Evidently, people spoke this way in 1885.) In 1903, two statisticians, K. Pearson and A. Lee, took a random sample of 1,078 father–son pairs to examine Galton’s law (“On the Laws of Inheritance in Man, I. Inheritance of Physical Characteristics,” Biometrika 2:457–462). Their sample regression line was Son’s height = 33.73 + .516 × Father’s height
a. Interpret the coefficients.
b. What does the regression line tell you about the heights of sons of tall fathers?
c. What does the regression line tell you about the heights of sons of short fathers?
16.7
Florida condominiums are popular winter retreats for many North Americans. In recent years, the prices have steadily increased. A real estate agent wanted to know why prices of similar-sized apartments in the same building vary. A possible answer lies in the floor. It may be that the higher the floor, the greater the sale price of the apartment. He recorded the price (in $1,000s) of 1,200 sq. ft. condominiums in several buildings in the same location that have sold recently and the floor number of the condominium.
a. Determine the regression line.
b. What do the coefficients tell you about the relationship between the two variables?
16.28 (Refer to Exercise…