C:\Users\jfloj\Downloads\DATA7-20.xls

#1) Data 7-20 has data on NBA (National Basketball Association) players' salaries andtheir determinants for 1989-90. The dependent variable is salary is in thousands ofdollars.The explanatory variables are:

YRS = the number of years in the NBA.

HT = height of the player in inches.

WT = weight of the player in inches

AGE = age of the player in 1989MIN = number of minutes played during the season

AVGPNTS = average points per game played

FGPRCNT = fraction of shots that each player made (1.000 = perfect shooting)POINTS = total points scored in the 1989-1990 season

ALLSTAR = 1 if the player was on the all star team in 1990-1991, zero otherwise.

WINTM = Dummy variable =1 if the team that the player is on won at least 45 games in1989-1990. zero otherwise.

REBOUNDS = The total number of rebounds by each player.

Do not include other variables that may be in the sheet that are not listed above.

a. Identify and explain the expected relationship between the dependent variable andeach independent variable.

b. Run the regression and show the results. Cut and paste the Excel Results (no data).

c. Give an interpretation for coefficients (both the sign and the magnitude of the coefficient) ofthe dummy variables

"WINTM," and "ALLSTAR." Do the signs of thecoefficients agree with your expectations? Explain.

2) DATA7-2 tabulates data on salaries and employment characteristics 49employees in a certain company. The dependent variable is WAGE (in $).The explanatory variables are (do not include other variables in the sheet not listed below in the regression) :

EXPER = Number of years at the company (Range 1 - 23)AGE = Age of employee (25 - 64)

GENDER = 1 for male and 0 for female

RACE = 1 For white, 0 for non-white

a. Identify and explain the expected relationship between the dependent variable andeach independent variable.

b. Generate a variable "experience X gender."

c. Run the regression and cut and paste the results only (no data). Do males have a higher starting salarythan females? Do males experience a faster increase in their salary per every yearof experience than females? Make sure you identify which part of the regression results leads you to that conclusion.

d. Interpret the coefficient of "experience X gender." Make sure you explain what the sign implies and what the magnitude (the size of the number)

solve this please