Suppose that n = 484 i.i.d. observations for (Yj, X;) yield the following regression results: Y= 32.59 + 65.86X, SER= 15.54, R² = 0.74 (16.1) (13.3) Another researcher is interested in the same regression, but he makes an error when he enters the data into the regression: He enters each observation twice, so he has 968 observations (with observation 1 entered twice, observation 2 entered twice, and so forth). Which of the following estimated parameters change as result? (Check all that apply) O A. The R2 of the regression. B. The standard error of the regression (SER). O C. The estimated intercept and slope. D. The standard errors of the estimated coefficients. Using the 968 observations, what results will be produced by his regression program? Y = 32.59 + 65.86X, SER = R = 0.74 (Round your responses to two decimal places)

Interpret the intercept and the coefficients of D1 and D2 in the regression above.

You’ve run a regression of the effect of years of schooling on wages for a sample of 102,498 individuals. Your regression results are:   wage = 2.051    +    0.29 × Years of Schooling            (0.0802)     (0.0168)   Interpret the coefficients from this regression. (The coefficients are shown in the regression equation itself.)   The numbers in parentheses under the equation are the standard errors of the estimates for the respective coefficients. Determine whether each coefficient is statistically significant at each of the conventional significance levels.   The R2 for this regression is 0.284. Interpret the meaning of this value.

A regression was run to determine if there is a relationship between hours of study per week (x) and the final exam scores (y). The results of the regression were: y=ax+b a=5.865 b=25.06 r²=0.81 r=0.9 Use this to predict the final exam score of a student who studies 4.5 hours per week, and please round your answer to a whole number.

| Find the regression lines of Y on X and X on Y for the following data. EX = 70, EY = 83, EX? = 590, EY² = 755, EXY= 640, n= 10.

​A set of n = 15 pairs of X and Y scores has SSX = 10, SSY = 40, and SP = 30. What is the slope for the regression equation for predicting Y from X?   a.  ​10/30   b.  ​10/40   c.  ​40/10   d.  ​30/10

An automobile rental company wants to predict the yearly maintenance expense (Y) for an automobile using the number of miles driven during the year () and the age of the car (, in years) at the beginning of the year. The company has gathered the data on 10 automobiles and run a regression analysis with the results shown below:.   Summary measures       Multiple R 0.9689       R-Square 0.9387       Adj R-Square 0.9212       StErr of Estimate 72.218                 Regression coefficients         Coefficient Std Err t-value p-value Constant 33.796 48.181 0.7014 0.5057 Miles Driven 0.0549 0.0191 2.8666 0.0241 Age of car 21.467 20.573 1.0434 0.3314 Use the information above to estimate the annual maintenance expense for a 10 years old car with 60,000 miles.

A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y).The results of the regression were:y=ax+b a=-1.34 b=36.954 r2=0.966289 r=-0.983 Use this to predict the number of situps a person who watches 5 hours of TV can do (to one decimal place)

A regression was run to determine if there is a relationship between hours of study per week (xx) and the test scores (yy).The results of the regression were:y=ax+b a=6.686 b=35.26 r2=0.6084 r=0.78 Use this to predict the final exam score of a student who studies 8.5 hours per week, and please round your answer to a whole number.

A regression was run to determine if there is a relationship between hours of study per week (xx) and the final exam scores (yy).The results of the regression were: y=ax+b a=5.614 b=32.79 r2=0.808201 r=0.899 Use this to predict the final exam score of a student who studies 1 hours per week, and please round your answer to a whole number.