Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total Obs. Intercept Xx HN Part I: Regression Basics SUMMARY OUTPUT A 1 2 3 Regression Statistics st 4 X556 8 0.97688814 df 0.939080583 3.277208147 5 1 3 4 Data Y 23 16 25 28 SS 672.9797 32.22028 Y hat Standard Error Coefficients t Stat P-value 2.531468531 3.604616 0.702285 0.533087 3.43006993 0.433317 7.915839 0.004203

Q) Plot the relationship between total operating costs and machine hours. Draw the regression line.

Big Time Corporation wanted to determine the relationship between its monthly operating costs and a potential cost driver, machine hours. The output of a regression analysis showed the following information (note: only a portion of the regression analysis results is presented here) SUMMARY OUTPUT Regression Statistics Multiple R 0.998041188 R Square 0.996086212 Adjusted R Square 0.994781616 Standard Error 917.1714273 Observations 5 ANOVA df SS MS F Significance F Regression 1 642276389.7 642276389.7 763.5208906 0.000104039 Residual 3 2523610.281 841203 427 Total 4 644800000 Coefficients Standard Errort Stat P-value Intercept 6679.617454 931.8558049 7.168080532 0.005592948 3714.03639 X Variable 9.796772265 0.354545968 27.63188178 0.000104039 8.66844876 What is variable cost per machine hour (rounded to the nearest cent)? OA. $6,679.62 OB. $917.17 OC. $9.80 OD. $.99 Lower 95% Upper 95.0% 9645.198517 10.92509577

A researcher's results are shown below using Femlab(labor force participation  rate among females) to try to predict Cancer (death rate per 100,000 population due to cancer) in the 50 US states. What is the R2 for this regression? Source of variation df ss ms f Regression 1 5377.836 5377.836 5.228879 residual 48 49367.389 1028.487   total 49 54745.225

Please fill in the blanks and select the correct answers over the image provided. Thank you

The parallel trends assumption is a crucial assumption for which the following estimators?     Multiple regression     Differences-in-Differences     First differences     Instrumental Variable

Using the regression model from the previous problem, what is the interpretation of the slope coefficient associated with Age?  Assume Salary is measured in $1,000's.

We will _______ if the test statistic lands in the unlikely region. Group of answer choices A. reject the alternative hypothesis B. fail to reject the null hypothesis C. cannot determine D. reject the null hypothesis and accept the alternative hypothesis

What is the​ least-squares regression line with the point (9,13) included in the data​ set?   Data Set    x      y 3   6   4   5   5   7   7   6   8   9   8   8   10   8   11   9   11   7   12   10   13   12   13   10   14   11     ​This is a reading assessment question.    .....   y hat = ______x + ______ ​Type integers or decimals rounded to 4 decimal places as​ needed

What is a residual for a multiple regression model and the data that is used to create it? Select one.   Question 3 options:   A statistic that explains the relationship between response and predictor variables   The predicted value of the response variable using the multiple regression model   A statistic that is used to evaluate the significance of the multiple regression model   The difference between the actual value of the response variable and the corresponding predicted value (regression error) using the multiple regression model