Below is some of the regression output from a regression of the amount rental houses on an island rent for (expressed in thousands of $'s) based on the size of the house (expressed in square feet), whether the house has an ocean front view (VIEW = 1 if it has an ocean front view and = 0 if not), and an interaction term between the ocean front view dummy variable and the size of the house. If the estimated equation is   Price = 1474 + 0.31*Size + 1885*View + 0.10*(Size*View)   How much more (or less) does a 3900 square foot house that has an ocean front view rent for compared to a similar sized house without an ocean front view? (if the ocean front house rents for more then express your answer as a POSITIVE number; if the ocean front house rents for less then express your answer as a NEGATIVE number)  (please express your answer using 1 decimal places)

The line of best fit through a set of data is y = - 42.824 – 3.033x According to this equation, what is the predicted value of the dependent variable when the independent variable has value 90? y = Round to 1 decimal place.

The table below shows the average weekly wages​ (in dollars) for state government employees and federal government employees for 10 years. Construct and interpret a 98% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is​ $878.The equation of the regression line is y=1.342x+55.816. Wages [state]- 712, 746, 786, 803, 841, 879, 918, 926, 954, 979 Wages [federal]- 1,024, 1,048, 1,098, 1,135, 1,195, 1,240, 1,270, 1,299, 1,340, 1,376 Construct and interpret a 98​% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $878. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to the nearest cent as​ needed.)     PICK THE CORRECT ANSWER [A] We can be 98​% confident that when the average weekly wages of state government employees is $878​, the average weekly wages of…

Below is some of the regression output from a regression of the amount various customers paid for a new car (expressed in dollars) versus the age of the customer (expressed in years), the number of previous cars the customer had purchased from the dealership in the past, a dummy variable indicating the gender of the customer (=1 for a Man and = 0 for a woman), and an interactive term the multiplies the age of the customer with the gender dummy variable.  Regression Statistics           Multiple R 0.963           R Square             Adjusted R Square             Standard Error             Observations 20                         ANOVA               df SS MS F Significance F Regression   24686354.49 6171589 47.8 2.3289E-08   Residual     129243       Total   26625000…

Please answer parts d, e and f.

Increase in sales (percent) An advertising firm wishes to demonstrate to its clients the effectiveness of the advertising campaigns it has conducted. The following bivariate data on twelve recent campaigns, including the cost of each campaign (in millions of dollars) and the resulting percentage increase in sales following the campaign, were presented by the firm. Based on these data, we would compute the least-squares regression line to be y = 6.16+0.18x, with x representing campaign cost and y representing the resulting percentage increase in sales. (This line is shown below, along with a scatter plot of the data.) Increase in sales, y Campaign cost, x (in millions of dollars) (percent) 3.02 6.91 7.2+ 1.92 6.80 3.83 6.85 6.8- 1.40 6.37 6.6 - 3.12 6.42 3.56 6.82 6.4- 4.06 6.94 6.2 1.64 6.56 6- 2.06 6.50 1.62 6.18 1.5 2.5 3.5 6.66 Campaign cost (in millions of dollars) 2.87 2.25 6.61 Send data to calculator Based on the firm's data and the regression line, complete the following. (a)…

if the equation of the line of best fit is y=3.87x+15.52 for an increase of one hour in the time spent studying what is the predicted increase in the midterm score

This question has do with linear regression.If I consider attendance in a class versus final grade in the class can you explain where there is a positive and when there is a negative relationship between them.

The line of best fit through a set of data is y = 41.762 2.926x According to this equation, what is the predicted value of the dependent variable when the independent variable has value 50? y = Round to 1 decimal place.

The following regression equation is based on the analysis of four variables:  SM_DOLLARS is the dollar amount of a watershed conservation agency's weekly spending on social media ads.  RADIO_ADS is the number of radio advertisements aired weekly by the agency.  WS_DOLLARS is the dollar amount of the agency’s weekly spending on web search ads.  The variable WEB_VISITS is the number of weekly visitors to their educational website.  These data have been recorded every week for the past three years.   WEB_VISITS (expected) = 109 + 0.2*SM_DOLLARS + 1.5*RADIO_ADS + 1.1*WS_DOLLARS   The data meet the assumptions for regression analysis, and the regression results, including the coefficients, were found to be statistically significant. How many additional weekly web visits would you predict when the agency increases its weekly spending on social media ads by $150 without changing the amount spent on radio ads or web search ads? (Round your answer to the nearest whole number.)