Before buying a new car , a consumer wants to learn how the weight of a car affects highway gas mileage. Statistical software was used to conduct a simple linear regression about the relationship between the weight (in lbs) of a car and its highway mpg. The following equation for the regression line was given:  mpg=49.5-0.0081weight  If your car weighs 3200 lbs , what does the model predict in the highway mpg? Round to 1 decimal places.

Run a regression where you control for “Promotion,” and test the effect of “Wins” on “Attendance”. What percent of the change (variation) in “Attendance” is explained by “Wins”? How do you know? Wins Promotion Attendance 4 29500 36300 6 55700 40100 6 71300 41200 8 87000 53000 6 75000 44000 7 72000 45600 5 55300 39000 7 81600 47500

You are studying how a penguin's flipper length (in mm) explains its body mass (in grams) using linear regression. You choose a non-directional alternative to be safe. You calculate an R2=0.7621. What is the interpretation of this value? O76.21% of the variability in body mass is explained by the flipper length. O 76.21% of the variability in flipper length is explained by the body mass. 0 Flipper length and body mass have a positive relationship becase R² is positive O76.21% of the body mass values will be inside the confidence interval

Bill wants to explore factors affecting work stress. He would like to examine the relationship between age, number of years at the workplace, perceived social support, and work stress. He collects data on the variables from 100 employees (males and females) working in banks. Conduct a multiple regression analysis to answer the following questions: What is the relationship of age, number of years, and social support with work stress? Is the regression significant? If yes, what does it indicate? What is the regression equation for all the predictors? Write a results section based on your analysis that answers the research question. * last person got this wrong*

In a quantitative analysis where widowed people suffering with bereavement suffer with a poor quality of life.   Would Widowed Individuals be the Unit of Analysis? The quality of life be the dependent variable, therefore making bereavement the independent variable?

Because colas tend to replace healthier beverages and colas contain caffeine and phosphoric acid, researchers wanted to know whether cola consumption is associated with lower bone mineral density in women. The accompanying data lists the typical number of cans of cola consumed in a week and the femoral neck bone mineral density for a sample of 15 women. Complete parts (a) through (d) below. Click the icon to view the women's data. (a) Find the regression equation treating cola consumption per week as the x-variable. y=x+ (Round to three decimal places as needed.) (b) Interpret the slope. Select the correct choice below and, if necessary, fill in the answer box to complete your choice. OA. For 0 colas consumed in a week, the bone density is predicted to be (Round to three decimal places as needed.) g/cm³. OB. For every cola consumed per week, the bone density decreases by (Round to three decimal places as needed.) g/cm³, on average. OC. For a bone density of 0 g/cm³, the number of colas…

I need the right answer to this problem.

Use the time/tip data from the table below, which includes data from New York City taxi rides. (The distances are in miles, the times are in minutes, the fares are in dollars, and the tips are in dollars.) Find the regression equation, letting time be the predictor (x) variable. Find the best predicted tip for a ride that takes 30 minutes. How does the result compare to the actual tip amount of $4.70? Distance 1.80 1.40 12.71 1.32 8.51 0.49 2.47 Time 25.00 18.00 27.00 31.00 2.00 8.00 36.80 7.80 31.75 4.80 Fare 16.30 12.30 Tip 1.50 2.46 0.00 0.00 1.65 18.00 11.00 14.30 9.80 2.98 0.00 4.29 1.96 The regression equation is y = + X. (Round the y-intercept to two decimal places as needed. Round the slope to four decimal places as needed.)

Using the regression formula with a slope = .704 and an intercept = .719, what would the predicted college GPA be for a student whose current high school GPA = 3.2?

For the data below, what is the value of "b" for the regression equation? Family Father  Son   120 121   110 105   120 125   92 87   85 92   72 90   107 110   115 122   155 133   90 123