The grades of a class of 9 students on a midterm report (x) and on the final examination (y) are shown below. Use the data to complete parts (a) and (b). x 77 50 71 72 83 94 96 99 67 y 81 67 79 36 48 84 99 99 68 (a) Estimate the linear regression line. ŷ=+x (Round the constant to one decimal place as needed. Round the coefficient to three decimal places as needed.)

A researcher is interested in seeing if there is a relationship the amount of time in minutes a person spends in their car during the day and the number of minutes that person spends listening to music.   Car Time 63 14 241 93 140 3 91 45 22 Music Time 73 16 260 142 206 31 78 47 29   a. Find the equation of the regression line and use it to make a prediction of the dollars purchased by someone who visits the website 4 times.b. Interpret the slope in the context of the problem.c. Interpret the y-intercept in the context of the problem or state why it is not applicable.d. State the null and alternative hypotheses for the hypothesis test of correlation e. Find the pvalue and state your conclusion in the context of the study.

The file Galton on D2L contains the 928 observations Francis Galton used in 1885 to estimate the relationship between the heights of parents and the heights of their children. The column Children refers to the height (in inches) of a child, and the column Mid-Parents refers to the average height (in inches) of the mother and father of that child. You can download this file into Excel and Minitab. a. Calculate the regression Height of Children = a +b (Height of Mid-Parents). b. Calculate the average for Height of Children, and calculate the average Height of Mid-Parents. c. Create a new variable in Minitab which is the Height of Children measured in terms of deviations from its mean. Call this new variable y. Also, create a new variable in Minitab with is the Height of Mid-Parents measured in terms of deviations from its mean. Call this new variable x. Calculate the regression y = a + bx. You can create the new y and x variables in Excel of Minitab, whichever you find more convenient.…

b. Find the equation of the regression line for the minutes the actor appeared shirtless in a film and the film's opening weekend gross. y = ___x + ____(Round to two decimal places as needed)

Find the slope (b1) for the regression equation for the following values. Round to 3 decimal places.    Define Variables xi yi 33 180 25 170 50 200 65 201 57 160 27 165

Use the data given below to answer a -c. Heigh (IN) 71 70.5 71 72 70 66.5 70 71 Weight (lb) 125 119 128 128 119 127 123 105 Find the regression equation letting the first variable (height) to be the independent variable (x). Find the best-predicted weight for a person whose height is 69in. What percentage of the variation in weight can be explained by the linear relationship between height and weight.

The datasetBody.xlsgives the percent of weight made up of body fat for 100 men as well as other variables such as Age, Weight (lb), Height (in), and circumference (cm) measurements for the Neck, Chest, Abdomen, Ankle, Biceps, and Wrist. We are interested in predicting body fat based on abdomen circumference. Find the equation of the regression line relating to body fat and abdomen circumference. Make a scatter-plot with a regression line. What body fat percent does the line predict for a person with an abdomen circumference of 110 cm? One of the men in the study had an abdomen circumference of 92.4 cm and a body fat of 22.5 percent. Find the residual that corresponds to this observation. Bodyfat Abdomen 32.3 115.6 22.5 92.4 22 86 12.3 85.2 20.5 95.6 22.6 100 28.7 103.1 21.3 89.6 29.9 110.3 21.3 100.5 29.9 100.5 20.4 98.9 16.9 90.3 14.7 83.3 10.8 73.7 26.7 94.9 11.3 86.7 18.1 87.5 8.8 82.8 11.8 83.3 11 83.6 14.9 87 31.9 108.5 17.3…

The following table shows the reported net sales by Nokia in 2008, 2009, and 2010.   Year    2008    2009    2010x    0    1    2Sales ($ millions)    20    50    60  Find the Equation of the Linear Regression Line. Rounds decimal values to the nearest tenths.

Show your work please.

Use the scatterplot of Vehicle Registrations below to answer the questions Vehicle Registrations in the United States, 1925- 2011 Vehicles millions 300 y = 3.0161x - 5819.5 R? = 0.9695 250 200 150 100 50 1920 -50 1940 1960 1980 2000 2020 Year Write a sentence explaining the value of the slope for this regression line. For every increase in year, the number of vehicle registrations in the US increases by 3.0161 million. For every increase in year, the number of vehicle registrations in the US increases by 5819.5. For every increase in vehicle registrations in the US, the number of years increases by 5819.5. For every increase in vehicle registrations in the US, the number of years increases by 3.0161 million. Registrations (in millions)