You make the bold assumption that there is a linear relationship between number of ads and sales revenues. Find the intercept, b0, and the slope, b1, of the estimated regression equation that will minimize the sum of square residuals.

An opinion poll asks an SRS of 501 teenagers, "Generally speaking, do you approve or disapprove of legal gambling or 6000*6 betting?" Suppose that, in fact, exactly 50% of all teenagers would say Approve if asked. (This is close to what polls show to be true.) The poll's statisticians tell us that the sample proportion who say Approve will vary in repeated Normal distribution with mean 0.5 and standard deviation about 0.022. keerples according to a Using the 68-95-99.7 rule, what is the probability that fewer than 54.4% say Yes? (Use decimal notation. Give your answer as an exact proportion.) probability: O hp 43°F Clear (1) 6:30 PM 11/26/2022 見

A real estate company wants to study the relationship between house sales prices and some important predictors of sales prices. Based on data from recently sold homes in the space, the following variables are used in a multiple regression model. y = sales price (in thousands of dollars) x₁ = total floor area (in square feet) x₂ = number of bedrooms x3 distance to nearest high school (in miles) = The estimated model is as follows. =76+0.098x₁ +16x₂ - 8x3 Answer the questions below for the interpretation of the coefficient of X₂ in this model. (a) Holding the other variables fixed, what is the average change in sales price for each additional bedroom in a house? dollars (b) Is this change an increase or a decrease? O increase O decrease X

The table below shows the amounts of crude oil (in thousands of barrels per day) produced by a country and the amounts of crude oil (in thousands of barrels per day) mported by a country, for the last seven years. Construct and interpret a 95% prediction interval for the amount of crude oil imported by the this country when the amount of crude oil produced by the country is 5,508 thousand barrels per day. The equation of the regression line is y = - 1.120x + 15,839.271. Oil produced, x 5,684 5,654 5,452 5,157 5,061 5,030 5,826 9,680 10,041 10,154 10,121 10,060 Oil imported, y 9,304 9,105 Construct and interpret a 95% prediction interval for the amount of crude oil imported when the amount of crude oil produced by the country is 5,508 thousand barrels per day. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to the nearest cent as needed.) and O A. We can be 95% confident that when the amount of oil produced is 5,508 thousand barrels, the…

For a linear regression b1 is the estimated y-intercept, and b0is the estimated slope of the regression line.   True or False

The table below shows the amounts of crude oil (in thousands of barrels per day) produced by a country and the amounts of crude oil (in thousands of barrels per day) imported by a country, for the last 7 years. Construct and interpret a 98% prediction interval for the amount of oil imported by the country and the amount of oil produced by the country is 5,483 thousand barrels per day. The equation of the regression line is y = -1.194x + 16,234.906

1. Develop a simple linear regression equation for starting salaries using an independent variable that has the closest relationship with the salaries. Explain how you chose this variable.

You run a linear regression to predict BMI (body mass index) from average minutes of physical activity per day. You calculate the slope of the regression to be -.054. Interpret the slope in terms of the independent and dependent variables.

write the regression equation that will predict the number of manatees killed given thenumber of powerboat registrations (in 1000's). Show all work usingformulas for slope, b1, and y-intercept, b0, calculations roundingto 4-decimal places, if necessary. Show all the calculations and math of slope, b1, and y-intercept, b0, calculations roundingto 4-decimal places, if necessary. SHOW ALL WORK! DO NOT USE EXCEL! I need to be able to see every single part and how you got it. attached is the question

What needs to change in an overall problem if one wants to use linear regression?