What two plots did we use in this chapter to decide whether we can reasonably presume that the assumptions for regression inferences are met by two variables of a population? What properties should those plots have?

Please show how to do this using PH STAT, not sure how to set up dummy variables. Thx

a) what is the regression equation? b) what is the predicted weight of the bear? c) is the result close to the actual weight of 528 pounds?

Please don't provide handwritten solution.....

An engineer wants to determine how the weight of a gas-powered car, x, affects gas mileage. v. The une ory tor ine most recent m odel year. Complete parts (a) through (d) accompanying data represent the weights of various domestic cars and their miles per gallon in BEE Click here to view the weight and gas mileage data (a) Find the least-squares regression line treating weight as the explanatory variable and miles per gallon as the response variable. y = 0.00702 * + (43.2) (Round the x coefficient to five decimal places as needed. Round the constant to one decimal place as needed.) (b) Interpret the slope and y-intercept, if appropriate. Choose the correct answer below and fill in any answer boxes in your choice.answer trom part a to find this answer O A. For every pound added to the weight of the car, gas mileage in the city will decrease by mile(s) per gallon, on average. A weightless car will get miles per gallon, on averag B. For every pound added to the weight of the car, gas…

If a regression line for two variables has a small positive slope, then the:  variables are positively associated? variables are negatively associated? association of the variables cannot be determined. variables have no association with each other.

An engineer wants to determine how the weight of a gas-powered car, x, affects gas mileage, y. The accompanying data represent the weights of various domestic cars and their miles per gallon in the city for the most recent model year. Complete parts (a) through (d) below. Click here to view the weight and gas mileage data. ..... (a) Find the least-squares regression line treating weight as the explanatory variable and miles per gallon as the response variable. x + (Round the x coefficient to five decimal places as needed. Round the constant to one decimal place as needed.) (b) Interpret the slope and y-intercept, if appropriate. Choose the correct answer below and fill in any answer boxes in your choice. (Use the answer from part a to find this answer.) A. For every pound added to the weight of the car, gas mileage in the city will decrease by mile(s) per gallon, on average. A weightless car will get miles per gallon, on average. O B. A weightless car will get miles per gallon, on…

This is only one question

(e) Find the line of best fit (or, the regression line) for the following data points: (3,13)(3,13), (4,18)(4,18), (5,23)(5,23), and (7,24)(7,24).

According to an article, one may be able to predict an individual's level of support for ecology based on demographic and ideological characteristics. The multiple regression model proposed by the authors was the following. y = 3.60-.01.x₁ +.01.x2-.07x3+.12x4+.02xs-.04x6-.01x7.04x8-.02xg+e The variables are defined as follows. y = ecology score (higher values indicate a greater concern for ecology) x₁ = age times 10 x₂ = income (in thousands of dollars) x3 = gender (1 = male, 0 = female) X4 = race (1 = white, 0 = nonwhite) X5 = education (in years) x6 = ideology (4 = conservative, 3 = right of center, 2 = middle of the road, 1 = left of center, and 0 = liberal) X7 = social class (4 = upper, 3 = upper middle, 2 = middle, 1 = lower middle, 0 = lower) x8 = postmaterialist (1 if postmaterialist, 0 otherwise) x9 = materialist (1 if materialist, O otherwise) (a) Suppose you knew a person with the following characteristics: a 30 year old, white female with a college degree (20 years of…