In simple linear regression and multiple regression, R2...     compares the regression SS to the total SS     accounts for the number of parameters in the model     always varies between -1 and 1     the ratio of the error SS versus the regression SS

The table shows the average weekly wages (in dollars) for state government employees and federal government employees for 8 years. The equation of the regression line is y = 1.405x – 12.307. Complete parts (a) and (b) below. Average Weekly Wages (state), x Average Weekly Wages (federal), y 751 760 791 817 835 881 924 951 1002 1047 1115 1149 1195 1250 1269 1300 (a) Find the coefficient of determination and interpret the result. 12 =O

What is the null hypothesis to test the significance of the slope in a regression equation? Multiple Choice Ho:B 20 Ho: Bs0 O Ho: B = 0 Ho: B 0

Two variables are defined, a regression equation is given, and one data point is given. Weight Training = = Weight 92 +11.9(Training) = maximum weight capable of bench pressing (pounds) number of hours spent lifting weights a week The data point is an individual who trains 5 hours a week and can bench 150 pounds. Residual (a) Find the predicted value for the data point and compute the residual. Enter the exact answers. Predicted value = M. lbs lbs

Two variables have a positive linear correlation.  Is the slope of the regression line for the variables positive or negative?

Two variables are defined, a regression equation is given, and one data point is given. Hgt = height in inches Age = age in years of a child Hgt = 24.5+2.78(Age) The data point is a child 12 years old who is 60 inches tall. X Your answer is incorrect. (a) Find the predicted value for the data point and compute the residual. Enter the exact answers. Predicted value = i Residual = inches inches

The data from a study of orange juice produced at a juice manufacturing plant are in the table. The simple linear regression was used to predict the sweetness index​ (y) from the amount of pectin​ (x) in the orange juice. Complete parts a through c.   view the table.   xi    yi8    23    37    22    61    71    63    5   Find the values of​ SSE, s2​, and s for this regression.   SSE=enter your response here ​(Round to four decimal places as​ needed.)

A high R2 is all that is needed to determine if a regression is a good model of a causal process. A. True B. False

A researcher is investigating possible explanations for deaths in traffic accidents. He examined data from 2000 for each of the 52 cities randomly selected in the US. The variables were death and income. Deaths: The number of deaths in traffic accidents per cityIncome: The median income per city  The researcher ran a simple linear regression model: Deaths = Bo+B1(Income). Results shown in photo below.  Question: Please help me better understand how to use results from photo to find value of R-squared of this simple linear regression model.

Find the regression​ equation, letting the first variable be the predictor​ (x) variable. Using the listed​ lemon/crash data, where lemon imports are in metric tons and the fatality rates are per​ 100,000 people, find the best predicted crash fatality rate for a year in which there are 500 metric tons of lemon imports. Is the prediction​ worthwhile? Find the equation of the regression line. ​(Round the constant three decimal places as needed. Round the coefficient to six decimal places as​ needed.) The best predicted crash fatality rate for a year in which there are 500 metric tons of lemon imports is _______ fatalities per​ 100,000 population. ​(Round to one decimal place as​ needed.) Is the prediction​ worthwhile? A. Since the sample size is​ small, the prediction is not appropriate.   B. Since common sense suggests there should not be much of a relationship between the two​ variables, the prediction does not make much sense.   C. Since all of the requirements…