An article on estimating 28-day strength of concrete considered regressing y = 28-day standard-cured strength (psi) against x = accelerated strength (psi). Suppose the equation of the true regression line is y = 1,830 + 1.5x. (a) What is the expected value (in pounds per square inch) of 28-day strength when accelerated strength = 2,410 psi? psi (b) By how much can we expect 28-day strength (in pounds per square inch) to change when accelerated strength increases by 1 psi? psi (c) By how much can we expect 28-day strength (in pounds per square inch) to change when accelerated strength increases by 130 psi? psi (d) By how much can we expect 28-day strength (in pounds per square inch) to change when accelerated strength decreases by 130 psi? psi

In regards to "Go to Stat > Regression > Regression > Fit a regression model." where is stat?

The linear regression equation for predicting systolic blood pressure from age is: ˆyy^  = 47 + 2.2*x Find the residual for a person who is 36 years of age with a systolic blood pressure of 128.3 (round your answer to one decimal place)

Find the slope of regression line, y-intercept of regression line, coefficient of determination (r^2), and the linear correlation coefficient (r)

Data showing the values of several pitching statistics for a random sample of 20 pitchers from the American League of Major League Baseball is provided. w L Player Тeam W ERA So/IP HR/IP R/IP Verlander, J DET 24 2.40 1.00 0.10 0.29 Вeckett, J BOS 13 7 2.89 0.91 0.11 0.34 Wilson, C TEX 16 7 2.94 0.92 0.07 0.40 Sabathia, C NYY 19 8 3.00 0.97 0.07 0.37 Haren, D LAA 16 10 3.17 0.81 0.08 0.38 McCarthy, B OAK 3.32 0.72 0.06 0.43 Santana, E LAA 11 12 3.38 0.78 0.11 0.42 Lester, J BOS 15 9. 3.47 0.95 0.10 0.40 Hernandez, F SEA 14 14 3.47 0.95 0.08 0.42 13 9 Buehrle, M CWS 3.59 0.53 0.10 0.45 Pineda, M SEA 9. 10 3.74 1.01 0.11 0.44 Colon, B NYY 8 10 4.00 0.82 0.13 0.52 Tomlin, J CLE 12 7 4.25 0.54 0.15 0.48 Pavano, C MIN 9. 13 4.30 0.46 0.10 0.55 Danks, J CWS 8. 12 4.33 0.79 0.11 0.52 Guthrie, J BAL 9 17 4.33 0.63 0.13 0.54 Lewis, C TEX 14 10 4.40 0.84 0.17 0.51 Scherzer, M DET 9. 4.43 0.89 0.15 0.52 Davis, W ТВ 11 10 4.45 0.57 0.13 0.52 Porcello, R DET 14 9. 4.75 0.57 0.10 0.57 An estimated…

how to Compute the slope of the OLS regression equation.  n=19 x=725 y=800  xy=33,30 x^2=31725 y^2= 35800

I need final answers for R^2 and press residuals. Round to three decimals in R^2

21) Below is some of the regression output from a simple regression of the number of wins for a major league baseball team and the size amount of money the team is paying its players (expressed in millions of $'s) *Please fill in the table and show scratchwork*

I need to compute R^2 for each model and compute the press for each model too in part c please

Use the least squares regression line of this data set to predict a value. Meteorologists in a seaside town wanted to understand how their annual rainfall is affected by the temperature of coastal waters. For the past few years, they monitored the average temperature of coastal waters (in Celsius), x, as well as the annual rainfall (in millimetres), y. Rainfall statistics • The mean of the x-values is 11.503. • The mean of the y-values is 366.637. • The sample standard deviation of the x-values is 4.900. • The sample standard deviation of the y-values is 44.387. • The correlation coefficient of the data set is 0.896. The least squares regression line of this data set is: y = 8.116x + 273.273 How much rainfall does this line predict in a year if the average temperature of coastal waters is 15 degrees Celsius? Round your answer to the nearest integer. millimetres