Prove that the logistic regression curve (5.1) has the steepest slope where 7 (x) = Generalize to model (5.8). }.
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- The large national bank charges local companies for using their services. A bank official reported the results of a regression analysi designed to predict the bank's charges (Y), measured in RM per month for services rendered to local companies. One independent variable used to predict service charge to a company is the the company's sales revenue (X), measured in millions of RM. Data for 21 companies who use the bank's services were used to fit the model. The results of the simple linear regression are provided below. Based on results below, a 95% confident interval for B is (15,30). Interpret the interval. * ŷ = -2,700 + 20X Sxy = 65, two – tailed p – value = 0.034 (for testing B We are 95% confident that the sales revenue (X) will increase between RM15 and RM30 million for every RM1 increase in service charge (Y). We are 95% confident that the mean service charge will fall between RM15 and RM30 per month. We are 95% confident that the average service charge (Y) will increase between…The maintenance manager at a trucking company wants to build a regression model to forecast the time (in years) until the first engine overhaul based on four predictor variables: (1) annual miles driven (in 1,000s of miles), (2) average load weight (in tons), (3) average driving speed (in mph), and (4) oil change interval (in 1,000s of miles). Based on driver logs and onboard computers, data have been obtained for a sample of 25 trucks. A portion of the data is shown in the accompanying table. Time Miles Load Speed Oil 7.7 42.9 22.0 44.0 16.0 0.8 98.3 20.0 47.0 34.0 6.3 61.1 22.0 62.0 15.0 E Click here for the Excel Data File b. Estimate the regression model. (Negative values should be indicated by a minus sign. Round your answers to 2 decimal places.) Time = Miles Load Speed oil + + d. What is the predicted time before the first engine overhaul for a particular truck driven 60,000 miles per year with an average load of 25 tons, an average driving speed of 53 mph, and 21,000 miles…no in Excel It is required to use the data given in the table to estimate the parameters of the simple linear regression equation by any of the estimation methods:
- Suppose we have a data set with five features, X1 = GPA, X2 = IQ, X3 = Level (1 for College and 0 for High School), X4 = product between GPA and IQ, and X5 = product between GPA and Level. We want to predict student's starting salary after graduation (in thousands of dollars). Suppose we use least squares to fit a linear regression model, and estimate the parameters of the model as follows: \beta 0 = 50; \beta 1 = b. Explain the effect of the low values of \ beta 2 and \beta 4 comparing to the high absolute values of \beta 1, \beta 3, and \beta 5. 20; \beta 2 = 0.07; 3 35; \beta 4 = 0.01; \beta Σ Q ...Given are five observations collected in a regression study on two variables. xi 2 6 9 13 20 yi 7 18 9 26 23 Compute b0 and b1 (to 1 decimal).b1 b0 Complete the estimated regression equation (to 1 decimal).^y = + x Use the estimated regression equation to predict the value of y when x = 6 (to 1 decimal).^y =In regards to "Go to Stat > Regression > Regression > Fit a regression model." where is stat?
- 8- According to the summary result of linear regression model between A and B obtained from R given below, we can fit a regression line. Assume that A has any value. If we decrease the value of A by 3, how would Y be affected? Call: Im (formula = B - A) Residuals: Min 10 Median 30 Маx -16.340 -10.793 -9.653 -8.502 58.325 Coefficients: Estimate Std. Error t value Pr (>[t]) (Intercept) 19.6315 20.6457 0.951 0.373 A 9.9609 0.3717 26.800 2.58e-08 *** --- Signif. codes: O *** 0.001 1** 0.01 1** 0.05 '.' 0.1 '' 1 Residual standard error: 26.46 on 7 degrees of freedom Multiple R-squared: 0.9903, Adjusted R-squared: 0.989 F-statistic: 718.2 on 1 and 7 DF, p-value: 2.58le-08 a) 49.5142 decrease b) 29.8827 increase c) 58.8945 decrease 29.8827 decrease 58.8945 increaseA researcher collects data between the age in years, (x), of a movie theater's popcorn popper and the cost of its monthly maintenance,(y).Find the regression equation. Round b to three decimal places.ˆyy^ = + CorrectxxFill in the table to find the residuals. Round table entries to three decimal places. xx yy ˆyy^ y−ˆyy-y^ 8 58 9 98 15 102 4 32 7 60 3 31 2 25 What is the correlation coefficient? Round to three decimal places. Graph the data and find the outlier. Give the ordered pair here:(, )If your ordered pair is actually the outlier, then the correlation coefficient would increase. Delete the ordered pair you chose and find the correlation coefficient again. Type the new correlation coefficient rounded to three decimal places here: Put the outlier back into your data and then find the test statistic, p-value, df, and critical value(s) for a test to find if there is a positive correlation with α=0.01α=0.01. Round to 3 decimal placestt…26) 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) *fill in the blank table* Suppose that the team owner is trying to decide whether to pay a particular free agent player. Based on the player's previous statistics, the owner thinks that the new player can help his team increase the number of wins but the new player is going to cost more than the player he will be replacing. The owner decides it is a good idea to sign the new player if he can be pretty sure that the coefficient is at least 0.20. When testing this hypothesis, what is the test statistic? (please express your answer using 2 decimal places)
- The regression line for a given dataset is found to be y^ =76−7.51xx. There is a pair of values x =7 and y =42 in this dataset taken from a specific individual. Compute the residual (error) of the predicted value y^ for this individual. Give your answer to two decimal placesSuppose you obtain the following regression model, E[y]=20+53*x +33*x^2. What is the impact of a 63 unit change of x on the expected value of y when x is at its mean of 54?Find the coefficients for the least-squares regression line y^=b0+b1x through the points (−2,0),(2,6),(4,14),(9,20),(9,25) b0 =. b1 =
