How should interpret assumptions of the technique used?Based on the tables and charts presented below, interpret the results and report your answer with an academic style. You should interpret assumptions of the technique used. ModelNormal P-P Plot of Regression Standardized ResidualDependent Variable CallonsPer100MesRegressionResidualObserved Cum ProbSum ofSquaresANOVAdf848.3632240.3253891088.688 391F424.182 686.598.618Mean SquareTotalDependent Variable, GallonsPer100Milesh. Predictors (Constant), Hores Power of the Engine, Number of cylindersSig..000Dependent Variable CallionsPer100MilesRegression Standardized Predicted Vale PearsonCorrelationModel SummaryRR Square.883 .779Model1.778a. Predictors: (Constant), Hores Power of the Engine,Number of cylindersb. Dependent Variable: GallonsPer100MilesModel Dimension Eigenvalue1 12.917Sig (1-tailed)Model23a. Dependent Variable: GallonsPer 100MiesCollinearity. Diagnostics067016ContarNumber of cindersHores Power of theEnginea Dependent variable CalenAdjusted RSquareConditionNumber of Hores PowerIndex (Constant) cylinders of the Engine1.000 01001485GallonaPer100MenNumber of cylindersHores Power of theEngine6.596 8513.68014CorrelationsGallonsPer100MilesNumber of cylindersHors Power of theEngineGallonsPer100MilesNumber of cylindersHores Power of theEngine2804062.185GalonsPer100MUnstandardand Coefficients1 Std. Ervar134141921.000840854*** 88.000392392Std. Error ofthe Estimate78600Variance Proportions392Number ofcylindersStandardedCafficerska0003971401.00034300000039239239212.094415 9.374504 11.343HoresPower ofthe EngineCoefficients8548431.00000000030239230295.5 Confidence aloSlow Round pe lund -ade370000003173211808542491 140 4292.563814500Pot T221271219 14582014

From the above graph we see that, the data fits well in the regression model. There are 3 variables.…

del Normal P-P Plot of Regression Standardized Residual Dependent Variable CallensPer100Mes Expected Cam Prob La Regression Residual Observed Cum Prob Sum of Squares A ANOVA df 848.363 2 240.325 389 1088.688 391 Regression Standardized Residual F 424.182 686.598 .618 Mean Square Total a. Dependent Variable: GallonsPer100Miles h. Predictors (Constant), Hores Power of the Engine, Number of cylinders Sig. .000 Dependent **** *** Regression Standardized Predicted Value

del Normal P-P Plot of Regression Standardized Residual Dependent Variable CallensPer100Mes Expected Cam Prob La Regression Residual Observed Cum Prob Sum of Squares A ANOVA df 848.363 2 240.325 389 1088.688 391 Regression Standardized Residual F 424.182 686.598 .618 Mean Square Total a. Dependent Variable: GallonsPer100Miles h. Predictors (Constant), Hores Power of the Engine, Number of cylinders Sig. .000 Dependent ** * Regression Standardized Predicted Value

Functions and Change: A Modeling Approach to College Algebra (MindTap Course List)

6th Edition

ISBN:9781337111348

Author:Bruce Crauder, Benny Evans, Alan Noell

Publisher:Bruce Crauder, Benny Evans, Alan Noell

Chapter3: Straight Lines And Linear Functions

Section3.CR: Chapter Review Exercises

Problem 16CR: XYZ Corporation Stock Prices The following table shows the average stock price, in dollars, of XYZ...

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XYZ Corporation Stock Prices The following table shows the average stock price, in dollars, of XYZ Corporation in the given month. Month Stock price January 2011 43.71 February 2011 44.22 March 2011 44.44 April 2011 45.17 May 2011 45.97 a. Find the equation of the regression line. Round the regression coefficients to three decimal places. b. Plot the data points and the regression line. c. Explain in practical terms the meaning of the slope of the regression line. d. Based on the trend of the regression line, what do you predict the stock price to be in January 2012? January 2013?
Noise and Intelligibility Audiologists study the intelligibility of spoken sentences under different noise levels. Intelligibility, the MRT score, is measured as the percent of a spoken sentence that the listener can decipher at a cesl4ain noise level in decibels (dB). The table shows the results of one such test. (a) Make a scatter plot of the data. (b) Find and graph the regression line. (c) Find the correlation coefficient. Is a linear model appropriate? (d) Use the linear model in put (b) to estimate the intelligibility of a sentence at a 94-dB noise level.
Using the regression line attached. The plot: a) reveals sure evidence that the population slope is unequal to 0 b) reveals sure evidence that the sample slope is unequal to 0 c) can be used alone to reject the null hypothesis that the population slope is unequal to 0 d) can be used alone to reject the null hypothesis that the population slope is equal to 0 e) a and c f) a and d
COmpare and constrast the use of prediction intervals for a Single Linear Regression model having one X and Multiple Linear Regression Model having two predictors X1 and X2. WHat are the similarities/differences in process and interpretation?
The production of wine is a multi-billion-dollar worldwide industry. In an attempt to develop a model of wine quality as judged by wine experts, data was collected from red wine variants from a particular type of foreign wine. A multiple linear regression model was developed from a sample of 55 wines. The model was used to predict wine quality, measured on a scale from 0 (very bad) to 10 (excellent) based on the alcohol content (%) and the amount of chlorides. a. Construct a 95% confidence interval estimate of the population slope between wine quality and the percentage of alcohol. (Round to four decimal places as needed.)
The “least squares” method of fitting the best straight line in simple linear regression does which of the following: a. Minimizes the standard deviation of the independent variable b. Minimizes the sum of squared deviations between the fitted line and the dependent variable c. Maximizes the sum of the absolute deviations between the fitted line and the dependent variable d. Minimizes the standard deviation of the dependent variable
Training Dept. of Nimrod Inc wants to develop a regression-based compensation model (compensation in $ per year, Comp) for its mid-level managers to encourage performance, loyalty, and continuing education based on three variables. ▪ Business unit-profitability (Profit per year in $). ▪ Working experiences in Nimrod Inc (Years). ▪ Whether or not a manager has a graduate degree (Grads). If a manager has a graduate degree equals 1, 0 otherwise. Table Attached Question: At the 5% significance level, is the overall regression model significant
TRUE or FALSE, if false explain why? 1. Simple linear regression is robust to situations where the variability in Y depends greatly on the value of X. 2. The Shapiro-Wilk test is the best way to identify non-normality of residuals that bad enough to invalidate a regression analysis. 3. The Working-Hoteling adjustment is made to ensure the false positive rates are not artificially increased when using prediciton bands.
The accompanying scatterplot shows the relationship between the age of an internet user and the amount of time spent browsing the internet per week (in minutes). The accompanying residual plot is also shown along with the QQ plot of the residuals. Choose the statement that best describes whether the condition for Normality of errors does or does not hold for the linear regression model. Choose the statement that best describes whether the condition for Normality of errors does or does not hold for the linear regression model. A.The residual plot displays a fan shape; therefore the Normality condition is not satisfied.B.The QQ plot mostly follows a straight line; therefore the Normality condition is satisfied.C.The scatterplot shows a negative trend; therefore the Normality condition is satisfied.D.The residual plot shows no trend; therefore the Normality condition is not satisfied.
The weight and systolic blood pressure of 30 randomly selected males in the age group 25-30 areshown below. Assuming that weight and blood pressure (BP) are normally distributed.a) Find a regression line relating systolic blood pressure wo weightb) Estimate the coefficient of determination and interpret your findingsc) Test the hypothesis that p=0d) Test the hypothesis that p=0.6.e) Find the 95% CI for pf) Consider the weight and blood pressure and fit a non-intercept model to the data andcompare it to the model obtain in part (a). which model would you consider superior?Subject Weight Systolic BP Subject Weight Systolic BP1 165 130 16 172 1532 167 133 17 159 1283 180 150 18 168 1324 155 128 19 174 1495 212 151 20 183 1586 175 146 21 215 1507 190 150 22 195 1638 210 140 23 180 1569 200 148 24 143 12410 149 125 25 240 17011 158 133 26 235 16512 169 135 27 192 16013 170 150 28 187 15914 156 131 29 200 13715 185 127 30 220 140
A researcher in a scientific foundation wished to evaluate the relation between intermediate and senior level annual salaries of research mathematician (Y, in thousand dollars) and an index of publication quality (X1), the number of years experience (X2), and an index of success in obtaining grant support (X3). A. Determine the R2 and adjusted R2. B. Determine the significant factors. C. Determine if the residual follows a normal distribution . Determine if the variance is constant over time. Find the leasts-squares regression equation. The data for a sample of 24 intermediate and senior level research mathematicians follow.
True or False and explain if false: 1. The slope estimate from a regression model is an example of descriptive statistic. 2. if a p-value is 0.9, then we may appropriately conclude that no relationship between X and Y exists 3. Assuming that X variable is controlled, one way to decrease standard errors in a sample linear regression analysis is to assign value of X variable that are further apart.