Regression. A coach wants to see the relationship between the statistics of practice games and official games of a local soccer team. A sample of 14 players was used and the resulting (partial) Excel output is shown below. Assume both x and y form normal distributions.RegressionMultiple RR SquareAdjusted R SquareStandard ErrorObservationsStatistics0.705240.6683958.70363314(a) The slope of the regression line istCoefficients StandardErrorO A. 0.757OB. 4.373OC. 0.177O D. 40.541(b) The correlation coefficient isOB. H₁: p = 0OA. -0.8398OB. 0.8398OC. None of the other answersO D. 0.705OC. H₁ :p #0OD. H₁:μ = 0t StatP-valueLower95%A hypothesis test is done to determine whether the correlation coefficient is significantly different from zero.(c) The alternate hypothesis isOA. H₁ : ³ 0Upper95%C

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Answered: Regression. A coach wants to see the…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Assuming a linear relationship between X and Y, if the coefficient of correlation (r) equal -0.30, there is no correlation. the slope is negative. variable X is larger than variable Y. O the variance of X is negative.
. A professor at the University of Alabama was interested in evaluating the relationship between family support and delinquency. Using data collected on 4545 families, the researcher used regression to analyze the relationship. The results are presented below. Variables Entered/Removeda Model Variables Entered Variables Removed Method 1 Family supportb . Enter a. Dependent Variable: Delinquency b. All requested variables entered. Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .249a .062 .062 1.59168 a. Predictors: (Constant), Family support ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 759.204 1 759.204 299.671 <.001b Residual 11479.107 4531 2.533 Total 12238.311 4532 a. Dependent Variable: Delinquency b. Predictors: (Constant), Family support…
What is the difference between a Multiple Regression model and a Multivariate Regression model? Suppose a researcher wants to predict the probability of a patient being diagnosed with breast cancer given their be used? age, family history, and smoking status. What type of regression model should alsboin sisiurviluM bae alqiluM alm?
u = (-4.6)
I need help finding the answers for A,B,and C
Use the value of the linear correlation coefficient to calculate the coefficient of determination. What does this tell you about the explained variation of the data about the regression line? About the unexplained variation? r=0.926
Using a sample of 46 college students, we want to determine if there is a significant correlation between weight (in lbs.) and weekly exercise (in minutes). The results of a correlation and regression analysis are indicated in the Excel output below. The mean weight (the independent variable) was 166.80 lbs., and the mean weekly exercise time (the dependent variable) was 158.83 minutes. SUMMARY OUTPUT Regression Statistics Multiple R 0.027082077 R Square 0.000733439 Adjusted R Square -0.021977165 Standard Error 79.41761298 Observations 46 ANOVA df SS MS F Significance F Regression 1 203.6896 203.6896 0.032295 0.858207 Residual 44 277514.9 6307.157 Total 45 277718.6 Coefficients Standard Error t Stat P-value Lower 95%…
State the regression equation and use it to predict taxes for a house with lot size 10K.
Dex Research Limited conducted a research to investigate consumer characteristics that can be used to predict the amount charged by credit card users. The following multiple regression output is based on a data collected by this research company on annual income, household size and annual credit card charges for a sample if 50 consumers. Regression Statistics Multiple R 0.9086 R Square A Adjusted R Square 0.8181 Standard Error 398.091 Observations B ANOVA df SS MS F Significance F Regression 2 C E G 1.50876E-18 Residual D 7448393 F Total 49 42699149 Coefficients Standard Error t Stat P-Value Intercept 1304.9048 197.6548 6.6019 3.28664E-08 Income ($1000s) 33.1330 3.9679 H 7.68206E-11 Household size 356.2959 33.2009 10.7315 3.12342E-14 a. Complete the missing entries from A to H in this outputb. Estimate the annual credit card charges…
Use the value of the linear correlation coefficient to calculate the coefficient of determination. What does this tell you about the explained variation of the data about the regression line? About the unexplained variation? r = -0.338 Calculate the coefficient of determination. (Round to three decimal places as needed.) % of the variation can be explained by the regression line (Round to one decimal place as needed.) % of the variation is unexplained and is due to other factors or to sampling error. (Round to one decimal place as needed.)
You may need to use the appropriate technology to answer this question. Following is a portion of the computer output for a regression analysis relating y = maintenance expense (dollars per month) to x = usage (hours per week) of a particular brand of computer terminal. Analysis of Variance SOURCE DF Adj SS Adj MS Regression 1 1575.76 1575.76 Error 8 349.14 43.64 Total 9 1924.90 Predictor Coef SE Coef Constant 6.1092 0.9361 X 0.8951 0.1490 Regression Equation Y = 6.1092 + 0.8951 X #1) Write the estimated regression equation. ŷ = #2) Find the value of the test statistic. (Round your answer to two decimal places.)Find the p-value. (Round your answer to three decimal places.) #3)Use the estimated regression equation to predict monthly maintenance expense (in dollars per month) for any terminal that is used 15 hoursper week. (Round your answer to the nearest cent.) $ _____per month
Find the regression equation, letting overhead width be the predictor (x) variable. Find the best predicted weight of a seal if the overhead width measured from a photograph is 2.3 cm. Can the prediction be correct? What is wrong with predicting the weight in this case? Use a significance level of 0.05. Overhead Width (cm) Weight (kg) 7.8 175 7.3 9.5 274 7.4 156 9.9 294 9.2 183 256 Click the icon to view the critical values of the Pearson correlation coefficient r. ..... The regression equation is y =+x. (Round to one decimal place as needed.)

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