compute the correlation coefficientState the hypothesisDetermine the regression line equationPlot the regression line on the scatterplotSummarize the results SAT Scores Educational researchers desired to find out if a relationship exists between the average SAT verbal score and the average SAT mathematical score.Several states were randomly selected and their SAT average scores are recorded below.Verbal.x585 526 589 503 594606 517 530 589 588Math ySend data to Excel

Step 1: Scatterplot: Equation of regression line = Predicted y = 0.1507x + 481.67 Pearson's…

Answered: SAT Scores Educational researchers…

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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Predicting final exams How well do exams given duringthe semester predict performance on the final? One classhad three tests during the semester. Computer output ofthe regression givesDependent variable is Finals = 13.46 R-Sq = 77.7, R-Sq(adj) = 74.1,Predictor Coeff SE(Coeff) t-Ratio P-ValueIntercept -6.72 14.00 -0.48 0.636Test1 0.2560 0.2274 1.13 0.274Test2 0.3912 0.2198 1.78 0.091Test3 0.9015 0.2086 4.32 60.0001Analysis of VarianceSource DF SS MS F-Ratio P-ValueRegression 3 11961.8 3987.3 22.02 60.0001Error 19 3440.8 181.1Total 22 15402.6a) Write the equation of the regression model.b) How much of the variation in final exam scores isaccounted for by the regression model?c) Explain in context what the coefficient of Test3 scoresmeans.d) A student argues that clearly the first exam doesn’t helpto predict final performance. She suggests that this examnot be given at all. Does Test1 have no effect on the finalexam score? Can you tell from this model? (Hint: Doyou think test scores are…
What does the residual plot tell you about the linear regression model? * 20 10 -10 -20 20 30 40 50 60 70 Fitted Value The plot suggests that the residuals having a constant variance. The linear model could not be used for prediction. O we can conclude that there is significant relationship between the variables. O The linear model is appropriate to explain the relationship between the variables. Residual
Interperting Regression Results (Continuation of Exercise 8-39) The following table showsadditional regression results presented by the researchers in the study described in Exercise 8-39.There are two regressions. The right-hand column shows the results for all patients, including thosetreated with laparoscopic surgery. The left-hand column shows the results for the sample of patientswho were treated without the laparoscopic surgery.Nonlaparoscopic Patients Only All PatientsCoefficients for Independent VariablesRegression intercept $8,043 $3,719 Length of stay Coefficient* Not significant 861 Standard error for the coefficient Not applicable 80 Number of complications Coefficient 3,393 1,986 Standard error for the coefficient 1,239 406 Laparascopic Coefficient Not applicable 908 Standard error for the coefficient Not applicable 358 R-squared 0.11 0.53 *All independent variables are significant at the level of p = .05 (and t-value >2) except for the length of stay variable in the…
APPLIED GENERAL STATISTICS: THEORY AND METHODS The data is given below: Class 3 1. 8. 5 4 5 2 attendance Academic 51 28 49 60 32 47 40 39 35 42 performance C. Required: i. Identify the key variables in the study Ydt naviD S Classify the variables into dependent and independent State the nature of the variables iv. State the simple linear regression model that can capture the study ( prob abitistic prodel ) V. Use the method of the ordinary least squares to estimate the regression coefficients and interpret your ii. ii. sbbLobusr result vi. Coub Use the fitted equation to predict the value of the dependent variable when the independent is 30 vii. State three factors that can be captured by the error term * viii. Assess the adequacy of the fittèd regression model using the ANOVA method (Global F-test) assume ɑ = 5% ix. Estimate the standard error of the slope and the Shot on S11 lite intercent Gionee Dual Camera 6
Average Age and Length of Service The data show the average ages and lengths of service in months. Age 24.6 25.5 26.1 27.3 27.2 Time 66.6 71 74.9 88.9 80.6 The correlation coefficient for the data is r=0.944 and α=0.05 Should regression analysis be done? The regression analysis should not be done. The regression analysis should be done. Find the equation of the regression line. Round the coefficients to at least three decimal places. y'=a+bx a= b= If a service person is 26.6 years old, predict the time that the person will serve. Round the answer to at least one decimal place. The service person will serve months.
SAT GPA 1070 3.50 1040 2.66 1120 3.54 1260 3.83 1100 2.60 1020 2.70 960 2.00 The least-squares regression line equation of GPA on SAT score is:
Pls if anyone can answer this I need help
Best picture that can be taken please answer with caution and as soon as possible.
Which of these is not true about dummy variable regression? Variable with k categories require (k-1) dummy variables When quantitative variable is put into categories, there is loss of information None of the above
Please do not give solution in image format thanku
using Excel
Average Age and Length of Service The data show the average ages and lengths of service in months. Age 25 25.5 26.5 26.6 26.9 Time 66.2 71.2 72.6 88.1 82.7 The correlation coefficient for the data is =r0.817 and =α0.05 . Should regression analysis be done? The regression analysis should not be done. The regression analysis should be done. Find the equation of the regression line. Round the coefficients to at least three decimal places. =y′+abx =a =b If a service person is 26.0 years old, predict the time that the person will serve. Round the answer to at least one decimal place. Theservicepersonwillservemonths.

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