40 Regressionn output for predicting the time (in minutes) for baseball games on the number of hits is givenbelow. Interpret the value of R2.The regression equation is Time = 156 + 1.36 HitsPredictorCoefSE CoefTConstant155.6812.78 12.18 0.000Hits1.36480.69321.970.059s = 19.5861R-sq = 12.2%%3DO 12.2% of the variability in hits is explained by by game times.O 12.2% is greater than 0, so the correlation is positive.O 12.2% of game times are accurately predicted by hits.O 12.2% is the correlation between game times and hits.12.2% of the variability in game times is explained by hits.

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Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter4: Equations Of Linear Functions

Section: Chapter Questions

Problem 4SGR

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Last tank! For Exercise 2’s regression model predicting fuel economy (in mpg) from the car’s horsepower, se = 3.287. Explain in this context what that means
A college faculty collected data on his studens' score in the first exam and their first quiz.Look for the image for table. Supposed that the value of regression constant is 9.1410114235and regression Coefficient is 0.90613879, try to interpret this or describe this data in an in-depth manner.Note: no calculation anymore, just interpretation of the data.Example of expected answer: The coefficient of determination gives the amount of variation in the model explained by the factor considered in the model. Here only 1.74% of the variation is explained by the independent variable. Therefore, we can conclude that the high school grade is not much associated with the general weighted average.
3- Fit full appropriate regression models to study the relationship between the variables. Test the significance of the model and the significance of the regression coefficients at 5% level. Answer it by excel
Let the X-values represent the times, in minutes, of preparation for a Statistics test; let the Y-values represent the points earned on the test. Assume that the sample of paired (X, Y) data is a simple random sample of quantitative data and the data have a bivariate normal distribution. Also, the scatterplot shows that the points approximate a straight-line pattern. Assume that the regression equation is y = 0.23x + 17. If a student spent 345 minutes preparing for the test, how many points should the student expect to earn?
Multiple regression analysis was used to study how an individual's income (Y in thousands of dollars) is influenced by age (X1 in years), level of education (X2 ranging from 1 to 5), and the person's gender (X3 where 0 =female and 1=male). The following is a partial result of computer output that was used on a sample of 20 individuals. Present the estimated regression equation and compute the coefficient of determination. Explain it. Use the t test to determine the significance of each independent variable. Let α = 0.05. (For each test, give the null and alternative hypotheses, test statistic, and conclusion.) Use the F test to determine whether or not the regression model is significant. Let α = 0.05. (For the test, give the null and alternative hypotheses, test statistic, and conclusion.) Does the estimated regression equation provide a good fit for the observed data? Explain it. Suppose a new person with X1=40, X2=4, X3=0. Use the estimated regression equation in part (a)…
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
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Find correlation coefficient between the exchange and expenditure from the datagiven below: Obtain the regression equation of exchange on expenditure expenses and find out theexpected exchange of a firm when expenditure is Rs. 25 lakhs. Also find coefficientof determination and interpret your result.
Use the regression identity for multiple linear regression to show that R2 =1- SSE/SST. a. Explain why this formula shows that the coefficient of multiple determination can also be interpreted as the percentage reduction in the total squared error obtained by using the regression equation instead of the mean,y~, to predict the observed values of the response variable. b. Referring to , what percentage reduction in the total squared error is obtained by using the regression equation instead of the mean of the observed prices to predict the observed prices? c. Referring to , what percentage reduction in the total squared error is obtained by using the regression equation instead of the mean of the observed graduation rates to predict the observed graduation rates?
A researcher investigated the relationship between family income and savings. Using data from 15 families, the computed r between income and savings was found to be 0.76. The researcher wants to test if there is a significant relationship between the two variables at 5% level of significance and create a regression equation to predict the possible savings given the income of the family. Interpret the computed r value. (Write your interpretation in statement form) Test if there is a significant relationship between the two variables at 5% level of significance (Show complete proof/steps with conclusion in statement form)

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Regressionn output for predicting the time (in minutes) for baseball games on the number of hits is given below. Interpret the value of R2.