Given are five observations for two variables, and y.Excel File: data14-25.xlsxThe estimated regression equation is ŷ = 7.6 +0.9x.a. What is the value of the standard error of the estimate (to 4 decimals)?0.9726b. Test for a significant relationship by using the t test. Use a = 0.05.What is the value of the t test statistic (to 2 decimals)?1.90What is the p-value? Use Table 2 of Appendix B.between 0.10 and 0.20What is your conclusion (a = 0.05)?XjYiCannot conclude a significant relationship exists between x and yc. Use the F test to test for a significant relationship. Use a = 0.05.Compute the value of the F test statistic (to 2 decimals).3.63What is the p-value? Use Table 4 of Appendix B.greater than 0.10What is your conclusion?Cannot conclude a significant relationship exists between x and y276189 1392026 23

Answered: Given are five observations for two…

College Algebra

1st Edition

ISBN:9781938168383

Author:Jay Abramson

Publisher:Jay Abramson

Chapter4: Linear Functions

Section: Chapter Questions

Problem 30PT: For the following exercises, use Table 4 which shows the percent of unemployed persons 25 years or...

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Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4
Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?
For the following exercises, use Table 4 which shows the percent of unemployed persons 25 years or older who are college graduates in a particular city, by year. Based on the set of data given in Table 5, calculate the regression line using a calculator or other technology tool, and determine the correlation coefficient. Round to three decimal places of accuracy
The following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t= Years since 2006 0 1 2 3 4 5 6 7 8 9 10 K= Price 56 51 50 55 58 52 45 43 44 48 51 Make a quartic model of these data. Round the regression parameters to two decimal places.
Given are five observations for two variables, and . Excel File: data14-25.xlsx 2 6 9 13 20 x 7 18 9 26 23 y The estimated regression equation is . a. What is the value of the standard error of the estimate (to decimals)? b. Test for a significant relationship by using the t test. Use .What is the value of the t test statistic (to decimals)? What is the -value? Use Table 2 of Appendix B. - Select your answer -between 0.01 and 0.02between 0.02 and 0.05between 0.05 and 0.10between 0.10 and 0.20between 0.20 and 0.40greater than 0.40less than 0.01Item 3 . What is your conclusion ()? - Select your answer -Conclude a significant relationship exists between x and yCannot conclude a significant relationship exists between x and yItem 4 c. Use the test to test for a significant relationship. Use . Compute the value of the test statistic (to decimals). What is the -value? Use Table 4 of Appendix B. - Select your answer -between 0.01 and 0.025between 0.025 and 0.05between…
Consider the following data on x = weight (pounds) and y = price ($) for 10 road-racing bikes. These data provided the estimated regression equation ŷ = 28,240 − 1,419x. For these data, SSE = 7,209,342.96 and SST = 50,969,800. Use the F test to determine whether the weight for a bike and the price are related at the 0.05 level of significance. -Find the value of the test statistic. (Round your answer to two decimal places.)
The following estimated regression equation relating sales to inventory investment and advertising expenditures was given. ŷ = 21 + 13x1 + 9x2 The data used to develop the model came from a survey of 10 stores; for those data, SST = 19,000 and SSR = 14,630. (a)For the estimated regression equation given, compute R2. R2 = 0.77 (b)Compute Ra2. (Round your answer to two decimal places.) Ra2 = ?? (c) Does the model appear to explain a large amount of variability in the data? Explain. (For purposes of this exercise, consider an amount large if it is at least 55%. Round your answer to the nearest integer.) The adjusted coefficient of determination shows that ?? ( not 71)% of the variability has been explained by the two independent variables; thus, we conclude that the model does explain a large amount of variability.
Given below are results from the regression analysis where the dependent variable is the number of weeks a worker is unemployed due to a layoff (Unemploy) and the independent variables are the age of the worker (Age), the number of years of education received (Edu), the number of years at the previous job (Job Yr), a dummy variable for marital status (Married: 1=married, 0=otherwise), a dummy variable for head of household (Head: 1=yes, 0=no) and a dummy variable for management position (Manager: 1=yes, 0=no). We shall call this Model 1. The coefficient of partial determination (R2Yj.(All variables except j)) of each of the six predictors are, respectively, 0.2807, 0.0386, 0.0317, 0.0141, 0.0958, and 0.1201. Model 2 is the regression analysis where the dependent variable is Unemploy and the independent variables are Age and Manager. The results of the regression analysis are given. Refer to model 1. Which of the following is the correct null hypothesis to test…
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The data on y = annual sales ($1,000s) for new customer accounts and x = number of years of experience for a sample of 10 salespersons provided the estimated regression equation ŷ = 80 + 4x. For these data, x = 7, Σ(xi − x)2 = 142, and s = 4.6098. (a) Develop a 95% confidence interval for the mean annual sales (in thousands of dollars) for all salespersons with twelve years of experience. (Round your answers to two decimal places.) $ thousand to $ thousand (b) The company is considering hiring Tom Smart, a salesperson with twelve years of experience. Develop a 95% prediction interval of annual sales (in thousands of dollars) for Tom Smart. (Round your answers to two decimal places.) $ thousand to $ thousand

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Given are five observations for two variables, * and y. Excel File: data14-25.xlsx The estimated regression equation is û - 7 6+0.9r Xi Yi 2 6 9 13 7 18 9 20 26 23