A regression model relating z, number of salespersons at a branch office, to y, annual sales at the office (in thousands of dollars) provided the following regression output. Where Total = 40. ANOVA Regression Residual Total Intercept Number of Salespersons a. Write the estimated regression equation (to whole number). df Coefficients 88.0 58.0 SS 6,761.8 8,905.8 MS F t Stat p-value is -Select your answer- we-Select your answer-Ho: B₁- d. Predict the annual sales at the Memphis branch office. This branch employs 14 salespersons. $ thousand (to whole number) Standard Error 11.338 5.589 Significance F b. Compute the F statistic and test the significance of the relationship at a 0.05 level of significance. (to 2 decimals) F-value p-value is -Select your answer- we-Select your answer- He c. Compute the t statistic and test the significance of the relationship at a 0.05 level of significance. (to 2 decimals) t Stat P-value

A regression model relating z, number of salespersons at a branch office, to y, annual sales at the office (in thousands of dollars) provided the following regression output. Where Total = 40. ANOVA Regression Residual Total Intercept Number of Salespersons a. Write the estimated regression equation (to whole number). df Coefficients 88.0 58.0 SS 6,761.8 8,905.8 MS F t Stat p-value is -Select your answer- we-Select your answer-Ho: B₁- d. Predict the annual sales at the Memphis branch office. This branch employs 14 salespersons. $ thousand (to whole number) Standard Error 11.338 5.589 Significance F b. Compute the F statistic and test the significance of the relationship at a 0.05 level of significance. (to 2 decimals) F-value p-value is -Select your answer- we-Select your answer- He c. Compute the t statistic and test the significance of the relationship at a 0.05 level of significance. (to 2 decimals) t Stat P-value

College Algebra

7th Edition

ISBN:9781305115545

Author:James Stewart, Lothar Redlin, Saleem Watson

Publisher:James Stewart, Lothar Redlin, Saleem Watson

Chapter1: Equations And Graphs

Section: Chapter Questions

Problem 10T: Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s...

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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
For the following exercises, consider the data in Table 5, which shows the percent of unemployed in a city ofpeople25 years or older who are college graduates is given below, by year. 41. Based on the set of data given in Table 7, calculatethe regression line using a calculator or othertechnology tool, and determine the correlationcoefficient to three decimal places.
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?
A researcher examined the relationship between the annual tax amount paid by the construction company owners and the total expense items spent for the construction with regression analysis and calculated the regression line estimation as Y=6+2X. According to this; Write the interpretations of the cutoff and regression parameters, respectively, in your OWN SENTENCES in a statistically appropriate way over the tax amount and expenses.
A researcher was interested in investigating whether the parent-child interaction time (in hours) is a predictor of a child's cognitive development. A sample of 9 children shown their parent-child interaction time and cognitive tests scores as below. 1. Base on the regression equation, estimate the predicted cognitive level for a child whose parent interacts with him 6 hours per day?
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A scientific foundation wanted to evaluate the relation between y= salary of researcher (in thousands of dollars), x1= number of years of experience, x2= an index of publication quality, x3=sex (M=1, F=0) and x4= an index of success in obtaining grant support. A sample of 35 randomly selected researchers was used to fit the multiple regression model. Parts of the computer output appear below. Based from the table, what is the constant term of the multiple linear regression?
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create graph of the two-variable data with a regression line, r, r2, and separate residual plot
A group of scientists are interested in finding out whether the days of rainfall during the dry season could predict the magnitude of butterfly migration in the local area during wet season. Every year for twenty years, they count the total days of rainfall during the dry season preceding the migration and measure the number of butterflies migrating in the following wet season. Which type of statistical test should they use to analyze their data? (pearson's r correlation OR, simple regression equation)
** had to resubmit this question because the first time the data was duplicated and reflected incorrectly. The table below gives the number of hours spent unsupervised each day as well as the overall grade averages for seven randomly selected middle school students. Using this data, consider the equation of the regression line, yˆ=b0+b1xy^=b0+b1x, for predicting the overall grade average for a middle school student based on the number of hours spent unsupervised each day. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Hours Unsupervised 1 2 3 4 5 5.5 6 Overall Grades 96 89 87 77 76 68 64 **Please circle the answer for each step so I don't get confused. Thanks in advance for helping me with the breakdown and notes** Step 1 of 6 : Find the…