Given the following regression source table, can we say that the slope is significant at 5%? (Use the exact values given in the table.)Summary OutputRegression StatisticsMultiple R0.97333R Square0.94737Adjusted R Square0.921053Standard Error0.643797Observations4ANOVAdfSSMSFSignificance FRegression 1 14.921052 14.921052 35.9999710.0266715Residual2 0.8289480.414474Total315.75Coefficients Standard Errort Stat P-valueLower 95%Upper 95%Intercept2.513160.798793.14621 0.08791-0.923765.95008X0.626640.104446.00000 0.026670.177271.07601We ---Select--- ✓ conclude that the slope is significant because the p-value ofgiven in the table is ---Select---0.05.

The table provided in the question that contains the result of the hypothesis test for the slope is…

Answered: Given the following regression source…

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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Use the following ANOVA table for regression to answer the questions. Analysis of Variance Source DF SS MS F P Regression 1 285.4 285.4 1.85 0.176 Residual Error 174 26848.2 154.3 Total 175 27133.6 Give the F-statistic and p-value. Enter the exact answers. The F-statistic is The p-value is eTextbook and Media Hint 63°F Cloudy Type here to search Pa DII PrtScn F8 Home F9 End F10
A multiple regression analysis produced the following tables. Summary Output Regression Statistics Multiple R 0.978724022 R Square 0.957900711 Adjusted R Square 0.952287472 Standard Error 67.67055418 Observations 18 ANOVA df SS MS F Significance F Regression 2 1562918.941 781459.5 170.6503 4.80907E-11 Residual 15 68689.55855 4579.304 Total 17 1631608.5 Coefficients Standard Error t Stat P-value Intercept 1959.709718 306.4905312 6.39403 1.21E-05 X1 -0.469657287 0.264557168 -1.77526 0.096144 X2 -2.163344882 0.278361425 -7.77171 1.23E-06 For x1= 360 and x2 = 220, the…
Which of the following is not a requirement for regression analysis? Choose the correct answer below. O A. The method for regression analysis line is not robust. It is seriously affected by a small departure from a normal distribution. O B. Visual examination of the scatterplot shows that the points approximate a straight-line pattern. O C. The sample of paired (x,y) data is a random sample of quantitative data. OD. Outliers can have a strong effect on the regression equation, so remove any outliers if they are known to be errors.
A multiple regression analysis produced the following tables. Predictor Coefficients StandardErrort Statistic p-valueIntercept 624.5369 78.49712 7.956176 6.88E-06x 8.569122 1.652255 5.186319 0.000301x 4.736515 0.699194 6.774248 3.06E-05Source df SS MS F p-valueRegression2 1660914 830457.1 58.319561.4E06Residual 11 156637.5 14239.77Total 13 1817552The adjusted R is ____________.0.91380.88910.88510.8981
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Use the following ANOVA table for regression to answer the questions. Analysis of Variance Source DF SS MS F P Regression 1 293.3 293.3 2.01 0.158 Residual Error 174 25386.6 145.9 Total 175 25679.9 The F-statistic is _____________.The p-value is ___________________
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The summary output obtained from fitting the multiple regression are given below. Model Unstandardized Coefficients Standardized Sig. Coefficients B Std. Error Beta -3.512 (Constant) Education (years) -3019.226 859.789 .000 658.518 45.852 .581 14.362 .000 Gender -1615.440 253.239 -.249 -6.379 .000 Age (years) 45.008 10.469 .163 4.299 .000 Dependent Variable: Beginning Salary, Male=0 & Female=1. (a) Write down the estimated multiple regression model of the beginning salary on education, gender and age of employees of a company. (b) Interpret estimated regression coefficient values. (c) Find the predicted beginning salary for an employee who is 24 years old male and has 17 years of education.
A sales manager for an advertising agency believes there is a relationship between the number of contacts that a salesperson makes and the amount of sales dollars earned. A regression analysis shows the following results. Coefficients Standard Error t-Stat p-value Intercept -12.201 6.560 -1.860 0.100 Number of contacts 2.195 0.176 12.505 0.000 ANOVA df SS MS F Significance F Regression 1.00 |13,555.42 |13,555.42 156.38 0.00 Residual 8.00 693.48 86.68 Total 9.00 14,248.90 Assume that X = 33.4 and E(X – X) 2814.4. Rounding to one decimal place, the 95% confidence interval for 30 calls is
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

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