17. Additional information was obtained from EXCEL. Conduct a test of hypothesis to determine if anyof the regression coefficients do not equal 0 Use the 005 significance level. The regressionequation is:Salary = 19.2 + 3.10 Years + 0.269 Perform - 0.704 AbsentInterceptYearsPerformAbsentCoefficients Standard Error19.1863.0960.269-0.70412.1460.7060.1200.586 -1.202t Stat1.5804.385P-value0.1430.0010.0460.2552.252а. Но:H:Họ:H1:Họ:H1:b. The decision rules are to reject Ho ifWhat is your decision? Interpret.c.305 Multiple Regression and Correlation AnalysisChapter 14

From the given information, a. H0: The coefficient of years is equal to 0. H1: The coefficient of…

Answered: Additional information was obtained…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

Consider the following data: x¯ = 20, sx = 2, y¯ = −5, sy = 4, and b1 = 0.40. Which of the following is the sample regression equation?
Listed below are systolic blood pressure measurements (in mm H) obtained from the same woman. Find the regression equation, letting the fight arm blood pressure be the predictor (x) variable, Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 90 mm Hg. Use a significance level of 0.05. Right Arm 100 99 93 76 77 9 Left Arm 176 169 118 145 146 EB Click the icon to view the critical values of the Pearson correlation coefficient r The regression equation is 9 = 7 + 7x (Round to one decimal place as needed.) Given that the systolic blood pressure in the right arm is 90 mm Hq, the best predicted systolic blood pressure in the left arm is mm Hg. (Round to one decimal place as needed.)
Fifty matched pairs of magnitude/depth measurements randomly selected from 10,594 earthquakes recorded in one year from a location in southern California. Find the best predicted depth of an earthquake with a magnitude of 2.2. Use a significance level of 0.05. : Click the icon to view the earthquake measurements. Click here to view the critical values of the Pearson correlation coefficient, r. The regression equation is y = ? + ?x. 回-ト i Critical Values of the Pearson Correlation Coefficient r (Round to one decimal place as needed.) Critical Values of the Pearson Correlation Coefficient r α= 0.05 0.950 0.878 0.811 0.754 0.707 0.666 0.632 0.602 0.576 a = 0.01 0.990 0.959 0.917 0.875 0.834 0.798 0.765 0.735 0.708 NOTE: To test Ho: p=0 Jagainst H,: p#0, reject H, if the absolute value of r is greater than the critical value in the table. 5 10 11 12
Consider the following computer output from a multiple regression analysis relating the cost of car insurance to the variables: number of car accidents, driver's credit score, and safety rating of the car. Answer Coefficients Coefficients Standard Error 680 Intercept Car Accidents (In last 3 years) Credit Score -74.80 Safety Rating - 104.25 122.40 Does the sign of the coefficient for the variable number of car accidents make sense? 79.71 14.75 8.89 11.46 t Stat P-value 8.531 0.0000 0.0000 8.298 -8.414 -9.097 0.0000 0.0000 O Yes, because it is expected that as the number of car accidents increases then the cost should also increase. O No, because it is expected that as the number of car accidents increases then the cost should also increase. O Yes, because it is expected that as the number of car accidents increases then the cost should decrease. O No, because it is expected that as the number of car accidents increases then the cost should decrease. Keyp- Keyboard Short Tables
Conduct a hypothesis for whether consumption and income are linearly related using ? =0.01. The standard error of the slope is 0.144. Slope = 0.75, Intercept = 0, sample:Income 9, 11, 5, 8, 2, 9, 12Consumption 7, 7, 2, 7, 2, 8, 9 Step 1: State the null and alternative hypotheses.Step 2: Choose the significance level.Step 3: Calculate the test statistic.Step 4: Find the critical value(s).Step 5: Compare the test statistic to the critical value(s).Step 6: State the conclusion.
Find the regression equation, lotting the diameler be the predictor (x) variable. Find the best predicted circumference of a marble with a diameter of 1.3 cm. How does the result compare to the achual circumference of 4.1 cm? Use a significance level of 0.05 Baseball Basketball Golf Soccer Tennis Ping Pong Volleyball 7.3 Diameter Circumference 23.5 4.4 21.9 7.1 3.9 21.4 22.9 73.8 13.8 68.8 22.3 12.3 67.2 Click the icon to view the critical values of the Pearson correlation coefficient r The regression equation is y = x (Round to five decimal places as needed.)
The best predicted circumference for a diameter 1.2 cm is?
Find the regression equation, letting overhead width be the predictor (x) variable. Find the best predicted weight of a seal if the overhead width measured from a photograph is 2.1 cm. Can the prediction be correct? What is wrong with predicting the weight in this case? Use a significance level of 0.05. Overhead Width (cm) 8.1 7.6 8.9 7.7 8.6 9.8 Weight (kg) 156 166 213 138 197 251 Click the icon to view the critical values of the Pearson correlation coefficient r. The regression equation is y = (Round to one decimal place as needed.)
Write the formula for the estimated regression line and interpret the slope of the estimated regression line, the intercept of the estimated regression line- Is it meaningful?, and the estimated R2. Based on the fitted regression model, what is the predicted ATST for a child who is 7 years old? What is the correlation between AGE and ATST? Does the residual plot suggest that the fitted regression line is inappropriate for these data? Explain why or why not. Suppose that a new subject is added to the study data and that subject is 12.5 years old with an ATST of 580 minutes. If the regression model were to be refit with this additional data point, would the new slope be greater than or less than -14.041? Justify your response.
b. Use statistical software to replicate the following regression analysis with all the Independent variables. Compute the coefficient of multiple determination. (Negative amounts should be indicated by a minus sign. Round your answer to 3 decimal places.) The regression equation is Paralegal GPA = -0.411 +1.20 HSGPA + 0.00163 SAT_Verbal - 0.00194 SAT_Math Predictor Constant HSGPA SAT Verbal SAT Math 0.001629 -0.001939 Coefficient SE Coefficient -0.4111 1.2014 t 0.7823 -0.53 р 0.622 0.2955 0.002147 4.07 0.010 0.76 0.482 0.002074 -0.94 0.393 Analysis of Variance SOURCE DF SS Regression 3 4.3595 MS F 1.4532 10.33 р 0.014 Residual Error 5 0.7036 0.1407 Total 8 5.0631 Source DF Seq SS HSGPA 1 4.2061 SAT Verbal 1 0.0303 SAT Math 1 0.1231 Coefficient of multiple determination Conduct a global test of hypothesis from the preceding output. c-1. State the decision rule at the 0.05 level of significance. (Round your answer to 2 decimal places.) Reject H₂ if F> c-2. Compute the value of F. (Round…
The local utility company surveys 12 randomly selected customers. For each survey participant, the company collects the following: annual electric bill (in dollars) and home size (in square feet). Output from a regression analysis appears below: Bill 13.45 + 4.39*Size Coefficients Estimate Std. Error (Intercept) 13.45 Size 4.39 0.54 0.2 We are 90% confident that the mean annual electric bill increases by between dollars and dollars for every additional square foot in home size. Round your answers to three decimal places and enter in increasing order.
2

SEE MORE QUESTIONS

Recommended textbooks for you

MATLAB: An Introduction with Applications

Statistics

ISBN:

9781119256830

Author:

Amos Gilat

Publisher:

John Wiley & Sons Inc

Probability and Statistics for Engineering and th…

Statistics

ISBN:

9781305251809

Author:

Jay L. Devore

Publisher:

Cengage Learning

Statistics for The Behavioral Sciences (MindTap C…

Statistics

ISBN:

9781305504912

Author:

Frederick J Gravetter, Larry B. Wallnau

Publisher:

Cengage Learning

MATLAB: An Introduction with Applications

Statistics

ISBN:

9781119256830

Author:

Amos Gilat

Publisher:

John Wiley & Sons Inc

Probability and Statistics for Engineering and th…

Statistics

ISBN:

9781305251809

Author:

Jay L. Devore

Publisher:

Cengage Learning

Statistics for The Behavioral Sciences (MindTap C…

Statistics

ISBN:

9781305504912

Author:

Frederick J Gravetter, Larry B. Wallnau

Publisher:

Cengage Learning

Elementary Statistics: Picturing the World (7th E…

Statistics

ISBN:

9780134683416

Author:

Ron Larson, Betsy Farber

Publisher:

PEARSON

The Basic Practice of Statistics

Statistics

ISBN:

9781319042578

Author:

David S. Moore, William I. Notz, Michael A. Fligner

Publisher:

W. H. Freeman

Introduction to the Practice of Statistics

Statistics

ISBN:

9781319013387

Author:

David S. Moore, George P. McCabe, Bruce A. Craig

Publisher:

W. H. Freeman

SEE MORE TEXTBOOKS