ANOVA df Regression 2 Residual Total SS 72.6374 14 58.0438 16 130.681 InterceptUnemployment Advertising MS 36.3187 4.1460 Coefficients Standard error 17.5060-0.6879 0.0266 3.9817 0.2997 0.0068 F 8.760 t stat 4.397 -2.296 3.932 Significance F0.003 p-value 0.007 0.038 0.002 a. At the 5% significance level, test whether thepredictor variables jointly influence sales. b. At the 1% significance level, test whetherthe unemployment rate is negatively related with sales. c. At the 1% significancelevel, test whether advertising expenditures are positively related with sales.

The random variable under study is Sales Unemployment AdvertisementThe regression model is fitted on…

Answered: ANOVA df Regression 2 Residual Total SS…

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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12. What is the answer in (7) in the ANOVA Table?
The results of the regression analysis to estimate setup costs using the number of setup hours are as follows: SUMMARY OUTPUT Regression Statistics Multiple R 0.965127 R Square 0.931469 Adjusted R Square 0.921679 Standard Error 285.6803 Observations 9 ANOVA df SS MS F Regression 1 7765004 7765004 95.14395 Residual 7 571292.5 81613.21 Total 8 8336296 Coefficients Std Error t Stat P-value Intercept 2498.644 680.6304 3.671073 0.007953 X Variable 1 2.506915 0.257009 9.754176 2.52E–05 What percentage change (rounded to one decimal place) in setup costs can be explained by changes in setup hours? a.95.1% b.96.5% c.25.7% d.none of these e.93.1%
17. How many observations are there?
pre-test post-test Mean Variance -2.25 0.75 9.30 13.30 Observations 12 12 Pearson Correlation 0.9478 Hypothesized Mean 0 Difference df 11 t Stat 2.076 P(T<=t) one-tail 0.035 t Critical one-tail 1.796 P(T<=t) two-tail 0.065 t Critical two-tail 2.201
Ques = Homework: Ch 8 - Sampling Distributions Critical values of the correlation coefficient ars. Com - X Int. Critical Values for Correlation Coefficient Data table 3 0,997 4 0.950 5 0.878 6 0.811 7 0.754 Year Rate of Return of Company Rate of Return of Company ble. Chod 6 2 2007 0.203 0.402 8 0.707 9 0.666 10 0.632 2008 0.310 0.510 2009 0.267 0.410 11 0.602 12 0.576 13 0.553 14 0.532 15 0.514 16 0.497 2010 0.195 0.426 2011 -0.101 -0.060 2012 - 0.130 -0.151 2013 -0.234 -0.357 2014 0.264 0.328 17 0.482 18 0.468 19 0.456 20 0.444 21 0.433 2015 0.090 0.207 2016 0.030 -0.014 2017 0.128 0.113 2018 - 0.035 0.027 22 0.423 23 0.413 24 0.404 25 0.396 Print Done 26 0.388 27 0.381 Tne correlauon coeicient is- (Round to three decimal places as needed.) Print Done
32.
42. When a correlation is sufficiently high, what statistic is used to predict the outcome of the dependent variable from a single independent variable? Stepwise comparison Bivariate regression Coefficient of determination
The ANOVA table of the above data is as follows: ANOVA Source of Variation SS df MS 2.083 P-value Factor A J 1 0.725 Marketing startegies 0.750 1 0.750 0.832 Interaction 90.750 K 90.750 0.043 Within 125.333 15.667 Total 218.917 10. Calculate J and L 11. State HO and H1 hypotheses of interaction effect based on the above problem. 12. At a = 0.1, is there any significant effect? What is your decision? Support your answer. 13. What is your conclusion?
Based on the ANOVA table given, is there enough evidence at the 0.05 level of significance to conclude that the linear relationship between the independent variables and the dependent variable is statistically significant? Source df SS Regression 2 984.715358 Residual 7 298.884642 Total 9 1283.600000 ANOVA MS F 492.357679 11.531217 42.697806 Significance F 0.006092 Copy Data Ĵ Based on the ANOVA table given, is there enough evidence at the 0.05 level of significance to conclude that the linear relationship between the independent variables and the dependent variable is statistically significant? Source df SS Regression 2 984.715358 Residual 7 298.884642 Total 9 1283.600000 ANOVA MS F Significance F 492.357679 11.531217 0.006092 42.697806 Copy Data
Chapter 9, Section 2, Exercise 032 Use the following ANOVA table for regression to answer the questions. Response: Y Source DF Sum Sq Mean Sq F-value Pr(>F) Regression 1 355.21 355.21 14.76 0.000 Residual Error 359 8641.13 24.07 Total 360 8996.34 Give the F-statistic and p-value.Enter the exact answers.The F-statistic is=The p-value is=
Based on the table below, what is the value of SST? (round to 2 decimal places) ANOVA df SS MS Regression 96 0.18 3 28.06 10.712 Residual 146 12.09 Total Coefficients Standard Error t Stat P-value Intercept 2.28249535 0.47 4.88 0.164989 Exercise 0.25590156 0.08 3.1 5.577E-17 Your Answer: Answer
The key assumptions of the ANOVA include homogeneity of variance, normality of population distributions and: Independence of observations The DV must be measured on a nominal level The IV must be measured on a continuous level Variability of residuals

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