The researcher performs an analysis of variance (ANOVA) to test the hypothesis that the populations defined by the treatment combinations are equal.The results are presented in the following ANOVA table.SourceBetween treatmentsFactor AFactor BAXB interactionWithin treatmentsTotalANOVA TableSS1,607.187537.8120645.9380 3923.4400 35,127.4975 726,734.6875 79df71 37.8120 0.53215.3127 3.02307.8133 4.3271.2152MSFUse the significance level a = 0.05 to complete the following conclusions.The critical F value for factor A (years in military) is 3.97. Therefore, the main effect due to factor A isThe critical F value for factor B (program component) is 2.73. Therefore, the main effect due to factor B isThe critical F value for the interaction of factors A and B is 2.73. Therefore, the effect due to the interaction of factors A and B is Given the results of the preceding analysis, what does the researcher conclude?O Veterans who took different components of the program had different PTSD symptom scores. The severity of PTSD symptoms wasunrelated to length of service either by itself or in conjunction with the various components of the program.O Neither length of service nor program component was related to the severity of PTSD symptoms when looked at alone. However, therewas an interaction between the two factors such that severity differed by program component differently depending on length of service(and vice versa).O Veterans who took different components of the program had different PTSD symptom scores. By itself, length of service was notassociated with differences in severity; however, the various components of the program resulted in different degrees of PTSD symptomsdepending on length of service.O Length of service and program component were each related to the severity of PTSD symptoms. However, the effect of each factor wasindependent of the other.Measure the effect size for factor A (years in military), factor B (program component), and the interaction by computing (partial) eta squares.(Express the value of each eta square as a percent.)n² for factor A (years in military)=n² for factor B (program component)n² for the interaction =

The output of the two-way ANOVA is given. Source SS df MS F Critical value Between 1607.1875 7…

Answered: Use the significance level a = 0.05 to…

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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please answer correctly:
The marketing manager wants to estimate the effect of the MBA program on Salary controlling for the other factors. Which regression model is the MOST appropriate? Oa. Salary = B_0+B_1 MBA + ε Ob. Salary = 3_0+ B_1 MBA + B_2 Work + e c. Salary = B_0+B_1 MBA+B_2 Work + B_3 Age +8 Od. Salary = B_0+ B_1 MBA + B_2 Work + B_3 Age +B_4 Gender + ε
when a regression is used as a method of predicting dependent variables from one or more independent variables. How are the independent variables different from each other yet related to the dependent variable?
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An agricultural field trial compares the yield of two varieties of corn. The researchers divide in half each of 8 fields of land in different locations and plant each corn variety in one half of each plot. After harvest, the yields are compared in bushels per acre at each location. The 8 differences (Variety A - Variety B) give x¯=3.07 and s=5.11. Does this sample provide evidence that Variety A had a higher yield than Variety B? (a) State the null and alternative hypotheses: (Type "mu" for the symbol μμ , e.g. mu > 1 for the mean is greater than 1, mu < 1 for the mean is less than 1, mu not = 1 for the mean is not equal to 1)H0 : Ha : (b) Find the test statistic, t = 7,6

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