I need help with this question 1. is the factor interaction significant? explain ## Multivariate TestsThis table presents the results of multivariate tests analyzing the effects of various factors. The table includes several statistical measures such as Pillai's Trace, Wilks' Lambda, Hotelling's Trace, and Roy's Largest Root, organized under different effects: Intercept, satjob2, agecat4, and the interaction of satjob2*agecat4.### Column Descriptions:1. **Effect**: The variables or combinations of variables being tested.2. **Value**: The test statistic value for each multivariate method.3. **F**: The F-statistic associated with the test.4. **Hypothesis df**: Degrees of freedom for the hypothesis.5. **Error df**: Degrees of freedom for the error.6. **Sig.**: Significance level, indicating the probability of the results occurring by chance. A value less than 0.05 typically indicates statistical significance.7. **Partial Eta Squared**: Represents effect size, indicating the magnitude of the effect.### Multivariate Test Methods:- **Pillai's Trace**: A test statistic used for multivariate hypothesis testing.- **Wilks' Lambda**: A test statistic that evaluates a null hypothesis in multivariate analysis.- **Hotelling's Trace**: A multivariate test statistic similar to the t-test.- **Roy's Largest Root**: A test statistic used particularly to detect the largest effect.### Notes:- The design tests the intercept, satjob2, agecat4, and their interaction.- Exact F statistic is indicated by superscript b.- Superscript c indicates an upper bound on F, providing a lower bound on the significance level.This table aids in understanding the effects of different variables and their combinations on the dependent variable in the context of multivariate analysis. The significance values help determine which effects are statistically significant.

Answered: I need help with this question 1. is…

Math

Statistics

I need help with this question 1. is the factor interaction significant? explain

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

The Simple Linear Regression model is Y = b0 + b1*X1 + u and the Multiple Linear Regression model with k variables is: Y = b0 + b1*X1 + b2*X2 + ... + bk*Xk + u Y is the dependent variable, the X1, X2, ..., Xk are the explanatory variables, b0 is the intercept, b1, b2, ..., bk are the slope coefficients, and u is the error term, Yhat represents the OLS fitted values, uhat represent the OLS residuals, b0_hat represents the OLS estimated intercept, and b1_hat, b2_hat,..., bk_hat, represent the OLS estimated slope coefficients. QUESTION 28 Suppose your estimated MLR model is: Y_hat = -30 + 2*X1 + 10*X2 Suppose the standard error for the estimated coefficient associated with X2 is equal to 5. Now, suppose that for some reason we multiply X2 by 5 and we re-estimate the model using the rescaled explanatory variable. What will be the value of the estimated coefficient of X2 and its standard error? The estimated coefficient of X2 will be equal to 50 and its standard error will be…
I need help with this assaigment
subject: Quantitative Analysis For Business Please answer both. Use the image for question 10. 10. A hair stylist used market research to learn that members of different age groups have different preferences for positive and negative advertisements. Research participants could mark their preference for only one of the two ads. The positive ad presented a model with attractive hair supported by a message affirming the decision to schedule hair styling services, whereas the negative ad displayed a model with unattractive hair supported by a message describing the need for hair styling services. Results are shown in the table below: What is the probability of a site visitor either preferring negative ads or being a member of age category B? 6% 62% 56% 68% 93% 11. A hair stylist averaged 21 clients per day over the past several months. Typically four of these clients have been male. What is the probability for the total number of female clients the hair stylist can expect…
Which below describes an interaction between 2 variables? a. the effect of one independent variable depends on the levels of the second variable b. both variables are equally influenced by a third factor c. the two variables are differentially affected by a third variable d. both variables produce a change in the subjects' scores
i need this. HELP ASAP 13) The categorical variable marital status has the following values: single, married,separated, divorced, and widowed. To include marital status in a multiple regressionmodel, how many indicator variables will be included?A) ThreeB) TwoC) FiveD) OneE) Four
We use the form ŷ = a + bx for the least-squares line. In some computer printouts, the least-squares equation is not given directly. Instead, the value of the constant a is given, and the coefficient b of the explanatory or predictor variable is displayed. Sometimes a is referred to as the constant, and sometimes as the intercept. Data from Climatology Report No. 77-3 of the Department of Atmospheric Science, Colorado State University, showed the following relationship between elevation (in thousands of feet) and average number of frost-free days per year in Colorado locations. A Minitab printout provides the following information. Predictor Constant Elevation Coef 315.00 -29.166 SE Coef 28.31 3.511 I 11.24 -8.79 P 0.002 0.003 S = 11.8603 R-Sq = 96.44 Notice that "Elevation" is listed under "Predictor." This means that elevation is the explanatory variable x. Its coefficient is the slope b. "Constant" refers to a in the equation ŷ = a + bx. (c) The printout gives the value of the…
The outcome variable is degree of brand liking (measured essentially as some sort of percentage). Higher numbers mean it was “liked” more. There are two potential predictors. The first is moisture content which is controlled at levels of 4, 6, 8, and 10. The second is sweetness, the recorded values are 2 and 4. (Matrix plot is attached) Comment on what you expect the regression analysis to show with regard to the relationship of the two predictors with the response. Comment on the scatterplot that shows the predictors against each other. Note that each “point” on this graph in fact represents 2 data points. What does this imply about the “experimental design”? About “collinearity”? About the ways in which we will be able to discuss the effects of moisture and sweetness?
Need help with this question. Thank you :)
а. Complete the table. (or just write answers) Xi Yi 2 2 3 4 Totals E x; = E yi = Exf = Σχy Find SSxy, SSXX B1. x, y, and fo- Write the equation of the least squares line. b. C. d) What will be y if x=10
Your answer is incorrect. Let u = (-3, 1, 7), v = (3,0, –6), and w = (6,-1, -3) Find the components of v – w. v - w = (-4,1, 3) eTextbook and Media Hint Submit Ans Attempts: 2 of 3 used Save for Later Using multiple attempts will impact your score.