The data in the figure below most likely portrays d a1 a2 b₁ b2 O a main effect for (b) No answer text provided. a main effect for (a) O an interaction between (a) and (b)
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- Consider the matrixes What does null (A) mean? I am confusedConsider the equations describing the interactions of robins ? and worms ?Suppose that we performed an estimate of the determinants of players' salaries for the 2018 NFL season. The R? = 0.65 for the regression that included 3 explanatory variables. Imagine that we decided to add an additional explanatory variable (like the players' previous playoff experience). When we run the regression with the additional explanatory variable the R2 = 0.78 is for the regression. We can interpret this as the additional explanatory variable is significant at the 5% level. the additional explanatory variable has lowered the explained sum of squares measure in the regression. the additional explanatory variable is related to player salary and does belong in the regression. the additional explanatory variable is not related to player salary and does not belong in the regression.
- Which of the following correspond to the adjacency matrix?Can you show that Q is an intensity matrix?A study was conducted to investigate effects of physical training. Sample data from ten subjects are listed below, with all weights given in kilograms. (See “Effect of Endurance Training on Possible Determinants of VO2 During Heavy Exercise,” by Casaburi et al., Journal of Applied Physiology, Vol. 62, No. 1.)a. Is there sufficient evidence to conclude that there is a difference between the pre-training and post-training weights? What do you conclude about the effect of training on weight?b. Construct a 95% confidence interval for the mean of the differences between pre-training and post-training weights.Pre-training: 99 57 62 69 74 77 59 92 70 85Post-training: 94 57 62 69 66 76 58 88 70 84
- In discriminant analysis the discriminant function is on the basis of: a. Correlation co-efficient b. F statistic c. Linear Regression d. Eigen valuesConsider a linear model to explain monthly beer consumption: beer = Bo + Biinc + Bzprice + Bzeduc + Bafemale + u E(ulinc, price, educ, female) = 0 Var(ulinc, price, educ, female) = o²inc². Write the transformed equation that has a homoskedastic error term.A predictive model's performance is presented below with following confusion matrix: [84 181 l14 38 Calculate G-mean for the given confusion matrix and give interpretation on the results.
- Consider a probit model with an interaction term: Pr(y = 1|r) = (Bo + B1r1+ B2r2 + Bza1 x r2) a. What is marginal effect of r1? b. Now suppose B = (1, -2,3,-1) find the marginal effect of r if r1 = 0 and %3D %3D 22 = 0. c. Now suppose 3 = (1, –2, 3,-1) find the marginal effect of r1 if r1 = 0 and %3D 12 = 1. d. Now suppose B = (1,-2, 3, –1) find the marginal effect of r if r, = 1 and %3D %3D I2 = 0. e. Now suppose B = (1,-2, 3,-1) find the marginal effect of ai if ri T2 = 1. 1 andAn ecologist models the interaction between the tree frog (P) and insect (N) populations of a small region of a rainforest using the Lotka-Volterra predator prey model. The insects are food for the tree frogs. The model has nullclines at N=0, N=500, P=0, and P=75. Suppose the small region of the rainforest currently has 800 insects and 50 tree frogs. In the short term, the model predicts the insect population will • and the tree frog population will At another point time, a researcher finds the region has 300 insects and 70 tree frogs. In the short term, the model predicts the insect population will * and the tree frog population willWhat is the output of the block diagram shown in the figure? X1 d dt X2 x3 = d³x₁ dt 3 Option 1 x3 = + Option 3 d² X1 dt² d -[ dt x1 d³x₁ + dt 3 dt² d² + d² dt² d dt dx2 dt dx2 dt d dt d³x₁ X3 dt = O Option 2 x3 = d³x₁ dt³ O Option 4 + + d² x1 dt d² dt² - X3 dx2 dt dx2 dt