You are testing for a correlation between day length and movement in a certain beetle and find that, even after several transformations, your data do not follow a normal distribution. What would be the best option for a statistical test in this case?

Group of answer choices

The Pearson Correlation test

A non-parametric test like the Mann-Whitney U test

A non-parametric test like the Kruskall-Wallis test

A non-parametric test like the Spearman's Rank Correlation test

A non-parametric X2 test

\f5. The residuals from the wage-productivity regression were regressed on lagged residuals going back six periods (i.e. AR (6)) thereby yielding the following results: Dependent Variable: RESI Method: Least Squares Sample (adjusted) : 1965-1998 Included Observations: 34 after adjusting endpoints Variable Coefficient Std. Error t-Statistic Prob. 5. 590462 1.963603 2.847043 0. 0085 -0. 066605 0. 023469 -2. 838058 0. 0087 RESI (-1) 0. 814971 0. 216231 3.768978 0. 0009 RES1 (-2) -0. 268651 0. 273887 -0.980882 0.3357 RES1 (-3) -0. 106017 0. 272780 -0. 388652 0.7007 RES1 (-4) 0. 305630 0. 273258 1. 118467 0.2736 RES1 ( -5) -0. 064375 0. 280577 -0. 229438 0. 8203 RES1 (-6) 0. 216156 0. 222160 0.972976 0.3395 R? = 0. 8920 Durbin-Watson d stat 1. 7589 R = 0. 8629 a. What can you say about the nature of autocorrelation in the above regression result? b. If you think that an AR (1) mechanism characterizes autocorrelation, would you use the first difference transformation to get rid of autocorrelation? Justify your answer.For, G(5) = 5/(5 +25+1) Represent this system in 1. controllable canonical form (3) 2. observable canonical form (3) 3. is the system observable (4) 4. is the system controllable (4 )Question 1 1 pts Which type of modeling focuses on accurate predictions only? 0 Predictive modeling 0 Explanatory modeling Q Descriptive analytics 0 Multiple linear regression Question 2 1 pts A decision tree to predict the salary of an employee is called a 0 Regression Tree 0 Classication Tree 0 tree diagram 0 Categorical Variable Tree