You have learned regression analysis model building and multilevel linear models, now please answer the following questions in detail by applying the knowledge that you have gained from readings and lectures. It is important to include hypothetical examples whenever applicable.
- Describe the objective of the multilevel linear model and state the underlying assumptions, formulation of the hypothesis, the test statistic, criterion for rejecting the null hypothesis, and possible test outcomes, provide a hypothetical example of formulating a hypothesis on the effect of the covariant.
- In answering the following questions, please include choice of significance level and the effect of p values.
a. Explain the curvilinear regression model, the independent and dependent variables, assumptions of the model, and the objectives, the approach to construct the model, ANOVA test on significance of the regression and how the result of this test is interpreted, the hypotheses on coefficients of the regression, how the results of testing these hypotheses are interpreted about significance of these coefficients in both unidirectional and bidirectional situations, interpretation of the effect of significant coefficients, testing normality of the observed residuals, the coefficient of determination, and what is its significance, the adjusted coefficient of determination and its significance, the effect of collinearity and diagnosing for it, using the model for prediction.
