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Construct your initial multivariate model by selecting a dependent variable Y and two independent variables X. Clearly define what each variable represents and how this relates to the overall theme you've been assigned. Explain the reasons for constructing this model by discussing the expected relationship between the Y and each X variable.
Step Simple Regression Analysis
Complete a separate simple regression analysis for Y and each X that you have selected for the model. Provide the equation, interpret the slope, and state its significance.. Also discuss the overall model performance for each X variable by looking at the adjusted R square. You should also plot the relationship between Y and each X in your model. Use the results of this step to comment on whether the chosen independent variables are suitable for inclusion in a multiple regression analysis. If you determine that an X variable is not appropriate, you should replace it with another variable.
Type of Variable in Regression Analysis There are two types of variable in regression analysis. These are: a. Dependent variable b. Independent variable
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Chebychev inequality
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Correspondence Analysis (CA) is a generalization of PCA to contingency tables. The factors of correspondence analysis give an orthogonal decomposi:ion of the Chi- square associated
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