Question;Purpose Statement and Model;1) In the introductory paragraph, state why;the dependent variable has been chosen for analysis. Then make a general;statement about the model;?The dependent variable _______ is;determined by variables ________, ________, ________, and ________.?;2) In the second paragraph, identify the;primary independent variable and defend why it is important.;?The most important variable in this;analysis is ________ because _________.? In;this paragraph, cite and discuss the two research sources that support the;thesis, i.e., the model.;3) Write the general form of the;regression model (less intercept and coefficients), with the variables named;appropriately so reader can identify each variable at a glance;Dep_Var = Ind_Var_1 + Ind_Var_2 + Ind_Var_3;For instance, a typical model would be;written;Price_of_Home = Square_Footage +;Number_Bedrooms + Lot_Size;Where;Price_of_Home: brief definition of;dependent variable;Square_Footage: brief definition of first;independent variable;Number_Bedrooms: brief definition of second;independent variable;Lot_Size: brief definition of third;independent variable;[Note: student of course replaces these;variable names with his/her own variable names.]Definition of Variables;4) Define and defend all variables;including the dependent variable, in a single paragraph for each variable.;Also, state the expectations for each independent variable. These paragraphs;should be in numerical order, i.e., dependent variable, X1, then X2, etc.;In each paragraph, the following should be;addressed;< How is the variable defined in the;data source?;< Which unit of measurement is used?;< For the independent variables: why;does the variable determine Y?;< What sign is expected for the;independent variable's coefficient, positive or negative? Why?;Data Description;5) In one paragraph, describe the data and identify the data sources.;< From which general sources and from;which specific tables are the data taken? (Citing a website is not acceptable.);< Which year or years were the data;collected?;< Are there any data limitations?;Presentation and Interpretation of Results;6) Write the regression (prediction) equation;Dep_Var = Intercept + c1 *;Ind_Var_1 + c2 * Ind_Var_2 + c3*;Ind_Var_3;7) Identify and interpret the adjusted R2 (one paragraph);< Define ?adjusted R2.?;< What does the value of the adjusted R2reveal;about the model?;< If the adjusted R2 is;low, how has the choice of independent variables created this result?;8) Identify and interpret the F test (one;paragraph);< Using the p-value approach, is the;null hypothesis for the F test rejected or not rejected? Why or why not?;< Interpret the implications of these;findings for the model.;9) Identify and interpret the t tests for each of the coefficients (one separate;paragraph for each variable, in numerical order);< Are the signs of the coefficients as;expected? If not, why not?;< For each of the coefficients;interpret the numerical value.;< Using the p-value approach, is the;null hypothesis for the t test rejected or not rejected for each coefficient?;Why or why not?;< Interpret the implications of these;findings for the variable.;< Identify the variable with the;greatest significance.;10) Analyze multicollinearity of the;independent variables (one paragraph);< Generate the correlation matrix.;< Define multicollinearity.;< Are any of the independent variables;highly correlated with each other? If so, identify the variables and explain;why they are correlated.;< State the implications of;multicollinearity (if found) for the model.;11) Other (not required);< If any additional techniques for;improving results are employed, discuss these at the end of the paper.
Paper#62150 | Written in 18-Jul-2015Price : $32