QuestionPurpose 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:<\/p>\n
\u201cThe dependent variable _______ is determined by variables ________, ________, ________, and ________.\u201d<\/p>\n
2) In the second paragraph, identify the primary independent variable and defend why it is important.<\/p>\n
\u201cThe most important variable in this analysis is ________ because _________.\u201d In this paragraph, cite and discuss the two research sources that support the thesis, i.e., the model.<\/p>\n
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:<\/p>\n
Dep_Var = Ind_Var_1 + Ind_Var_2 + Ind_Var_3<\/p>\n
For instance, a typical model would be written:<\/p>\n
Price_of_Home = Square_Footage + Number_Bedrooms + Lot_Size<\/p>\n
Where<\/p>\n
Price_of_Home: brief definition of dependent variable<\/p>\n
Square_Footage: brief definition of first independent variable<\/p>\n
Number_Bedrooms: brief definition of second independent variable<\/p>\n
Lot_Size: brief definition of third independent variable<\/p>\n
[Note: student of course replaces these variable names with his\/her own variable names.]<\/p>\n
Definition of Variables<\/p>\n
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.<\/p>\n
In each paragraph, the following should be addressed:<\/p>\n
< How is the variable defined in the data source?<\/p>\n
< Which unit of measurement is used?<\/p>\n
< For the independent variables: why does the variable determine Y?<\/p>\n
< What sign is expected for the independent variable\u2019s coefficient, positive or negative? Why?<\/p>\n
Data Description<\/p>\n
5) In one paragraph, describe the data and identify the data sources.<\/p>\n
< From which general sources and from which specific tables are the data taken? (Citing a website is not acceptable.)<\/p>\n
< Which year or years were the data collected?<\/p>\n
< Are there any data limitations?<\/p>\n
Presentation and Interpretation of Results<\/p>\n
6) Write the regression (prediction) equation:<\/p>\n
Dep_Var = Intercept + c1 * Ind_Var_1 + c2 * Ind_Var_2 + c3 * Ind_Var_3<\/p>\n
7) Identify and interpret the adjusted R2 (one paragraph):<\/p>\n
< Define \u201cadjusted R2.\u201d<\/p>\n
< What does the value of the adjusted R2 reveal about the model?<\/p>\n
< If the adjusted R2 is low, how has the choice of independent variables created this result?<\/p>\n
8) Identify and interpret the F test (one paragraph):<\/p>\n
< Using the p-value approach, is the null hypothesis for the F test rejected or not rejected? Why or why not?<\/p>\n
< Interpret the implications of these findings for the model.<\/p>\n
9) Identify and interpret the t tests for each of the coefficients (one separate paragraph for each variable, in numerical order):<\/p>\n
< Are the signs of the coefficients as expected? If not, why not?<\/p>\n
< For each of the coefficients, interpret the numerical value.<\/p>\n
< Using the p-value approach, is the null hypothesis for the t test rejected or not rejected for each coefficient? Why or why not?<\/p>\n
< Interpret the implications of these findings for the variable.<\/p>\n
< Identify the variable with the greatest significance.<\/p>\n
10) Analyze multicollinearity of the independent variables (one paragraph):<\/p>\n
< Generate the correlation matrix.<\/p>\n
< Define multicollinearity.<\/p>\n
< Are any of the independent variables highly correlated with each other? If so, identify the variables and explain why they are correlated.<\/p>\n
< State the implications of multicollinearity (if found) for the model.<\/i><\/p>\n","protected":false},"excerpt":{"rendered":"
QuestionPurpose 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: \u201cThe dependent variable _______ is determined by variables ________, ________, ________, and ________.\u201d Read More …<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[],"tags":[],"class_list":["post-75845","post","type-post","status-publish","format-standard","hentry"],"_links":{"self":[{"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/posts\/75845","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/comments?post=75845"}],"version-history":[{"count":0,"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/posts\/75845\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/media?parent=75845"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/categories?post=75845"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.benedictsol.com\/blogs\/wp-json\/wp\/v2\/tags?post=75845"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}