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    Contingency Tables and Odds in Excel
    In the prerequisite courseQuantitative Reasoning and Analysis you constructed basic contingency (crosstab) tables. You might be surprised to learn that you can estimate a simple logistic regression model with a categorical predictor using the descriptive values presented in the crosstab table.
    In this assignment you use Microsoft Excel to construct a specialized tool that creates basic logistic regression models given a crosstab/contingency table. As if that were not useful enough this Excel tool is not specializedyou can use it given any crosstab/contingency tables you encounter in research. In the field of statistical research this is just about as exciting as you can get!
    To prepare
    The Assignment
    Using one of the datasets provided select two variables that allow you to construct a 22 contingency table. Use SPSS to run the initial crosstab table using any two variables that you think are appropriate. Then use Excel to construct a table in which you report:
    Be sure to apply the template from the Osborne text. Note that page 42 has a completed example that should help you determine these values. Be sure to use formulas and cell references in Excel so that the spreadsheet you create can be used as a tool for calculating similar values for other datasets.
    Once you have created the tool write a 1- to 2-paragraph summary in APA format interpreting your results. Submit both your Excel file and your summary to complete this assignment.
    Possible References
    Datasets
    I placed in the zip file I also converted them to Excel in case they are unable to open NOTE I do need all the output results in SPSS thanks
    Readings
    Osborne J. W. (2015).Best practices in logistic regression. Thousand Oaks CA: SAGE Publications.
    Best Practices in Logistic Regression 1st Edition by Osborne J.Copyright2015 by Sage College. Reprinted by permission ofSage College via the Copyright Clearance Center.
    These chapters provide simple examples that demonstrate important aspects of logistic regression including how logistic regression is distinct from ordinary least squares (OLS) regression and how it is much more effective than OLS regression in predicting dichotomous variables.
    These I also attached to the files section in case they can’t be opened
    Chapter 1 A Conceptual Introduction to Bivariate Logistic Regression (PDF)
    Chapter 2 How Does Logistic Regression Handle a Binary Dependent Variable? (PDF)

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