Assignment2_CategoricalVariables_ShubhamJethwa

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Statistics

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Feb 20, 2024

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1/ 11 Assignment 2 Bank Marketing Case Study: Categorical Attributes Check The head of Marketing wants to know which customers have the highest propensity for buying a Certificate of Deposit (CD) from the institution. The goal of this assignment is to check errors in character variables and correct them. Learning outcomes  Use PROC FREQ to inspect errors in character variables.  Use character functions for data cleaning  Use 2x2 contingency table to examine dependency between variables by looking at Chi- square test.  Use mosaic plot to visually examine dependency between variables

2/ 11 Readings: Simple frequency table: http://support.sas.com/training/sas94/m15_2.htm (http://support.sas.com/training/sas94/m15_2.htm) 2x2 contingency table: A contingency table shows the frequency distribution of the variables in a matrix format, while a mosaic plot graphically displays the information. Look here for an example: http://assets.csom.umn.edu/assets/163747.pdf (http://assets.csom.umn.edu/assets/163747.pdf) https://support.sas.com/documentation/cdl/en/statug/63962/HTML/default/viewer.htm#statug_freq_sec (https://support.sas.com/documentation/cdl/en/statug/63962/HTML/default/viewer.htm#statug_freq_sec Mosaic plot: https://blogs.sas.com/content/iml/2013/11/04/create-mosaic-plots-in-sas-by-using-proc-freq.html https://towardsdatascience.com/mosaic-plot-and-chi-square-test-c41b1a527ce4 Measuring association between categorical variables: The null hypothesis for a chi-square independence test is that two categorical variables are independent in some population. The p-value is given by the area under the right tail after the χ² test value. p=P[X>=chisquareValue]. Usually we can say two variables are related (we’re rejecting the null hypothesis of independence) if p-value<0.01 (sometimes also p- value<0.05 is considered statistically significant) and we can assume the two variables are related. You can find the p-value in the third column of the statistics table. https://support.sas.com/documentation/cdl/en/statug/63962/HTML/default/viewer.htm#statug_freq_sec The range of Cramer’s V is [-1 1] for 2x2 tables The range of the phi coefficient is [-1 1] for 2x2 tables. The contingency coefficient is a measure of association derived from the Pearson chi-square and is >0. https://www.statisticshowto.datasciencecentral.com/contingency-coefficient/ Understanding Contingency Coefficient Values A contingency coefficient is particularly informative if you’re working with a large sample. The contingency coefficient helps us decide if variable b is ‘contingent’ on variable a. However, it is a rough measure and doesn’t quantify the dependence exactly; It can be used as a rough guide: If C is near zero (or equal to zero) you can conclude that your variables are independent of each other; there is no association between them. If C is away from zero there is some relationship; C can only take on positive values.

3/ 11 Q1. Examine the target variable y:  Use PROC FREQ to list a simple frequency table for the variable y. Q2. Examine the variable "contact" and study its dependency with the target variable y.  Use PROC FREQ to list a simple frequency table for the variable "contact".  Examine the output for invalid values.

4/ 11 Q3. Contingency table Contact by y and mosaic plot:  Create a 2x2 contingency table along with a mosaic plot. Show the statistics for a table of contact by y.

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