MKT 3340 Study Guide - Midterm Guide: Chi-Squared Distribution, Null Hypothesis, Pivot Table

• School: UT-Dallas
• Department: Marketing Management
• Course: MKT 3340
• Professor: Prasad Ashutosh

Document Summary

Making analysis on your original data without using the original spreadsheet. Use statistical tool we will discover relationships between two variables. Consistent and systematic linkage between the levels (metric variables) or labels (categorical variables) for two variables. Examination of frequencies for two categorical variables in a cross-tabulation table to determine whether the variables have a significant relationship. Begins with the hypothesis (null) that the two do not have a significant relationship: cross tabulations, calculated expected cell frequency. = (cell column total x cell row total)/grand total: computed chi-square value. X2 = sum of all[(observed expected)2/expected: degrees of freedom df = (number of rows 1) * (number of columns 1) Find critical value on table using df and 95% confidence level: evaluate whether or not the null hypothesis of no relationship is supported. If smaller than computed chi square critical value then null hypothesis support (no relationship) If larger, then hypothesis not supported (significant relationship: how to present cross-tabulation findings.