MKF2121 Week 10 Moodle1.pdf - Lecture 10 JM1 Lecture 10 Linear Regression Dr Junzhao Ma MKF2121 Marketing Research Methods Department of Marketing

# MKF2121 Week 10 Moodle1.pdf - Lecture 10 JM1 Lecture 10...

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Lecture 10 MKF2121 1 Lecture 10 Linear Regression Department of Marketing Dr. Junzhao Ma MKF2121 Marketing Research Methods JM1 Today’s agenda 2 Quick review of statistical tests covered to date Linear regression What it is about and how to use it Using dummy variable in a linear regression Application: using linear regression for t test and correlation analysis Taxonomy of different statistical tests 10/4/2018 4 Hypothesis Testing Test of Association (relational RQ) Test of Differences (comparative RQ) Means Proportions Different forms of t test Cross tabulation Correlation Multiple regression Lecture 10 MKF2121 2 Association btw 2 categorical variables Test of association Association btw 2 metric variables Mean diff. btw 1 metric var. and constant Something = 5 Mean diff. of 1 metric variable btw. 2 groups Weight of males vs Weight of females Mean diff. btw 2 metric variables Attitude before vs Attitude after (same ind.) Mean diff. of 1 metric var. among >2 groups Prices of brands A,B and C One sample T-test Independent samples T-test Paired samples T-test One-way ANOVA Which test should you choose? –depends on hypothesis Cross-tabulation (Chi-squared test) Correlation analysis Interpreting SPSS results - what is the outcome of your test? If the p‐value (Sig.) < 0.05 If the p‐value (Sig.) ≥ 0.05 reject H 0 , go to step 2 do not reject H 0 . State H 0 in conclusion Step 1 Step 2 clearly state the relationship between variables or the differences between groups An very important point about the statistical techniques we learned in week 8,9 and the regression analysis this week 7 The inference we make with these techniques are statistical in nature The implication of this is two fold The conclusions we draw using these techniques are descriptive (i.e., not causal*) The conclusions are probabilistic (i.e., true only “on average”, and not deterministic) *although they could be (and often are) used as evidence to infer causality in some context Lecture 10 MKF2121 3 9  • • • 