MKF2121 Week 09 moodle.pdf - Lecture 9 Hypothesis Testing Related to Differences(and some tips about assignment 2 Dr Junzhao Ma MKF2121 2 Marketing

# MKF2121 Week 09 moodle.pdf - Lecture 9 Hypothesis Testing...

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1 Lecture 9 Hypothesis Testing Related to Differences (and some tips about assignment 2) Department of Marketing Dr. Junzhao Ma MKF2121 Marketing Research Methods 2 Today’s agenda 3 Hypothesis testing – tests of differences Different types of t tests One-way ANOVA How to write about hypothesis testing A few words on assignment 2 Quick review of week 8 material Hypothesis testing Cross tabulation/chi- square test 4 Key Concepts Sample vs. population characteristics Null vs. alternative hypothesis Test statistic P Value Cross tabulation/chi square test 2 The procedure of hypothesis testing is the same for different RQs. What is different is 1. the test you use and 2. how to interpret the results if you reject the null hypothesis 5 1. Problem Definition (RQ) 2. Clearly State the Null and Alternative Hypotheses 3. Choose the relevant statistical test 4. Calculate p-value 5. Is p-value<0.05?NoDo not reject null 1. One Sample 2. Two Independent Samples 3. Paired Samples 4. More Than Two Samples The different types of tests of differences t tests ANOVA 7 3 All the tests of differences are about comparing average values 8 One sample t test Compare the average value of one variable to a constant Example RQs – Is the mean service rating above 5? – Is average customer spending equal to \$500? – Is the average miles per gallon (fuel efficiency measure) equal to 30? 17-9 Paired samples t test Compare the average value of two variables (from one group of respondents) • Example – Is the mean consumer rating for McDonalds different from that of Hungry Jacks? – Is consumers’ mean willingness to pay for iphone 6 different from that of Samsung S6? 17-10 4 Two independent samples t test Compare the average value of one variable from two different groups Example RQs – Does the mean rating for the new iphone 7 differ between users and non-users? – Does the mean purchase intention differ between men and women? 17-11 Which t test to use? 1 Group 2 Groups 1 metric Variable One sample t test H 0 : pop mean = value Two Independent samples t test H 0 : pop mean for 1 st pop = pop mean for 2 nd pop 2 metric Variables Paired Sample t test H 0 : pop mean var 1 = pop mean var 2 17-12 Why are they all called t tests? t statistic P value* = the shaded area Because their test statistic follows a t distribution 17-13 5 Hypothesis Testing Using the t Statistic – same as before 17-14 1. Problem Definition (RQ) 2. Clearly State the Null and Alternative Hypotheses 3. Choose the relevant statistical test (one of the t tests) 4. Calculate p-value  • • • 