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# Let’s Have a Cup of Tea!

Let’s Have a Cup of Tea! Minjuan Wang ED 690 T test Video 21. Inference for One Mean the t statistic for use when σ is not known. Emphasis is on paired samples and the t confidence test and interval.. 22. Comparing Two Means

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## Let’s Have a Cup of Tea!

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1. Let’s Have a Cup of Tea! Minjuan Wang ED 690

2. T test Video • 21. Inference for One Mean • the t statistic for use when σ is not known. Emphasis is on paired samples and the t confidence test and interval.. • 22. Comparing Two Means • How to recognize a two-sample problem and how to distinguish such problems from one- and paired-sample situations are the subject of this program.

3. Paired Samples T Test (T for one) • Inference for One Mean • http://learner.org/resources/series65.html?pop=yes&vodid=328482&pid=159# • Watch minutes: 12:30 to 20:58 • Paired t test on neutralsweet • Taste evaluation • One right after it is made • One after 4 months • H0= no differences in sweetness • Ha: one-tailed test (there are differences) • Before and after- sweetness values from each panelists • Calculate p (probability of chance)

4. Independent Samples (Tea for Two) • Comparing Two Means • http://learner.org/resources/series65.html?pop=yes&vodid=328482&pid=159# • Do women make more money after participating in the Options program in Baltimore? (a 3-year study) • Watch the beginning 10-11 minutes • N=1398 • The dataset will be too large for us to practice in class. • Pay attention to the t calculation on video

5. T(ea) for One (flow chart p. 208 of Salkind) • T test for dependent samples (paired t test) • To test hypothesis • Examine changes between one group of participant (or two matched pairs) on one or more variables • To compare if there is significant change in the meansof the variables studied • Example: • (Not significant) attitude change of 21 youth before and after their participation in Expeditions • Significant change in self-confidence and competence • 10 patients going through a 2-hour psychotherapy

6. Types of T(ea) for One • Repeated measures • Matched pairs • Two groups matched on critical variables • Example • E-classroom on fire • Compare the occurring frequency of flaming and buffoonery in traditional and E classrooms • Content analysis of discussions (counting) • Which test to use?

7. Interpretation (Results) • Level of significance • Indicates how much the differences found are due to chance rather than intervention • Usually set at 5% (a = 0.05) • Shown as Confidence interval = 95% • Attitudinal gains (change)? • P > 0.05 • Learning Gains? • P <0.05

8. T(ea) for Two • Flow chart p. 194 of Salkind) • T test for independent samples (unpaired t) • Test for a difference • Examine differences between two groups of participants on one or more variables • To compare if there is significant difference between the means of the variables studied • Examples: • Mid-term scores of class A and class B • User engagementin two types of multimedia training systems • The article on user engagement

9. Type of T(ea) for Two • Archetypal experiment • Randomly selected and assigned to 2 groups • Anti-depression drug versus placebo • T to compare mean differences on a depression measurement scale • In Situ design • Pre-assigned to 2 groups by nature or God • Insomnia on work efficiency • Gender and …

10. T(ea) for Two • Is there significant difference in the intensity of eating disorder across different cultures • 297 Australian->249 Indian University students • Eating Attitudes Test and Goldfarb Fear of Fat Scale • To measure Intensity of eating disorder • Run t test for independent samples (unpaired t-test) • Any difference on the mean of eating attitude scores • Any difference on the mean of Fear of Fat scores

11. Interpretation • Results: • Descriptive • Indian students scored higher on both of the tests (higher intensity) • Is the mean difference statistically significant? • Take it to unpaired t test for independent samples • T (eating attitude)= -4.19, p < .0001 • T (fear of fat)= -7.64, P < 0.0001

12. Conclusion • Judge by P value • The probability that the difference is due to chance • P < 0.0001 (very small chance that the differences are due to things other than group membership) • There are significant differences between Australian and Indian students in their intensity of eating disorder.

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