Let’s Have a Cup of Tea!

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# Let’s Have a Cup of Tea! - PowerPoint PPT Presentation

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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### 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
• 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.
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)
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
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
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?
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
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
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 …

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

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

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.