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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

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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
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
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
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
slide5
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
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
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
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
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 …
slide10

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
slide11

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
slide12

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.