Introduction to t Test

1
Introduction to t Test

• 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
  means of 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
• 
  

2
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?

3
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 gt 0.05
• Learning Gains?
• P lt0.05

4
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 engagement in two types of multimedia
  training systems
• The article on user engagement
  
• 
  

5
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

6

• T(ea) for Two

• Is there significant difference in the intensity
  of eating disorder across different cultures
• 297 Australian-gt249 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

7
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 lt .0001
• T (fear of fat) -7.64, P lt 0.0001

8
Conclusion

• Judge by P value
• The probability that the difference is due to
  chance
• P lt 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.