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Hypothesis Testing and Results Interpretation. By Minjuan Wang ED 690 Educational Technology. Types of Hypothesis. Null hypothesis There is no change, difference or relationship between A and B A starting point or a benchmark

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hypothesis testing and results interpretation

Hypothesis Testing and Results Interpretation

By Minjuan Wang

ED 690

Educational Technology

types of hypothesis
Types of Hypothesis
  • Null hypothesis
    • There is no change, difference or relationship between A and B
    • A starting point or a benchmark
    • Many articles have implied null hypothesis, but may not clearly stated.
    • Few studies are designed to verify the nonexistence of a relationship
  • Coffee maker is broken
    • no relationship between its broken and the humming birds on the tree outside my balcony.
alternative research hypothesis
Alternative/Research Hypothesis
  • Hypothesis that is implicitly accepted if the null hypothesis is rejected
    • Directional (one-tailed test)
    • Non-directional (two-tailed test)
  • Hypothesis: not to be proven but to be supported
    • Does your study fail if your hypothesis is not supported by the data?
hypothesis testing
Hypothesis testing
  • Core of Inferential Statistics
    • contributes to the science of education primarily by expanding, refining, or revising its knowledge base.
hypothesis testing procedure
Hypothesis Testing Procedure
  • Come up with a hypothesis
  • Set a: level of risk you are willing to take; or the cut-off point for a test result to be significant
  • Select the test
  • Compute the obtained value: t, f, r, etc.
  • Find the critical value in the respective table
  • To reject a null hypothesis->Obtained value must be > critical value
  • Otherwise, fail to reject null hypothesis (H0)
  • But, never “accept” null hypothesis
    • Many tests are needed to confirm that A is not different from or associated with B.
  • When rejecting null-P, the alternative 2-tailed P is implicitly accepted.
p from fancy schmancy software
P from Fancy Schmancy Software
  • Inferential statistics
    • T, ANOVA, Correlation, Regression
    • P is the probability of chance (indicator of significance)
    • Free us from the test tables
  • Results vary
    • P<.05
    • P<.001
    • P=.013 (the exact probability of the outcome/effect due to chance—SPSS)
      • Outcome: difference, change, or association
    • P>.05 or p=ns (nonsignificant)
      • The probability of rejecting a null-P exceeds 0.05 (the cut-off point) (Salkind)
      • So reject it
examples exercise
Examples & Exercise
  • Scenario:
    • two groups of patients: anti-depression drug group; and placebo group
    • Run t for two (null-HP)
  • t(58)=2.45, p<.05
    • t: the test that was used
    • 58: degree of freedom
    • 2.45: the obtained value
    • P: the probability of chance is within the cut-off point (level of significance/or risks allowed)
    • Significant mood difference exists between the two groups
    • So the treatment (drug) did work
examples exercise8
Examples & Exercise
  • Scenario:
    • two groups of patients: anti-depression drug group; and placebo group
    • Run t for two
  • t(58)=0.14, p>.05
    • t: the test that was used
    • 58: degree of freedom
    • 0.14: the obtained value
    • The probability of rejecting the null-p exceeds the cut-off point, so reject it!
    • Also means, the probability of chance exceeds the cut-off point (level of significance/or risks allowed)
    • No significant mood difference exists between the two groups
    • So the treatment (drug) did not work
examples exercise9
Examples & Exercise
  • Scenario:
    • two groups of patients: anti-depression drug group; and placebo group
    • Run t for two
  • t(58)=0.14, p=.891
    • t: the test that was used
    • 58: degree of freedom
    • 0.14: the obtained value < critical value 2.001
      • Not extreme enough for us to conclude the difference is due to treatment
    • P: the exact probability that the outcome (difference) is due to chance
    • Also means, the probability of chance exceeds the cut-off point (level of significance/or risks allowed)
    • No significant mood difference exists between the two groups
    • So the treatment (drug) did not work
shaprio w normality test
Shaprio-W Normality Test
  • Seems to have a different interpretation
  • But only used in Analyse-it
  • The higher the p, the more normal the distribution is.
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