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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

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Hypothesis testing and results interpretation l.jpg

Hypothesis Testing and Results Interpretation

By Minjuan Wang

ED 690

Educational Technology


Types of hypothesis l.jpg

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.


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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 l.jpg

Hypothesis testing

  • Core of Inferential Statistics

    • contributes to the science of education primarily by expanding, refining, or revising its knowledge base.


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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.


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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


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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 l.jpg

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 l.jpg

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


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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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