Difference between revisions of "Manuals/calci/FRIEDMANTEST"

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==Feature==
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<div style="font-size:25px">'''FRIEDMAN(Array,SignificanceLevel,logicalValue)'''</div><br/>
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*<math>Array</math> is the array of values to find the test statistic.
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*<math>SignificanceLevel</math> is the value between 0 and 1.
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*<math>Logicalvalue</math> is either TRUE or FALSE.
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==Description==
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*This function gives the Test statistic summary of FriedMan Test.
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*Friedman's test is a nonparametric test that compares three or more paired groups.
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*It is the alternative to ANOVA with repeated measures.
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*It is used to test for differences between groups when the dependent variable being measured is ordinal.
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*It can also be used for continuous data that has violated the assumptions necessary to run the one-way ANOVA with repeated measures.
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*This test is simelar to the Kruskal Wallis test.
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*The data of the Fried Man test having the following assumptions:
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*1. One group that is measured on three or more different occasions.
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*2.Group is a random sample from the population.
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*3.The dependent variable should be measured at the ordinal or continuous level.
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*4.Samples do NOT need to be normally distributed.
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*'''Steps for Fried man Test''':
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*1.Define Null and Alternative Hypotheses:Null Hypotheses:There is no difference between the conditions.Alternative Hypotheses:There is a difference between the conditions.
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*2.State Alpha:Alpha=0.05.
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*3.Calculate degrees of freedom:df = k – 1, where k = number of groups.
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*4.State Decision Rule:From the Chi squared table calculate the critical value.
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*Suppose the chisquared(symbol)is greater than the critical value then reject the null hypothesis
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*5.Calculate the Test Statistic:<math>M=\frac{12}{nk(k+1)}\sum_{j=1}^k {R_j}^2-3n(k+1)</math>
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*k = number of columns (often called “treatments”)
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*n = number of rows (often called “blocks”)
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*Rj = sum of the ranks in column j.
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*If there is no significant difference between the sum of the ranks of each of the columns, then
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M will be small, but if at least one column shows significant difference then M will be larger.
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*6.State Results:In this step we have to take a decision of null hypothesis either accept or reject depending on the  critical value table.
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*7.State Conclusion:To be significant, our obtained U has to be equal to or LESS than this
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critical value.
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==Example==

Revision as of 23:24, 21 May 2014

FRIEDMAN(Array,SignificanceLevel,logicalValue)


  • is the array of values to find the test statistic.
  • is the value between 0 and 1.
  • is either TRUE or FALSE.

Description

  • This function gives the Test statistic summary of FriedMan Test.
  • Friedman's test is a nonparametric test that compares three or more paired groups.
  • It is the alternative to ANOVA with repeated measures.
  • It is used to test for differences between groups when the dependent variable being measured is ordinal.
  • It can also be used for continuous data that has violated the assumptions necessary to run the one-way ANOVA with repeated measures.
  • This test is simelar to the Kruskal Wallis test.
  • The data of the Fried Man test having the following assumptions:
  • 1. One group that is measured on three or more different occasions.
  • 2.Group is a random sample from the population.
  • 3.The dependent variable should be measured at the ordinal or continuous level.
  • 4.Samples do NOT need to be normally distributed.
  • Steps for Fried man Test:
  • 1.Define Null and Alternative Hypotheses:Null Hypotheses:There is no difference between the conditions.Alternative Hypotheses:There is a difference between the conditions.
  • 2.State Alpha:Alpha=0.05.
  • 3.Calculate degrees of freedom:df = k – 1, where k = number of groups.
  • 4.State Decision Rule:From the Chi squared table calculate the critical value.
  • Suppose the chisquared(symbol)is greater than the critical value then reject the null hypothesis
  • 5.Calculate the Test Statistic:
  • k = number of columns (often called “treatments”)
  • n = number of rows (often called “blocks”)
  • Rj = sum of the ranks in column j.
  • If there is no significant difference between the sum of the ranks of each of the columns, then

M will be small, but if at least one column shows significant difference then M will be larger.

  • 6.State Results:In this step we have to take a decision of null hypothesis either accept or reject depending on the critical value table.
  • 7.State Conclusion:To be significant, our obtained U has to be equal to or LESS than this

critical value.

Example