Difference between revisions of "Manuals/calci/FRIEDMANTEST"
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− | == | + | <div style="font-size:25px">'''FRIEDMAN(Array,SignificanceLevel,logicalValue)'''</div><br/> |
+ | *<math>Array</math> is the array of values to find the test statistic. | ||
+ | *<math>SignificanceLevel</math> is the value between 0 and 1. | ||
+ | *<math>Logicalvalue</math> 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:<math>M=\frac{12}{nk(k+1)}\sum_{j=1}^k {R_j}^2-3n(k+1)</math> | ||
+ | *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== |
Revision as of 22:24, 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.