Difference between revisions of "Manuals/calci/FRIEDMANTEST"
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==Example== | ==Example== | ||
+ | {| class="wikitable" | ||
+ | |+Spreadsheet | ||
+ | |- | ||
+ | ! !! A !! B !! C | ||
+ | |- | ||
+ | ! 1 | ||
+ | | 31 || 37 || 38 | ||
+ | |- | ||
+ | ! 2 | ||
+ | | 25 || 20 || 22 | ||
+ | |- | ||
+ | ! 3 | ||
+ | | 42 || 49 || 45 | ||
+ | |- | ||
+ | ! 4 | ||
+ | | 10 || 15 || 17 | ||
+ | |- | ||
+ | !5 | ||
+ | | 54 || 56 || 60 | ||
+ | |} | ||
+ | *=FRIEDMANTEST(A1:C5,0.05,TRUE) |
Revision as of 22:32, 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
A | B | C | |
---|---|---|---|
1 | 31 | 37 | 38 |
2 | 25 | 20 | 22 |
3 | 42 | 49 | 45 |
4 | 10 | 15 | 17 |
5 | 54 | 56 | 60 |
- =FRIEDMANTEST(A1:C5,0.05,TRUE)