Difference between revisions of "Manuals/calci/LEVENESTEST"
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*The Levene test statistic is: | *The Levene test statistic is: | ||
<math>W=\frac{(N-k)\sum_{i=1}^k N_i(Z_i-Z)^2}{(k-1)\sum_{i=1}^k \sum_{i=1}^k \sum_{j=1}^{N_i} (Z_{ij}-Z_i)^2}</math>. | <math>W=\frac{(N-k)\sum_{i=1}^k N_i(Z_i-Z)^2}{(k-1)\sum_{i=1}^k \sum_{i=1}^k \sum_{j=1}^{N_i} (Z_{ij}-Z_i)^2}</math>. | ||
− | *where <math>W< is the result of the test | + | **where <math>W</math> is the result of the test. |
− | + | **<math>k</math> is the number of different groups to which the sampled cases belong. | |
+ | **<math>N</math> is the total number of cases in all groups. | ||
+ | **<math>N_i</math> is the number of cases in the <math>i^th</math> group. | ||
+ | **<math>Y_{ij} is the value of the measured variable for the <math>j_th</math> case from the <math>i^th</math> group. | ||
+ | *Zij is satisfying the one of the following conditions: | ||
+ | *1.<math>z_{ij}=|y_{ij}-\bar{y_i}|</math>,Where <math>\bar{y_i}</math> is the Mean of the <math>i^th</math> subgroup. | ||
+ | *2.<math>z_{ij}=|y_{ij}-\bar{y_i}|</math>,Where <math>\bar{y_i}</math> is the Median of the <math>i^th</math> subgroup | ||
+ | *3.<math>z_{ij}=|y_{ij}-\bar{y_i}|</math>,Where <math>\bar{y_i}</math> is the 10%Trimmed Mean of the <math>i^th</math> subgroup. | ||
+ | *Levene's Testing Procedure: | ||
+ | *1. checking the assumptions. | ||
+ | *2.State the Null(H0) and alternative(H1) hypothesis. | ||
+ | *3.Decide on the Significance level (α). | ||
+ | *4.Finding the Critical value and Rejection Region.Here <math>df_1=t-1</math>,<math>df_2=N-t</math>. | ||
+ | *5.Compute the Levenes statistic using the formula. | ||
+ | *6.Then decision of the value of the test statistic,W is falls in the rejection region or if p-value ≤ α, then reject <math>H_0</math>.Otherwise, fail to reject <math>H_0</math>. For the computation p-value we have to use the value of <math>df_1</math> and <math>df_2</math>. | ||
+ | *7. Finally we have to conclude that the rejection of <math>H_0</math> or fail to rejection <math>H_0</math> according to the test statistic at the significance level. | ||
+ | |||
+ | ==Example== |
Revision as of 04:24, 30 April 2014
LEVENESTEST(xRange,ConfidenceLevel,LogicalValue)
- is the set of values for the test.
- is the value from 0 to 1.
- is either TRUE or FALSE.
Description
- This function used to test the Homogeneity of variances.
- Levene's test is used to test the Samples have equal variances.
- Equal variances across samples is called homogeneity of variance or homoscedasticity.
- To do the Levenes test we need the following assumptions:
1.The Samples from the populations are independently of one another. 2. The population under consideration are Normally Distributed.
- For three or more variables the following statistical tests for homogeneity of variances are commonly used:
1.Levene's Test. 2.Bartlett Test.
- Levene's test is an alternative to the Bartlett test.
- If the data surely is of normally distributed or nearly to normally distributed then we can use the Bartlett test.
- The Levene's test is defined as
. =Not all of the variances are equal.
- Normally there are three versions of the Levenes test.
- There are 1.Use of Mean.2.Use of Median.3.Use of 10% of Trimmed Mean.
- The Levene test statistic is:
.
- where is the result of the test.
- is the number of different groups to which the sampled cases belong.
- is the total number of cases in all groups.
- is the number of cases in the group.
- case from the group.
- Zij is satisfying the one of the following conditions:
- 1.,Where is the Mean of the subgroup.
- 2.,Where is the Median of the subgroup
- 3.,Where is the 10%Trimmed Mean of the subgroup.
- Levene's Testing Procedure:
- 1. checking the assumptions.
- 2.State the Null(H0) and alternative(H1) hypothesis.
- 3.Decide on the Significance level (α).
- 4.Finding the Critical value and Rejection Region.Here ,.
- 5.Compute the Levenes statistic using the formula.
- 6.Then decision of the value of the test statistic,W is falls in the rejection region or if p-value ≤ α, then reject .Otherwise, fail to reject . For the computation p-value we have to use the value of and .
- 7. Finally we have to conclude that the rejection of or fail to rejection according to the test statistic at the significance level.