Feb 15, 2011
Requirements for Data Analysis
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Nonparametric test is used when the assumptions of parametric tests are not met. The most common assumption in the parametric test is a random sample from a normally distributed population, the data is homogeneous, and linear. If these assumptions are met, or at least a little deviation to the assumption, then the parametric test is still reliable. But if the assumptions are not met then an alternative nonparametric test. There are three assumptions of parametric statistical tests as described above, ie normality, homogeneity, and linearity data.
A. Normality Test Data
Testing normality conducted to determine whether or not a normal data distribution. It is important to know related to the election ketetapatan statistical test that will be used. Misalmya parametric test, data must berdistibusi mengsyaratkan normal. If the data distribution is not normal it is advisable to use a nonparametric test
Tests of normality has to be done if there is no theory which states that the variables studied were normal. In other words, if there is a theory which states that a normal variable under investigation, it is no longer needed test data normality.
Step work with normality test test test Liliefors
Arrange the data from small to large. Any data written once, although there is the same data.
Check the data, how many times have the appearance of numbers (the frequency must be written.)
From the frequency cumulative frequency stacking.
Based on cumulative frequency, calculate the proportion of empirical (observation).
Calculate the value of z to know Theoretical Proportion in table z.
Calculating Theoretical Proportion.
Compare with Theoretical Proportion Proportion empirical, then look for the biggest difference between observation points.
Make a conclusion, with the test criteria, reject H0 if D> D (n,?), With criteria:
H0: X follow a normal distribution.
H1: X does not follow a normal distribution.
B. Data Homogeneity
Parametric test requirements the second is the homogeneity of the data. The test is a test of homogeneity of variance-variance at least two or more distributions. Test of homogeneity that will be discussed in this paper is to test homogeneity of variance and test Burlett.
Test of homogeneity of variance were used to compare two predictor variables. Test criteria used were the two distributions are said to have a homogenous distribution when calculating the value of F smaller than the value of F with a particular table and dk1 = (n1-1) and dk2 = (n2 - 1). In other cases the distribution is not homogeneous / different.
Tests for homogeneity of data with Barlett test was to see whether the variance of k-variance group of predictor variables are the number of data per group may vary and are taken randomly from each population data are normally distributed, different or not (Ruseffendi, 1998: 297).
Test criteria used is when the count> table value, then H0 stating homogeneous variance is rejected, in other cases accepted. Formulas refer to the book source (Sambas Ali Muhidin. 2007. Correlation Analysis, Regression, and Path in the study. Bandung: Pustaka Setia).
The steps that can be done in testing the homogeneity with the Barlett test were:
Define groups of data, and calculate the variance for each group
Create a table helpers to facilitate the process of calculation
Calculate the combined variance.
Calculating the log of the variance combined.
Calculating the value of Barlett.
Calculating value
Determining the value and the critical point.
Make a conclusion.
C. Linearity Data
Checking linearity of regression is done through testing the null hypothesis, that the linear regression against a rival hypothesis that the regression is not linear. Step Test linearity of regression: See book seumber ((Sambas Ali Muhidin. 2007. Correlation Analysis, Regression, and Path in the study. Bandung: Pustaka Setia).
A. Normality Test Data
Testing normality conducted to determine whether or not a normal data distribution. It is important to know related to the election ketetapatan statistical test that will be used. Misalmya parametric test, data must berdistibusi mengsyaratkan normal. If the data distribution is not normal it is advisable to use a nonparametric test
Tests of normality has to be done if there is no theory which states that the variables studied were normal. In other words, if there is a theory which states that a normal variable under investigation, it is no longer needed test data normality.
Step work with normality test test test Liliefors
Arrange the data from small to large. Any data written once, although there is the same data.
Check the data, how many times have the appearance of numbers (the frequency must be written.)
From the frequency cumulative frequency stacking.
Based on cumulative frequency, calculate the proportion of empirical (observation).
Calculate the value of z to know Theoretical Proportion in table z.
Calculating Theoretical Proportion.
Compare with Theoretical Proportion Proportion empirical, then look for the biggest difference between observation points.
Make a conclusion, with the test criteria, reject H0 if D> D (n,?), With criteria:
H0: X follow a normal distribution.
H1: X does not follow a normal distribution.
B. Data Homogeneity
Parametric test requirements the second is the homogeneity of the data. The test is a test of homogeneity of variance-variance at least two or more distributions. Test of homogeneity that will be discussed in this paper is to test homogeneity of variance and test Burlett.
Test of homogeneity of variance were used to compare two predictor variables. Test criteria used were the two distributions are said to have a homogenous distribution when calculating the value of F smaller than the value of F with a particular table and dk1 = (n1-1) and dk2 = (n2 - 1). In other cases the distribution is not homogeneous / different.
Tests for homogeneity of data with Barlett test was to see whether the variance of k-variance group of predictor variables are the number of data per group may vary and are taken randomly from each population data are normally distributed, different or not (Ruseffendi, 1998: 297).
Test criteria used is when the count> table value, then H0 stating homogeneous variance is rejected, in other cases accepted. Formulas refer to the book source (Sambas Ali Muhidin. 2007. Correlation Analysis, Regression, and Path in the study. Bandung: Pustaka Setia).
The steps that can be done in testing the homogeneity with the Barlett test were:
Define groups of data, and calculate the variance for each group
Create a table helpers to facilitate the process of calculation
Calculate the combined variance.
Calculating the log of the variance combined.
Calculating the value of Barlett.
Calculating value
Determining the value and the critical point.
Make a conclusion.
C. Linearity Data
Checking linearity of regression is done through testing the null hypothesis, that the linear regression against a rival hypothesis that the regression is not linear. Step Test linearity of regression: See book seumber ((Sambas Ali Muhidin. 2007. Correlation Analysis, Regression, and Path in the study. Bandung: Pustaka Setia).
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