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Analysis of variance allows us to test whether the differences among more than two sample means are significant or not. This technique overcomes the drawback of the method used in statistical inferences, which allows us to test the significance among the means drawn from two populations only. Since managers are required to test the significance of the differences among the means and variances drawn from more than two populations, the importance of this technique cannot be underestimated. Therefore it is natural that this technique plays an important role in the day-to-day decision making. We do observe a certain degree of similarity between this technique and the Chi Square test (employed for testing significance of proportions among more than two populations) which we have seen earlier.
A suitable example for ANOVA would be to compare the stipend given to the management graduates belonging to various premier institutes during their summer internship. If we would set up a hypothesis to test the significance of the differences among the means, it would be like
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A researcher is interested in comparing the effectiveness of three different parts of therapy for anger problems. 8 participants are randomly assigned to 3 treatment conditions: Co
Significance of Correlation The study of correlation is of immense use in practical life. Correlation analysis contributes to the understanding of economic behavior, aids in lo
Using a random sample of 670 individuals for the population of people in the workforce in 1976, we want to estimate the impact of education on wages. Let wage denote hourly wage in
Simple Linear Regression While correlation analysis determines the degree to which the variables are related, regression analysis develops the relationship between the var
introduction of median
Assumptions in ANOVA The various populations from which the samples are drawn should be normal and have the same variance. The requirement of normality can be discarded if t
X 110 120 130 120 140 135 155 160 165 155 Y 12 18 20 15 25 30 35 20 25 10
Cluster Sampling Here the population is divided into clusters or groups and then Random Sampling is done for each cluster. Cluster Sampling differs from Stratified Sampl
Hi There, I have a question regarding R, and I am wondering if anyone can help me. Here is a code that I would like to understand: squareFunc g f(x)^2 } return(g) } sin
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