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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
The cost of living index number on a some data was 200. From the base period, the percentage enhances in prices were-Rent Rs 60, clothing Rs 250, Fuel and Light Rs 150 and Miscella
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Ask queFrom these studies, which of the following may be considered a variable that can have a probability distribution? [I] Percentage of Sub-Saharan Africans that smoke [II] Perc
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Examples of grouped, simple and frequency distribution data
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regression line drawn as Y=C+1075x, when x was 2, and y was 239, given that y intercept was 11. calculate the residual
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