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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 4 assumptions of regression: 1. Variables are normally distributed 2. Linear relationship between the independent and dependent variables 3. Homosced
Show that when h = h* for the histogram, the contribution to AMISE of the IV and ISB terms is asymptotically in the ratio 2:1. Compare the sensitivity of the AMISE(ch) in Equa
There exists an unclassified data set with hidden data structures in it. The task in this assignment is to perform comprehensive Cluster Analysis in order to reveal the structures
Factor analysis (FA) explains variability among observed random variables in terms of fewer unobserved random variables called factors. The observed variables are expressed in
Other Measures of Dispersion In this section, we look at relatively less used measures of dispersion like fractiles, deciles, percentiles, quartiles, interquartile range and f
1) Suppose you want to test a hypothesis that two treatments, A and B, are equivalent against the alternative that the response for A tend to be larger than those of B. You plan to
Cause and Effect Even a highly significant correlation does not necessarily mean that a cause and effect relationship exists between the two variables. Thus, correlation does
Differentiate between data and database
programming
Example of discrete random variable: 1. What is a discrete random variable? Give three examples from the field of business. 2. Of 1000 items produced in a day at XYZ Manufa
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