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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
find the average rate of increase in population which in the first decade has increased 20%.in the second 25% and in the third 44%
Identify the (time, censor) pair for each of the following analyses:
Arithmetic Mean The process of computing Arithmetic Mean in the case of individual observations is to take the sum of the values of the variable and then divide by the number
Test for Equality of Proportions For example, we may want to test whether the percentage of smokers (p 1 ) among the males equals the percentage of female smokers (p 2 ). W
Properties of correlation
You are going to purchase a part from a specialty vendor. Your company needs a C p of at least 1.67 on a critical dimension of the part. The dimensional specification for this p
Calculation for Continuous Series or Grouped Data = where, m = mid-point of class =
what is non linear modl
1. If you are calculating a correlation coefficient testing the relationship between height and weight, state the null and alternative hypotheses. 2. What kind of relationship d
Agency revenues. An economic consultant was retained by a large employment agency in a metropolitan area to develop a regression model for predicting monthly agency revenues ( y ).
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