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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
Consider the linear transformation (a) Find the image of (3 , -2 , 2) under T. (b) Does the vector (5, 3) belong to the range of T? (c) Determine the matrix of the transf
We are interested in assessing the effects of temperature (low, medium, and high) and technical configuration on the amount of waste output for a manufacturing plant. Suppose that
Linear Regression Generally, in two mutually related statistical series, the regression analysis based on graphic method. Under graphic method the values of X and Y variable
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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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Regression Coefficient While analysing regression in two related series, we calculate their regression coefficients also. There are two regression coefficients like two regress
Based on the following graphs (next page) you should write a discussion report (2 pages) on: 1. Determination of whether the open-loop system response is consistent with a 1st o
Scatter Diagram The first step in correlation analysis is to visualize the relationship. For each unit of observation in correlation analysis there is a pair of numerical value
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