operational analysis of a select spinning mill - International ...

The validity of the model has been tested by ANOVA. The output of the ANOVA is
presented as :
Table No.3 - Analysis of Variance
Source Sum of Squares Df Mean Square F-Ratio P-Value
Model 56.9084 2 28.4542 646.83 0.0000
Residual 0.307931 7 0.0439901
Total (Corr.) 57.2163 9
Since the P-value in the ANOVA table is less than 0.05, there is a statistically significant
relationship between the variables at the 95.0% or higher confidence level. Hence fitted model
is the most suitable model to describe the relationships of the variables.
Table.4. Related Statistics
R2
Standard
Mean Absolute Error Dubin-Watson Statistics
Error of Estimate
99.4618 percent 0.209738 0.136684 1.30309(P=0.0942)
The R-Squared statistic indicates that the model as fitted explains 99.4618%of the
variability in production. The standard error of the estimate shows the standard deviation of the
residuals to be 0.209738.
The mean absolute error (MAE) of 0.136684is the average value of the residuals. The
Durbin-Watson (DW) statistic tests the residuals to determine if the re is any significant
correlation based on the order in which they occur. Since the P-value is greater than 0.05, there is
no indication of serial autocorrelation in the residuals at the 95.0% confidence level.
HYPOTHESIS.2:
THERE IS NO SIGNIFICANT REATIONSHIP BETWEEN YARN PRODUCTION, RAW
MATERIAL CONSUMPTION AND YIELD RATIO OF SSM LTD UNIT-2
To study the Significant Relationship between the Yarn Productions, Raw Material
Consumption and yield ratio multiple regression analysis is employed. Here we take the yarn
production as dependent variable and other factors as independent variables. The following
table shows the results of fitting a multiple linear regression model:
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