Multivariate Data Analysis - 3054 Words

Introduction This document presents the regression analysis of customer survey data of Hatco, a large industrial supplier. The data has been collected for 100 customers of Hatco on 14 parameters. The 14 variables are as follows: * Perceptions of Hatco: This data was collected on a graphic measurement rating scale consisting of a 10cm line ranging from poor to excellent. Indicator | Variable | Description | X1 | Delivery speed | amount of time it takes to deliver the product once an order as been confirmed | X2 | Price level | perceived level of price charged by product suppliers | X3 | Price flexibility | perceived willingness of HATCO representatives to negotiate price on all types of purchases | X4 | Manufacturers†¦show more content†¦For now these variables will be considered for step wise regression. Normality For multiple regression analysis it is important that all the dependant variables must be normally distributred. We can check this from the normal distribution curves of each of the dependant variables. From the above distribution curves we can see that all the variables have standard deviations approximately equal to 1. Usage level has a higher standard deviation. If this variable becomes a part of the final equation then wwe can apply corrective measures to ensure its normality. Step 2: Perform Multiple Regression The method used to arrive at the regression equation will be step wise. In order to obtain the first variable which will be used to form the regression equation we need to check which of the dependant variables has the highest correlation with the independent variable at a significant less than 0.05. The correlations of the dependant variables against the independent variable are as shown in the figure below. The table shows the correlation of all the independent variables against the dependant variable satisfaction level. The values in the cells show the correlation with satisfaction level along with the significance level. Looking down the first column it can be seen that usage level has the highest correlation of 0.711 at the highest significance level. This will be the first variableShow MoreRelatedData Analysis : Correlation, Univariate And Multivariate Regression Models Essay1200 Words   |  5 Pages2.4 Data Analysis: Correlation, Univaria te and Multivariate regression models Multivariate regression is a statistical tool used to predict the functional relationship between some dependent variable and a set of independent variables [13, 14]. It comes as a generalization to simple univariate regression models therefore it will be introduced accordingly. However selecting which variables best influence the survival rate in LC is quite difficult. 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