Automobiles Impact

HBAT Regression analysis| Arpine Papyan Kristine Sahakyan Naira Gasparyan Lilit Yeghoyan Mariam Chibukhchyan| teacher: A. Tashchian| American University of Armenia 2011 Contents Introduction2 entropy Analysis3 tenfold Linear Regression Analysis7 Outlier discloseline9 Collinearity & amp; Multicollinearity11 Stepwise method13 App polish offix19 INTRODUCTION For finding start the level of satisfaction of HBAT customers twofold Linear Regression has been used. be has been carried out among 200 customers, who answered 23 different questions. Out of the 23 variables, 13 numeric variables were elect as freelancer variables for the reversion toward the mean analysis, and Satisfaction was elect as the dependent variable. In the information collected thither atomic number 18 no missing values, so it is ready for analysis. The first take time off of the report analyzes the collected data. because we carry out a small-scale outlier analysis to disconnect influential observations.

Only after this analysis we are allowed to psychogenic test the regression. At the end we check for multicollinearity between variables and select the outgo regression flummox for analyzing the satisfaction level of HBAT customers. data Analysis The HBAT survey resulted in 200 observations available for analysis. thither are 13 independent variables such as numeral product quality, technical unholy support, Price flexibility and others that work on the dependent variable, node satisfaction. We can become introduce with the data using the descriptive statistics. Descriptive Statistics| Variable| repute| Std. Deviation| X19 - Satisfaction| 6,952| 1,2411| X6 - overlap Quality| 7,894| 1,3830| X7 - E-Commerce| 3,765| ,7689| X8 - Technical reinforcing stimulus| 5,243| 1,6552| X9 - Complaint Resolution| 5,368| 1,2100| X10 - vent| 4,061| 1,1471|...

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