Automobile Industry Structure In 1998

HBAT Regression outline| Arpine Papyan Kristine Sahakyan Naira Gasparyan Lilit Yeghoyan Mariam Chibukhchyan| Instructor: A. Tashchian| Ameri canful University of Armenia 2011 Contents Introduction2 selective information Analysis3 quadruplex Linear Regression Analysis7 Outlier psychoanalysis9 Collinearity & Multicollinearity11 Stepwise method13 App blockix19 world For finding fall out the level of satisfaction of HBAT customers Multiple Linear Regression has been used. espouse has been carried out among 200 customers, who answered 23 different questions. Out of the 23 variables, 13 numeric variables were chosen as main(a) variables for the degeneration analysis, and Satisfaction was chosen as the dependent variable. I n the data collected there atomic number 18 no missing values, so it is ready for analysis. The first bulge of the report analyzes the collected data. whence we carry out a small-scale outlier analysis to do away with influential observations.

exactly after this analysis we are allowed to leave the regression. At the end we check for multicollinearity between variables and choose the trump regression clay sculpture for analyzing the satisfaction level of HBAT customers. Data Analysis The HBAT survey resulted in 200 observations available for analysis. There are 13 independent variables such as mathematical product quality, technological support, legal injury flexibility a nd others that influence on the dependent va! riable, client satisfaction. We can become acquainted with the data using the descriptive statistics. descriptive Statistics| Variable| Mean| Std. Deviation| X19 - Satisfaction| 6,952| 1,2411| X6 - Product musical note| 7,894| 1,3830| X7 - E-Commerce| 3,765| ,7689| X8 - Technical Support| 5,243| 1,6552| X9 - Complaint Resolution| 5,368| 1,2100| X10 - advertizing| 4,061| 1,1471|...If you necessity to get a full essay, order it on our website: OrderEssay.net

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