4. Regression analysis
4-1 Tourism destination image depending on PPL effect
We analyzed that PPL give what kind of effect on to Cognitive, Emotional tourism destination image. In other words, we took linear regression analysis to know the Cognitive, Emotional tourism destination image depending on PPL effect. Through the variable calculation, we got the mean of PPL effect. We set this to
analysis tolerance limit is 1 that is biggest number so we don't need to interpretate it.
VIF is inverse number of tolerance limit. And if value of VIF is big, there is high Collinearity between independent variables.
This is a result of regression analysis.
Y = 4.649+0.175*(factor1)+0.263*(factor2)+0.279*(factor3)-0.008*(factor4)+0.157*(factor5)
regression model was used. First, 10 explanatory variables that are likely to affect selling price of the car were potentially set and the data were collected. In this course, we referred to website (http://www.enuri.com/car) that sells new cars. Next, the standard regression assumptions were checked. Finally, fitness of model was examined by deciding whether the price of the car can be explained