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분야
hwpⅠ. Introduction
1. Background of study
2. Purpose of study
Ⅱ. Research Design
1. Setting up hypothesis and research model
2. Subject and method of research
3. Construction of survey
4. Method of data analysis
Ⅲ. Result of study
1. Hypothesis
2. Characteristics of samples
1) Analysis of demographic factors
2) Analysis of usage pattern of cafe
3. Comment about reliability and validity
4. Analysis of our project
1) Factor analysis
2) Reliability anlaysis
3) Regression analysis
Ⅳ. Conclusion
1. Summary
2. Suggestion
1) SWOT & brief marketing strategy
Tolerance limit and VIF in Collinearity statistics are indexes that judge multicollinearity of factor variables. Collinearity means relationship between two independent variables. For example, if coefficients correlation of two factor variables is 1, these variables have perfect Collinearity. And if coefficients correlation is 0, they have Collinearity not at all. Especially, relationship among 3 or more variables is called multicollinearity.
Tolerance limit means a part that a factor variable is not explained by other variables. In other words, if tolerance limit is small, multicollearity is high. In this 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)
Dependent Variable
Independent Variables
Standardized Coefficients
t(p)
F(p-value)
VIF
Satisfaction
Convenience Accessibility
0.131
1.772(.078)
4.412
(.001)
1.000
Visibility
0.197
2.657(.009)
1.000
Comfort
0.209
2.824(.005)
1.000
Crowding
-0.006
-0.085(.932)
1.000
Geographic proximity of college
0.118
1.591(.114)
1.000
R(.337ª),R Squre(.113), Adjusted R Squre(.086)
*:p
