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In View Of The Current Home Ownership Questionnaire Design And Analysis Of Psychological Change

Posted on:2013-02-12Degree:MasterType:Thesis
Country:ChinaCandidate:H Y ZhangFull Text:PDF
GTID:2249330374954799Subject:Applied Mathematics
Abstract/Summary:PDF Full Text Request
Based on a practical problem in our daily life, two questionnaires have been de-signed, to consider the psychological change of house buying by using the samplingsurvey method. Two network questionnaires were investigated in June,2011and De-cember,2011. I have got414efective responses in the previous time and211in thesecond time. By reorganizing the data of the efective responses using the methodof contingency table independence test, the conclusions are finally demonstrated,that there are no correlations between the features of consumers and the attitudetowards the price of the houses, that the features of consumers are not related tothe attitude towards the price of the houses in the next year. There are no correla-tions between features of consumers and attitudes toward national macroeconomicregulations about control of house prices in addition to the gender. Meanwhile, theother conclusions were proved to be true, that there are significant correlations be-tween“Housing loan”,“Living state”,“Personal average annual income” and “Thetime of planning to buy houses”. After the questionnaire-items were combined, us-ing “Whether need house” as the response variable, the logistic regression modelof binary classification response variables was established. Using the software SASin the logistic regression analysis of the binary classification variables, we selectedthe variables of “Living state” and “Marital status” into the model, and the twovariables are statistically significant(P value <0.1). Using “The time of planningto buy houses” as the response variable, we establish the polytomous orderd logisticregression model. After the stepwise regression analysis, we selected the variablesof “Housing loan”,“Personal average annual income” and “Degree” into the model,and these variables are statistically significant(P value <0.1).
Keywords/Search Tags:Sample survey, Contingency table, Independence test, Logistic regres-sion model, SAS
PDF Full Text Request
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