Statistical Analysis Of Commodity Price Data In Changchun

With the deepening of reforming and opening up, real estate has become one ofthe pillars of national economy. It plays an important role in the economicdevelopment. Prices of commodity houses have become a major concern for thepublic. What on earth is the reasonable price of a commodity house? Throughvariance analysis of the data released on major Internet and other factors influencingaverage price of commodity houses, this paper provides theoretical foundation forpricing of commodity houses.Covariance Analysis combines regression analysis and variance analysis, whosegist is that, consider the qualitative influencing factors as covariant and establish aregression equation where dependent variables vary with the arguments; use theregression equation to exclude the impact of uncontrollable qualitative factors duringchanges of dependent variables, Thus it can be more reasonable to comparequalitative factors at different levels, whether there is a significant difference betweenthe overall dependent variable in regression analysis means amendment mean. Thispaper uses SAS to deal with a dataset obtained from the nine interpretativevariable’s(urban area, decoration, building type, commercial area, famous schools,property fees,floor-area ratio, afforestation rate, parks and gardens) influence onlogarithm.A regression model will be established, on which a F-examination will beconducted to identify the interpretative variables which influence the average prices ofcommodity houses remarkably.