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This report is aimed to develop understanding of regression analysis and its implications in data analysis to make decisions. In this report, impact of different independent variables Sydney Price Index, Annual Percentage Change, Land size and Age of house on the house prices in Sydney market has been analyzed. From regression analysis, it is analyzed that there is a positive linear relationship between Sydney price index, land size and annual percentage change with the market prices of Houses in Sydney. but at the same time, there is a negative linear relationship between age of house and market price of houses. In addition, multiple regression analysis shows that Sydney Price Index shows the moderate fit or reliable value. Moreover, it can be identified from hypothesis testing that there is a significant relationship between dependent and independent variables.
IntroductionThe use of statistical analysis is significant to make decisions in the business efficiently. In relation to this, the presented case study is also based on the utilization of linear regression model for determining relationship between variables including dependent and independent variables. Apart from this, the use of regression analysis is also significant to determine the degree of impact of independent variable on the dependent variable (Newbold et al., 2012). It is also effective to predict the values of one variable in future based on the change in another variable. The sample size of the given data set is 15 observations during 2002-03 and 2016-17
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