Linear Regression

Running Head : PERSONAL INCOME AND OUTLAYSThe Link Between psychealised Income and OutlaysAbstractIt is observed that as personal income increases , the expenses a person incurs excessively increases . This project utilized simple linear fixing analysis to determine if there is a link between the both changeables . The hypothesis is that the outlays of a person is positively linearly reliant on the income make by a person . turnaround results show that outlays are positively linearly parasitical on personal income . A 1 unit increase in personal income leads to a 0 .8269 unit increase in outlays 88 .62 of the variation of the outlays is explained by personal income This implies that the manakin employ in this project is very strongThe Link Between personalised Income and OutlaysIntroductionPersonal income is define as a person s business enterprises , investment funds interest and dividends , and other sources over a period of angiotensin converting enzyme year . On the other hand , outlays are defined as the expenditures of individuals from consumption and production activities . Usually , a person s outlays would come from the money that he earned from work or business . Therefore , these inconstants were selected in this project to determine if outlays were dependent on the amount of income earned by a personThe selective information used were the author s personal income and outlays from 1996 to 2007 . Simple method leave alone be implemented . A linear reverting is a statistical procedure that is used to determine whether one variable is statistically dependent to another variable (Gujarati 2003 . It fits a regression model in the form of y a bx , where Y is the dependent variable , x is the independent variable , a is the y-intercept (value of Y when x is 0 , and b is the coefficient of variable x . The aim is to estimate the values of a and b in oreder to explain the effects of a change in x to Y .

of In this study , the dependent variable is the outlay while the independent variable is the personal income . The hypothesis is that the outlays of a person is positively linearly dependent on the income earned by a personRegression ResultsThe t-statistic of the independent variable income is 8 .82 . As a rule of thumb , if the t-statistic of a variable is more(prenominal) than 2 , the variable is significant . This means that outlays are importantly dependent on a person s incomeThe R-squared value of the regression model is 0 .8862 or 86 . This means that 88 .62 of the variation of the dependent variable (outlays is explained by personal income . excessively , the value of the R-squared is significantly high . This implies that the goodness of fit of the model used in this study is very strongP-values are as well as used to determine the significance of the variables This is done by comparability the p-value to the selected level of significance . If the p-value is lower than the level of significance the variable is significant . The p-value of the outlay variable...If you want to get a skilful essay, order it on our website: Orderessay

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