An economist wanted to investigate the factors that determined the price of petrol RON97. He gathered 17 months of data on the four variables below: Y = Price of petrol RON97 (RM/litre) X1 = Price of world oil (USD/barrel) X2 = Exchange rate (RM/USD) X3 = Quantity demand for petrol RON97 (million litre) The Excel results are shown as follows: ANOVA df Significance F 0.000 MS 0.467 Regression Residual 0.156 32.763 13 0.062 0.005 Total 16 0.529 Coefficients Standard Error t Stat p-value 0.094 0.000 0.003 Intercept -1.132 0.627 -1.805 X1 0.021 0.003 7.000 X2 -0.334 0.092 -3.630 X3 0.010 0.007 1.429 0.165 (a) Determine the regression equation. (b) Determine the coefficient of determination, and interpret. (c) Which independent variables linearly related to the price of petrol RON 95 in this model? Explain.
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
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