Actual commuting time in minutes (T) depends on both the weather, and the length of commute. Suppose on a given day T= (1 – Y)(15 + 15X) + Y(45 +35X). The following table shows commuting times as a function of the random outcomes described in Part II: No rain (X= 0) Rain (X= 1) Соmmuting times (T) Short commute (Y= 0) Long commute (Y= 1) 15 min 30 min 45 min 80 min
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.
hi, this is econometry & statistic question. It asks
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Verify the value reported for T in the cell for (X = 0, Y = 1)
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Calculate E(T) and interpret the number you found.
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