The data below represent commute times (in minutes) and scores on a well-being survey. Complete parts (a) through (d) below. Commute Time (minutes), x Well-Being Index Score, y 20 25 35 69.3 68.1 67.6 67.2 66.1 66.2 64.1 60 72 105 D Interpret the y-intercept. Select the correct choice below and, if necessary, fill in the answer box to complete your choice. O A. For a commute time of zero minutes, the index score is predicted to be (Round to three decimal places as needed.) O B. For every unit increase in commute time, the index score falls by (Round to three decimal places as needed.) on average. O C. For an index score of zero, the commute time is predicted to be (Round to three decimal places as needed.) minutes O D. For every unit increase in index score, the commute time falls by on average. (Round to three decimal places as needed.) O E. It is not appropriate to interpret the y-intercept because a commute time of zero minutes does not make sense and the value of zero minutes is much smaller than those observed in the data set (c) Predict the well-being index of a person whose commute time is 30 minutes The predicted index score is Click to select your answer(s)
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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