Thinking about correlation. Exercise 4.26 presents data on wine intake and the relative risk of breast cancer in women. (a) If wine intake is measured in ounces per day rather than grams per day, how would the correlation change? (There are 0.035 ounces in a gram.) (b) How would r change if all the relative risks were 0.25 less than the values given in the table? Does the correlation tell us that among women who drink, those who drink more wine tend to have a greater relative risk of cancer than women who don't drink at all? (c) If drinking an additional gram of wine each day raised the relative risk of breast cancer by exactly 0.01, what would be the correlation between wine intake and relative risk of breast cancer? (Hint: Draw a scatterplot for several values of wine intake.)
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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