There is a negative correlation between the number of flu cases reported each week throughout the year (call this variable X) and the amount of ice cream (call this variable Y) sold that week. The most plausible explanation for this association is: Group of answer choices c. changes in X and Y are due to a common response to other variables: winter months see low ice cream sales and simultaneously high numbers of flu cases. Vice versa for summer months. a. X causes Y: Sick people don’t eat ice cream. Thus, more flu cases results in less ice cream consumption. b. Y causes X: Eating a lot of ice cream causes people to get sick. Thus, the more ice cream consumed the more flu cases. d. the association between X and Y is purely coincidental: It is a complete fluke.
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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