True or False: If the correlation coefficient from two variables X and Y , the number of shark attacks and number of iced lemonade sales, respectively, is r= 0.98, we can conclude that an increase in iced lemonade sales causes an increase in shark attacks.
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.
True or False: If the
From the known information, a change in one variable affects the change in another variable. Which is called as correlation.
From the given information, let X be the number of shark attacks.
Let Y be the number of iced lemonade sales.
The correlation coefficient between X and Y is,
r = 0.98.
From the known information, if X is increases then Y is also increases or if X is decreases then Y is also decreases. Then such X and Y can be called as positively correlated. Here, the correlation coefficient r will be lies between 0 and 1.
If X is increases then Y is decreases or X is decreases then Y is increases. Then such X and Y can be called as negatively correlated. Here, the correlation coefficient r will be lies between -1 and 0.
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