b. Randomly selected individuals, some sick and some healthy, are chosen to receive a treatment. The measured variables are not necessarily 100% correlated and they appear to improve after the treatment is administered. This improvement is interpreted as being due to the treatment.
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.
Which is a regression fallacy?
a. Randomly selected individuals, some sick and some healthy, are chosen to receive a treatment. The measured variables are 100%
b. Randomly selected individuals, some sick and some healthy, are chosen to receive a treatment. The measured variables are not necessarily 100% correlated and they appear to improve after the treatment is administered. This improvement is interpreted as being due to the treatment.
c. Only sick individuals (no healthy individuals are chosen) are given a treatment. The measured variables are not 100% correlated and the measured variables appear to improve after a treatment is administered. This improvement is interpreted as being due to the treatment.
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