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A regression model is used to express a variable Y as a function of another variable X. This implies that
- a)There is a causal relationship between Y and X
- b)A value of X may be used to estimate a value of Y
- c)Values of X exactly determine values of Y
- d)There is no causal relationship between Y and X
Correct answer is option 'B'. Can you explain this answer?
Most Upvoted Answer
A regression model is used to express a variable Y as a function of an...
Explanation:
A regression model is used to describe the relationship between two or more variables. Typically, one variable is considered the dependent variable (Y) and the other variable(s) are considered independent variable(s) (X). The purpose of a regression model is to estimate the relationship between the dependent and independent variables.
Option A: There is a causal relationship between Y and X.
This statement is not necessarily true. A regression model can only show a correlation between variables, but it cannot prove causation. Correlation does not imply causation, so just because Y and X are correlated does not necessarily mean that X causes Y.
Option B: A value of X may be used to estimate a value of Y.
This statement is true. In a regression model, the independent variable(s) are used to predict the value of the dependent variable. Therefore, given a value of X, the regression model can be used to estimate the corresponding value of Y.
Option C: Values of X exactly determine values of Y.
This statement is not necessarily true. A regression model can only provide an estimate of the dependent variable based on the independent variable(s). There may be other factors that also influence the value of the dependent variable.
Option D: There is no causal relationship between Y and X.
This statement is not necessarily true. A regression model can show a correlation between variables, but it cannot prove causation. There may be a causal relationship between Y and X, but the regression model cannot prove it.
Conclusion:
In conclusion, option B is the correct answer because a regression model can be used to estimate the value of the dependent variable (Y) based on the independent variable(s) (X). However, a regression model cannot prove causation between the variables, and there may be other factors that also influence the value of the dependent variable.
A regression model is used to describe the relationship between two or more variables. Typically, one variable is considered the dependent variable (Y) and the other variable(s) are considered independent variable(s) (X). The purpose of a regression model is to estimate the relationship between the dependent and independent variables.
Option A: There is a causal relationship between Y and X.
This statement is not necessarily true. A regression model can only show a correlation between variables, but it cannot prove causation. Correlation does not imply causation, so just because Y and X are correlated does not necessarily mean that X causes Y.
Option B: A value of X may be used to estimate a value of Y.
This statement is true. In a regression model, the independent variable(s) are used to predict the value of the dependent variable. Therefore, given a value of X, the regression model can be used to estimate the corresponding value of Y.
Option C: Values of X exactly determine values of Y.
This statement is not necessarily true. A regression model can only provide an estimate of the dependent variable based on the independent variable(s). There may be other factors that also influence the value of the dependent variable.
Option D: There is no causal relationship between Y and X.
This statement is not necessarily true. A regression model can show a correlation between variables, but it cannot prove causation. There may be a causal relationship between Y and X, but the regression model cannot prove it.
Conclusion:
In conclusion, option B is the correct answer because a regression model can be used to estimate the value of the dependent variable (Y) based on the independent variable(s) (X). However, a regression model cannot prove causation between the variables, and there may be other factors that also influence the value of the dependent variable.
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A regression model is used to express a variable Y as a function of another variable X. This implies that a)There is a causal relationship between Y and X b)A value of X may be used to estimate a value of Y c)Values of X exactly determine values of Y d)There is no causal relationship between Y and XCorrect answer is option 'B'. Can you explain this answer?
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