Question

If time is used as an independent variable in a simple linear regression, which of the following assumption could be violated?
Successive observations of the dependent variable are uncorrelated
Residual variation is same for all fitted values of dependent variable
There exists a linear relationship between independent and dependent variables
Residuals are normally distributed

Answer 1

Answer:

The dependent variable's successive observations are unrelated.

Explanation:

• We might wish to look at the relationship between BMI and systolic blood pressure, or between weekly activity hours and body fat percentage.
• A similar approach for determining the link between an outcome variable and one or more risk factors or confounding variables is regression analysis (confounding is discussed later).
• The response or dependent variable is also known as the outcome variable, whereas the risk factors and confounders are known as the predictors, or explanatory or independent variables.
• The dependent variable in regression analysis is indicated by "Y," while the independent variables are denoted by "X."
• If the term "predictor" is regarded as the ability to predict even beyond the bounds of the data, it might be deceptive. In a circumstance where conclusions should be confined to finding relationships, the term "explanatory variable" may create the appearance of a causative influence. Because they do not clearly indicate cause and effect, the labels "independent" and "dependent" variables are less susceptible to these interpretations.