Suppose researchers are interested in exploring the factors which affect depression for Australian adults. The researchers recruited a sample of 99 Australian adults and collected data on several variables which may influence depression. Note that here depression is represented by a score, with higher values representing higher levels of depression. The variables for this study are listed below: Age Gender (0 = female, 1 = male) Stress level Anxiety level Depression Why would conducting a multiple linear regression analysis be appropriate here? Group of answer choices A) Multiple linear regression can be appropriate here because we have one metric dependent variable and several metric or dichotomous independent variables B) Multiple linear regression can be appropriate here because we have one metric dependent variable and several categorical independent variables C) Multiple linear regression can be appropriate here because we have one categorical dependent variable and several categorical independent variables D) Multiple linear regression can be appropriate here because we have one categorical dependent variable and several metric or dichotomous independent variables
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.
Suppose researchers are interested in exploring the factors which affect depression for Australian adults. The researchers recruited a sample of 99 Australian adults and collected data on several variables which may influence depression. Note that here depression is represented by a score, with higher values representing higher levels of depression.
The variables for this study are listed below:
- Age
- Gender (0 = female, 1 = male)
- Stress level
- Anxiety level
- Depression
Why would conducting a multiple linear
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