A researcher wants to know if more average income in a country is associated with more trust in government. They measure both variables and find that r = .52, with p = .01. But then they wonder if that correlation is actually a by-product of the fact that greater corruption in a country predicts both less average income and less trust. They compute a partial correlation between income and trust, partialling out corruption. They find the partial r = .11, with p = .34. Using a two-tailed α = .05, what is their substantive conclusion? A) In a two-variable correlation, greater income predicts greater trust in government. This relationship continues to be true even partialling out corruption B) In a two-variable correlation, greater income predicts greater trust in government. But when partialling out corruption, there is no longer a relationship between income and trust C) At no point is there is a correlation between average income and trust, whether considering a two-variable correlation or a partial correlation D) There is not enough information given to determine what their conclusion was.
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.
A researcher wants to know if more average income in a country is associated with more trust in government. They measure both variables and find that r = .52, with p = .01. But then they wonder if that
| A) |
In a two-variable correlation, greater income predicts greater trust in government. This relationship continues to be true even partialling out corruption |
|
| B) |
In a two-variable correlation, greater income predicts greater trust in government. But when partialling out corruption, there is no longer a relationship between income and trust |
|
| C) |
At no point is there is a correlation between average income and trust, whether considering a two-variable correlation or a partial correlation |
|
| D) |
There is not enough information given to determine what their conclusion was. |
Trending now
This is a popular solution!
Step by step
Solved in 2 steps
