Using data from the 2008 General Social Survey (GSS), political psychologists were interested in whether speaking a language other than English (1=yes, 2=no) and political views (1=extremely liberal, 7=extremely conservative) would predict attitudes toward the number of immigrants there should be in the United States (1=should be increased a lot, 5=should be reduced a lot). Write out the regression model and explain what the bs and a mean. Which predictor variable contributed more to the model? Show evidence.
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.
Using data from the 2008 General Social Survey (GSS), political psychologists were interested in whether speaking a language other than English (1=yes, 2=no) and political views (1=extremely liberal, 7=extremely conservative) would predict attitudes toward the number of immigrants there should be in the United States (1=should be increased a lot, 5=should be reduced a lot).
Write out the regression model and explain what the bs and a mean. Which predictor variable contributed more to the model? Show evidence.


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