Question

A recent study on crime rates examines whether crime depends on sunshine. A researcher hypothesizes that sunshine makes people happy and thus reduces crime. She collects data from cities across the USA and their sunshine exposure, runs a regression, and finds the following:Dependent Variable: Number of Crimes per 100,000 people (higher scores mean more crime)DemocratsRepublicansIndependentSupport10300Oppose50100Don’t Care5020 R2 = .45Interpret the estimated slope, estimated intercept, and R2 from this regression. State whether the slope is statistically significant, how you reach

Answer 1

Answer and Explanation:

R-square measures whether the variation exists or how much dependence the independent variables on the dependent variables.

R2 = .45 which is quite low. This shows that there is not much variation. In order to increase the R2 the researcher can add more independent variables.

The below part is taken from the internet as the question was incomplete:

Sunny days = 0.5

Intercept = 2.1

The slope shows a positive relationship (direct relationship) with the dependent variable which is crime dependency.

Sunny days is the independent variable.

Intercept is also positive whereas there is significance in the p value which helps in concluding that we will reject the null hypothesis.