Single linear regression allows statistics to show the relationship between two variables. The Kesher Foundation wanted to compare anxiety to homelessness for veterans. The levels of anxiety will indicate if there is a correlation with being homeless. One variable denotes as the predictor (homelessness), independent variable, while the other variable is the response, dependent variable (anxiety). The equation y = a + bx can be used to predict anxiety levels by putting the dependent variable where the Y goes. The X is where you would put the independent variable at. B is the slope of the line, meaning the direction of the. Looking at the output of the gathered information the correlation (R) shows a positive relationship. It is closer to positive one, so therefore the relationship is positive. The R square of 85% shows that the minutes of meditating for the veterans is the variance. It verifies that the expectation of homelessness increases anxiety is a positive relationship. The significant area shows a number of .000, which means that the outcome is significant because the p value is less than 0.05. The constant area shows a number value of 7.723, which means that x = 0 and y is equal to 7.7. The slope of the equation is the minutes per day area. It shows a representation of -.102