Simple regression analysis Essay Lab 3: Simple Regression Analysis Given a desire of a Retail Chain management team to develop a strategy to forecasting annual sales, the following data from a random sample of existing stores has been gathered: STORE SQUARE FOOTAGE ANNUAL SALES ($) 1 1726.00 3681.00 2 1642.00 3895.00 3 2816.00 6653.00 4 5555.00 9543.00 5 1292.00 3418.00 6 2208.00 5563.00 7 1313.00 3660.00 8 1102.00 2694.00 9 3151.00 5468.00 10 1516.00 2898.00 11 5161.00 10674.00 12 4567.00 7585.00 13 5841.00 11760.00 14 3008.00 4085.00 Enter the variable names as follows: File Next, by clicking on ‘Data View’, we can enter the data: File Assuming, for now, that if a relationship exists between the two variables, it is linear in nature, we can generate a simple Scatterplot (or Scatter Diagram) for the data. Simple regression analysis Essay This is accomplished with the command sequence: File Which yields the following (editable) scatterplot: File We can generate a simple straight-line equation from the output resulting when using the Enter Command in regression: File File Regression Variables Entered/Removeda Model Variables Entered Variables Removed Method 1 Square Footageb . Enter a. Dependent Variable: Annual Sales in Dollars b. All requested variables entered. Simple regression analysis Essay Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .954a .910 .902 $936.850 a. Predictors: (Constant), Square Footage ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 106208119.686 1 106208119.686 121.009 .000b Residual 10532255.243 12 877687.937 Total 116740374.929 13 a. Dependent Variable: Annual Sales in Dollars b. Predictors: (Constant), Square Footage This is the intercept File Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 901.247 513.023 1.757 .104 Square Footage File1.686 .153 .954 11.000 .000 This is the slope a. Dependent Variable: Annual Sales in Dollars How to write up regression: Simple regression analysis Essay A linear regression was used to test the hypothesis that time in minutes would predict understanding. The overall model was significant in that R = .97, F(1, 222) = 579.32, p < .001. As time in minutes increased, understanding also increased. Regression Equation(y) = a + bx where x and y are the variables. b = The slope of the regression line a = The intercept point of the regression line and the y axis. X = First Score Y = Second Score you are predicting for Square footage: Please solve for the following square footage: x = 1. 300 2. 5000 3. 6000 4. 4498 5. 6600 6. 2200 7. 3450 8. 1700 9. 1000 10. 9000 Example: for number 1. Y = 901.247 + 1.686(300) 901.247 + 505.8 = $1407.047 Lab 3 Assignment for Canvas upload: For this week, please turn in a complete APA paper with all the sections as you did before including an abstract. Simple regression analysis Essay At the end of the paper, please include all of the solved regression equation problems as I did in the first example.