7. Geese counting part II - Residual analysis In the last problem, you conducted significance tests and developed a standardized residual using the estimated regression equation: y = bo + bix, where y = a goose observer's estimate of the number of geese in a flock, and x = the count of the geese in a flock based on a photograph. In this problem, you will use graphs of the standardized residuals from the regression for observer A to identify outliers and to check the validity of the model assumptions about the error variable E. The following output was obtained from the regression analysis for observer A using Minitab Statistical Software: The regression equation is A Estimate = - 4.93 + 0.850 Photo Predictor Coel SE Coel T Constant -4.927 9. 318 -0.53 0.600 Photo 0. 85014 0. 07479 11.37 0.000 S = 43. 5824 R-Sq = 75.0% R-Sq(adj ) = 74.4% A plot of the n = 45 standardized residuals against the independent variable x is shown here:A plot of the n = 45 standardized residuals against the independent variable x is shown here: 2- Standardized Residual -2 100 200 300 400 photo Note: Statisticians will often standardize the residuals (that is subtract their mean (0) and divide by their standard deviation) so that the values plotted have a standard deviation of 1. The shape of the plot is identical to the shape when non-standardized residuals are used, but using standardized residuals also allows you to test the assumption that the errors are normally distributed. If the standardized residuals follow a standard normal distribution, about 95% of the standardized residuals fall within two standard deviations of 0, and almost all of the standardized residuals fall within three standard deviations of 0. Assume that an observation is considered an outlier if it has a standardized residual that is greater than 2 in absolute value. How many observations are outliers using this criterion? O Two O Three None O OneThe standardized residual plot evidence contrary to the assumption that the variance of the error variable is constant. The histogram of the standardized residuals is shown here: 25- 20- 15 Frequency 10- -2.5 -2.0 -15 -1.0 05 0.0 0.5 10 15 2.0 25 3.0 35 40 45 50 5.5 Standardized Residual The histogram that the condition that the error variable & is normally distributed is violated. Based on your residual analysis, the inferences you made in the previous problem Minitab" and all other trademarks and logos for the Company's products and services are the exclusive property of Minitab Inc. All other marks referenced remain the property of their respective owners. See minitab.com for more information