If there is no seasonal effect on human births, we would expect equal numbers of children to be born in each season (winter, spring, summer, and fall). A student takes a census of her statistics class and finds that of the 120 students in the class, were born in winter, in spring, in summer, and in fall. She wonders if the excess in the spring is an indication that births are not uniform throughout the year. The results of a hypothesis test based on this information are given. Complete parts (a) through (c). : There is no seasonal effect for birth rates. : There is a seasonal effect for birth rates. With and 3 degrees of freedom, the P-value is , and we fail to reject the null hypothesis at the significance level. There is insufficient evidence to conclude that there is a season effect for birth rates. a) Compute the standardized residual for each season. (Type integers or decimals rounded to three decimal places as needed.) Standardized Residual Winter negative 0.913 Spring 0.730 0.365 Fall negative 0.183 b) Are any of the standardized residuals particularly large? (Compared to what?) A. The standardized residuals are z-scores and not particularly large because they are between and 2. Your answer is correct.B. The standardized residuals are particularly large compared to the value of the chi-square test statistic. C. The standardized residuals are z-scores and at least one of them is particularly large, having a magnitude greater than 2. D. The standardized residuals are not particularly large compared to the value of the chi-square test statistic. c) Why should you have anticipated the answer to (b)? A. Would have anticipated that none of the standardized residuals would be too large because the data values are all similar. B. We would have anticipated that at least one of the standardized residuals is particularly large because we rejected the null hypothesis. C. We would have anticipated that none of the standardized residuals would be too large because we did not reject the null hypothesis.