Consider the following data. The summary statistics, histogram, and normal quantile plot were generated by Minitab. 27 27 27 28 28 28 28 28 28 29 29 29 29 29 29 29 29 29 29 30 30 30 30 30 30 30 30 30 30 30 30 31 31 31 31 31 31 31 31 32 32 32 32 33 33 33 33 33 34 34 Variable N N* Mean SE Mean StDev Data 50 0 30.160 0.256 1.811 Variable Minimum Q1 Median Q3 Maximum Data 27.000 29.000 30.000 31.000 34.000 (a) Does the histogram indicate normality for the data distribution? Explain. Yes, we observe a uniform, symmetric distribution. No, we observe a bell-shaped, skewed distribution. No, we observe a uniform, skewed distribution. Yes, we observe a bell-shaped, symmetric distribution. (b) Does the normal quantile plot indicate normality for the data distribution? Explain. Yes, the points fall approximately on a straight line. No, the points fall approximately on a straight line. Yes, the points do not fall on a straight line. No, the points do not fall on a straight line. (c) Compute the interquartile range. Check for outliers. There are two outliers. There is one outlier. There are no outliers. There are no outliers, but two data points fall exactly on the boundary. (d) Compute Pearson's index. (Round your answer to three decimal places.) Does the index value indicate skewness? Yes No (e) Using parts (a) through (d), would you say the data are from a normal distribution? No, the graphs do not support normality, there is no skewness, but there are apparent outliers . No, the graphs do not support normality, there are no apparent outliers, but there is skewness. Yes, the graphs support normality, there are no apparent outliers, but there is skewness . Yes, the graphs support normality, there are no apparent outliers, and there is no skewness