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ex. distribution: = 150, S = 5 xx 1) If the distribution is bell-shaped (symmetric) What % of all data contains scores that are at least 165? ~0.15% Find the score having Z = 2.47 x = + SZ -> 150... + 5(2.47) -> 162.35 xx Between what scores can we find approx. 95% of all the data values? between 140 and 160 Compute and interpret the Z score for 139. z = (x- )/S -> (139-150)/5 = -2.20 xx the score 139 is 2.20 SD below the mean Write the intervals containing suspicious outliers. [135,140] or [160,165] Write the intervals containing definite outliers. x < 135 or x > 165 Write the intervals containing the usual data values. [140,160] Classify the values: {130, 139, 146,164, 167, 140} Usual Data Values: 146, 140 Suspect: 139, 164 Definite Outliers: 130, 167 At least, what percent of all data lies between 145 and 155? k = 1 cannot be determined using Chebyshev b/c k=1 and it has to be >1 At least, what percent of all data lies between 140 and 160? k = 2 at least 75% At least, what percent of all data lies between 135 and 165? k = 3 at least 88.9% P68 = 1000 -> 1000 is the 68th percentile Interpretations: 1000 is greater than or equal to 68% of the data 1000 is less than or equal to 32% of the data 68% of the data is less than or equal to 1000 32% of the data is greater than or equal to 1000 P25 can be interpreted as the 25th percentile, the first quartile (Q1), and the lower quartile (QL) P50: 50th percentile, 2nd quartile (Q2), middle quartile (QM), and median [Show More]

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