For Q, For Q39 L25 5710 = 5755 Ls = P The first quartile, or 25th...

 

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For Q, For Q39 L25 5710 = 5755 Ls = P The first quartile, or 25th percentile, is .25 of the way between the value in position 3 (5850) and the value in position 4 (5880). Thus, Q = 5850+.25(5880-5850) = 5850+.25(30) = 5857.5 (n (n + 1) = 100 5850 5880 Q = 5857.5 P 100 (n + 1) = (12 + 1) = 9.75 The third quartile, or 75th percentile, is .75 of the way between the value in position 9 (5950) and the value in position 10 (6050). Thus, Q = 5950+.75(6050-5950) = 5950+.75(100) = 6025 The quartiles divide the starting salary data into four parts, with each part containing 25% of the observations. 25% of the data 25% of the data 25 100 5880 5890 75 100 (12 + 1) = 3.25 25% of the data 5920 Q -5905 (Median) 5940 5950 25% of the data 6050 23=6025 6130 6325 We defined the quartiles as the 25th, 50th, and 75th percentiles and then we computed the quartiles in the same way as percentiles. However, other conventions are sometimes used to compute quartiles, and the actual values reported for quartiles may vary slightly de- pending on the convention used. Nevertheless, the objective of all procedures for comput- ing quartiles is to divide the data into four parts that contain equal numbers of observations. *2225 3.2 2.0 5.0 Weight (w,) 63200 8 a. Compute the weighted mean. b. Compute the sample mean of the four data values without weighting. Note the dif- ference in the results provided by the two computations. For Q, For Q39 L25 5710 = 5755 Ls = P The first quartile, or 25th percentile, is .25 of the way between the value in position 3 (5850) and the value in position 4 (5880). Thus, Q = 5850+.25(5880-5850) = 5850+.25(30) = 5857.5 (n (n + 1) = 100 5850 5880 Q = 5857.5 P 100 (n + 1) = (12 + 1) = 9.75 The third quartile, or 75th percentile, is .75 of the way between the value in position 9 (5950) and the value in position 10 (6050). Thus, Q = 5950+.75(6050-5950) = 5950+.75(100) = 6025 The quartiles divide the starting salary data into four parts, with each part containing 25% of the observations. 25% of the data 25% of the data 25 100 5880 5890 75 100 (12 + 1) = 3.25 25% of the data 5920 Q -5905 (Median) 5940 5950 25% of the data 6050 23=6025 6130 6325 We defined the quartiles as the 25th, 50th, and 75th percentiles and then we computed the quartiles in the same way as percentiles. However, other conventions are sometimes used to compute quartiles, and the actual values reported for quartiles may vary slightly de- pending on the convention used. Nevertheless, the objective of all procedures for comput- ing quartiles is to divide the data into four parts that contain equal numbers of observations. *2225 3.2 2.0 5.0 Weight (w,) 63200 8 a. Compute the weighted mean. b. Compute the sample mean of the four data values without weighting. Note the dif- ference in the results provided by the two computations.

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a To compute the weighted mean we use the formula weighted mean xi wi wi where xi represents the data values and wi represents their respective weight... View the full answer