Data Random number generator to generate 50 values between zero and one.  0.0829 0.1917 0.8315 0.4897 0.5853 0.1376 0.9130 0.0618 0.2030 0.4521 0.3671 0.1921 1.000 0.5895 0.5568 0.3556 0.1293 0.5557 0.2341 0.4925 0.1948 0.6502 0.4771 0.7551 0.5425 0.9948 0.9128 0.8358 0.6053 0.6806 0.4290 0.2006 0.5654 0.3456 0.6568 0.3163 0.9002 0.6010 0.5173 0.4209 0.2407 0.5987 0.8626 0.2776 0.0051 0.8137 0.8831 0.9749 0.1041 0.6744 Plot the Data Construct a box plot of the data. Be sure to use a ruler t scale accurately and draw straight edges.  Do you notice any potential outliers? If so, which values are they? Either way, justify your answer numerically. (Recall that any DATA that are less than Q1 – 1.5(IQR) or more than Q3 + 1.5(IQR) are potential outliers. IQR means interquartile range.) Suppose that the number of values generated was 500, not 50. How would that affect what you would expect the empirical data to be and the shape of its graph to look like?

please use the calculator method ti 83 or 84 Several insurance adjusters were concerned about the unusually high estimates from Fosbert's U-Bet Repair Station. They obtained the following data: Car Number                            1          2          3          4          5          6          7          8 Fosbert's Estimate                 2.1       4.5       6.3       3.0       1.2       5.4       7.3       9.3 Nickles' Estimate                    2.0       3.8       5.9       2.8       1.3       5.0       6.5       8.6 Estimates are in hundreds of dollars. At a .005 level of significance determine whether the adjusters can conclude that Fosbert's is significantly higher than Nickles'. State hypotheses, P-value, and conclusion.

In computing the standard error of the mean, the finite population correction factor is used when O a. N/n> 0.05. O b. N/n S0.05. O C. n/N> 0.05. O d. n/N S 30.

Student  ID Math Score Project Score Age (years) Sex 001254 52 75 15 M 003256 78 89 15 F 001547 92 82 18 F 012589 91 66 17 M 021475 72 93 14 M 032658 46 76 13 M 009561 68 76 14 F 008654 52 82 12 F 008561 83 75 16 M 003547 45 78 14 F 047452 73 96 14 M 041212 64 79 13 F 032320 41 67 13 F 000258 77 72 15 F 001478 82 75 17 M 019521 59 83 15 M 017451 80 71 17 F 016335 48 76 13 M 002474 57 80 14 F 095844 97 71 18 F 097304 86     86 17 M 090024 75 85 15 F 034702 81 80 16 F 001910 67 74 14 F 006454 86 77 17 M 087478 63 82 13 M 078474 68 79 14 F 000977 54 89 12 M 063010 91 73 18 M 007406 46 77 15 F 025740 93 85 17 M…