Question: This is statistics course, sampling distributions, estimation and tests of units.I need help with this. I attached formula sheet in case you need it. II.

 This is statistics course, sampling distributions, estimation and tests of units.Ineed help with this. I attached formula sheet in case you needit. II. Probability P(AUB) = P(A) + P(B) - P(An B) P(AB)= P(An B) P(B) E(X) = Ux = Expi Var(X) = 0;= _(x - ux)2pi If X has a binomial distribution with parametersn and p, then: P(X = k) = k) p* (1 -p)" -* HI = np Or = Vnp(1 - p) Ho =P Op = P(1- p n If x is the mean of

This is statistics course, sampling distributions, estimation and tests of units.I need help with this. I attached formula sheet in case you need it.

a random sample of size n from an infinite population with meanu and standard deviation O, then: MY = HIII. Inferential Statistics Standardizedtest statistic: statistic - parameter standard deviation of statistic Confidence interval: statistic+ (critical value) . (standard deviation of statistic) Single-Sample Statistic Standard Deviationof Statistic Sample Mean Sample Proportion p(1 - p) n Two-Sample StatisticStandard Deviation of Statistic Difference of sample means 722 Special case when61 =02 ol+1 n2 Difference of PI (1 - PI) + P2(1 - P2) sample proportions n1 n2 Special case when P1 =

II. Probability P(AUB) = P(A) + P(B) - P(An B) P(AB) = P(An B) P(B) E(X) = Ux = Expi Var(X) = 0; = _(x - ux)2pi If X has a binomial distribution with parameters n and p, then: P(X = k) = k) p* (1 - p)" -* HI = np Or = Vnp(1 - p) Ho = P Op = P(1- p n If x is the mean of a random sample of size n from an infinite population with mean u and standard deviation O, then: MY = HIII. Inferential Statistics Standardized test statistic: statistic - parameter standard deviation of statistic Confidence interval: statistic + (critical value) . (standard deviation of statistic) Single-Sample Statistic Standard Deviation of Statistic Sample Mean Sample Proportion p(1 - p) n Two-Sample Statistic Standard Deviation of Statistic Difference of sample means 722 Special case when 61 =02 ol+1 n2 Difference of PI (1 - PI) + P2 (1 - P2) sample proportions n1 n2 Special case when P1 = P2 Jp(1 - P) 1 + 1 Vn, n2 Chi-square test statistic = \\ (observed - expected) expected\fTable entry for p and C is the point t* with probability p lying above it Probability p and probability C lying between -t* and t*. Table B t distribution critical values Tail probability p df .25 .20 .15 .10 05 .025 .02 .01 .005 0025 .001 .0005 1.000 1.376 1.963 3.078 6.314 12.71 15.89 31.82 63.66 127.3 318.3 636.6 .816 1.061 1.386 1.886 2.920 4.303 4.849 6.965 9.925 14.09 22.33 31.60 .765 978 1.250 1.638 2.353 3.182 3.482 4.541 5.841 7.453 10.21 12.92 .741 .941 1.190 1.533 2.132 2.776 2.999 3.747 4.604 5.598 7.173 8.610 .727 920 1.156 1.476 2.015 2.571 2.757 3.365 4.032 4.773 5.893 6.869 .718 906 1.134 1.440 1.943 2.447 2.612 3.143 3.707 4.317 5.208 5.959 .711 .896 1.119 1.415 1.895 2.365 2.517 2.998 3.499 4.029 4.785 5.408 .706 889 1.108 1.397 1.860 2.306 2.449 2.896 3.355 3.833 4.501 5.041 1703 883 1.100 1.383 1.833 2.262 2.398 2.821 3.250 3.690 4.297 4.781 10 700 879 1.093 1.372 1.812 2.228 2.359 2.764 3.169 3.581 4.144 4.587 .697 .876 1.088 1.363 1.796 2.201 2.328 2.718 3.106 3.497 4.025 4.437 12 695 873 1.083 1.356 1.782 2.179 2.303 2.681 3.055 3.428 3.930 4.318 13 694 870 1.079 1.350 1.771 2.160 2.282 2.650 3.012 3.372 3.852 4.221 14 .692 868 1.076 1.345 1.761 2.145 2.264 2.624 2.977 3.326 3.787 4.140 15 691 866 1.074 1.341 1.753 2.131 2.249 2.602 2.947 3.286 3.733 4.073 16 .690 865 1.071 1.337 1.746 2.120 2.235 2.583 2.921 3.252 3.686 4.015 689 863 1.069 1.333 1.740 2.110 2.224 2.567 2.898 3.222 3.646 3.965 18 688 862 1.067 1.330 1.734 2.101 2.214 2.552 2.878 3.197 3.611 3.922 19 .688 .861 1.066 1.328 1.729 2.093 2.205 2.539 2.861 3.174 3.579 3.883 20 687 860 1.064 1.325 1.725 2.086 2.197 2.528 2.845 3.153 3.552 3.850 21 686 859 1.063 1.323 1.721 2.080 2.189 2.518 2.831 3.135 3.527 3.819 686 .858 1.061 1.321 1.717 2.074 2.183 2.508 2.819 3.119 3.505 3.792 23 685 858 1.060 1.319 1.714 2.069 2.177 2.500 2.807 3.104 3.485 3.768 24 685 857 1.059 1.318 1.711 2.064 2.172 2.492 2.797 3.091 3.467 3.745 25 .684 856 1.058 1.316 1.708 2.060 2.167 2.485 2.787 3.078 3.450 3.725 26 .684 856 1058 1.315 1.706 2.056 2.162 2.479 2.779 3.067 3.435 3.707 27 684 855 1.057 1.314 1.703 2.052 2.158 2.473 2.771 3.057 3.421 3.690 28 683 855 1.056 1.313 1.701 2.048 2.154 2.467 2.763 3.047 3.408 3.674 29 683 .854 1.055 1.311 1.699 2.045 2.150 2.462 2.756 3.038 3.396 3.659 30 .683 .854 1.055 1.310 1.697 2.042 2.147 2.457 2.750 3.030 3.385 3.646 40 .681 .851 1.050 1.303 1.684 2.021 2.123 2.423 2.704 2.971 3.307 3.551 50 .679 .849 1.047 1.299 1.676 2.009 2.109 2.403 2.678 2.937 3.261 3.496 60 .679 .848 1.045 1.296 1.671 2.000 2.099 2.390 2.660 2.915 3.232 3.460 80 .678 .846 1.043 1.292 1.664 1.990 2.088 2.374 2.639 2.887 3.195 3.416 100 .677 .845 1.042 1.290 1.660 1.984 2.081 2.364 2.626 2.871 3.174 3.390 1000 .675 .842 1.037 1.282 1.646 1.962 2.056 2.330 2.581 2.813 3.098 3.300 .674 841 1.036 1.282 1.645 1.960 2.054 2.326 2.576 2.807 3.091 3.291 50% 60% 70% 80% 90% 95% 96% 98% 99% 99.5% 99.8% 99.9% Confidence level CTable entry Probability p for p is the point (x ) with probability p lying above it. (x2) Table C * critical values Tail probability p df .25 .20 .15 .10 05 025 .02 .01 .005 .0025 001 1 1.32 1.64 2.07 2.71 3.84 5.02 5.41 6.63 7.88 9.14 10.83 2.77 3.22 3.79 4.61 5.99 7.38 7.82 9.21 10.60 11.98 13.82 4.11 4.64 5.32 6.25 7.81 9.35 9.84 11.34 12.84 14.32 16.27 5.39 5.99 6.74 7.78 9.49 11.14 11.67 13.28 14.86 16.42 18.47 6.63 7.29 8.12 9.24 11.07 12.83 13.39 15.09 16.75 18.39 20.51 7.84 8.56 9.45 10.64 12.59 14.45 15.03 16.81 18.55 20.25 22.46 9.04 9.80 10.75 12.02 14.07 16.01 16.62 18.48 20.28 22.04 24.32 10.22 11.03 12.03 13.36 15.51 17.53 18.17 20.09 21.95 23.77 26.12 11.39 12.24 13.29 14.68 16.92 19.02 19.68 21.67 23.59 25.46 27.88 12.55 13.44 14.53 15.99 18.31 20.48 21.16 23.21 25.19 27.11 29.59 11 13.70 14.63 15.77 17.28 19.68 21.92 22.62 24.72 26.76 28.73 31.26 12 14.85 15.81 16.99 18.55 21.03 23.34 24.05 26.22 28.30 30.32 32.91 13 15.98 16.98 18.20 19.81 22.36 24.74 25.47 27.69 29.82 31.88 34.53 14 17.12 18.15 19.41 21.06 23.68 26.12 26.87 29.14 31.32 33.43 36.12 15 18.25 19.31 20.60 22.31 25.00 27.49 28.26 30.58 32.80 34.95 37.70 16 19.37 20.47 21.79 23.54 26.30 28.85 29.63 32.00 34.27 36.46 39.25 17 20.49 21.61 22.98 24.77 27.59 30.19 31.00 33.41 35.72 37.95 40.79 18 21.60 22.76 24.16 25.99 28.87 31.53 32.35 34.8 37.16 39.42 42.31 19 22.72 23.90 25.33 27.20 30.14 32.85 33.69 36.19 38.58 40.88 43.82 20 23.83 25.04 26.50 28.41 31.41 34.17 35.02 37.57 40.00 42.34 45.31 21 24.93 26.17 27.66 29.62 32.67 35.48 36.34 38.93 41.40 43.78 46.80 22 26.04 27.30 28.82 30.81 33.92 36.78 37.66 40.29 42.80 45.20 48.27 23 27.14 28.43 29.98 32.01 35.17 38.08 38.97 1.64 44.18 46.62 49.73 24 28.24 29.55 31.13 33.20 36.42 39.36 40.27 42.98 45.56 48.03 51.18 25 29.34 30.68 32.28 34.38 37.65 40.65 41.57 44.31 46.93 49.44 52.62 26 30.43 31.79 33.43 35.56 38.89 41.92 42.86 45.64 48.29 50.83 54.05 27 31.53 32.91 34.57 36.74 40.11 43.19 44.14 46.96 49.64 52.22 55.48 28 32.62 34.03 35.71 37.92 41.34 44.46 45.42 48.28 50.99 53.59 56.89 29 33.71 35.14 36.85 39.09 42.56 45.72 46.69 49.59 52.34 54.97 58.30 30 34.80 36.25 37.99 40.26 43.77 46.98 47.96 50.89 53.67 56.33 59.70 40 45.62 47.27 49.24 51.8 55.76 59.34 60.44 63.69 66.77 69.70 73.40 50 56.33 58.16 60.35 63.17 67.50 71.42 72.61 76.15 79.49 82.66 86.66 60 66.98 68.97 71.34 74.40 79.08 83.30 84.58 88.38 91.95 95.34 99.61 80 88.13 90.41 93.11 96.58 101.9 106.6 108.1 112.3 116.3 120.1 124.8 100 109.1 111.7 114.7 118.5 124.3 129.6 131.1 135.8 140.2 144.3 149.4\fD Question 43 1 pts Which of these represents the width of a confidence interval? O the product of the test statistic and the point estimator one margin of error O two margins of error O three margins of error O the product of the test statistic and the standard deviationD Question 44 1 pts A research firm conducted a simple random survey of 25 residents asking them if they planned to watch the 2017 Super Bowl or not. Of those surveyed, 16 responded "yes" and 9 responded "no". Does this scenario satisfy the conditions np > 10 and n(1 - p) 2 10 for normality? Choose the best explanation. Yes, because both the number of successes and failures is at least 10. O No, because the number of successes is not large enough. The sample size needs to be larger. O No, because the number of failures is not large enough. The sample size needs to be larger. O No, because the number of successes is at least 10. The sample size needs to be smaller. O No, because both the number of successes and failures is at least 10

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