Honors Statistics. 3. Discuss homework C2# Discuss standard scores and percentiles. Chapter 2 Section Review day 2016s Notes.
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1 Honors Statistics Aug 23-8:26 PM 3. Discuss homework C2#11 4. Discuss standard scores and percentiles Aug 23-8:31 PM 1
2 Feb 8-7:44 AM Sep 6-2:27 PM 2
3 Sep 18-12:51 PM Chapter 2 Modeling Distributions of data Sep 6-2:28 PM 3
4 Complete the SLTR worksheet page : 1-4, 9-11 #10 use list FLIES and only do a Normal probability plot Chapter 2 Review Exercises ANSWERS IN BACK OF TEXTBOOK Oct 10-10:50 AM Key The distribution of St. Louis total runs is NOT symmetric. It is skewed to the right. It is NOT normally distributed. Feb 6-12:38 PM 4
5 _ x = 5.97 S x = 3.13 n = Feb 6-12:33 PM too 0.76 high perfect 1.00 almost perfect First st dev off but in general pretty close IQR s = 8-3 = This value is too high, meaning that the middle 50% of data spreads out too many standard deviations to be considered normally distributed. Feb 6-12:32 PM 5
6 There is slight arcing on this normal probability plot of the St Louis total runs, the plot is not a straight line but it is not terrible. The data set can be determined to be slightly right skewed using the "line analysis" because it falls away "right" of the red line. Sep 28-8:59 AM This data set should not be considered Normally Distributed. None of the methods provide an analysis that shows the data to be normally distributed. Method 2 show the 2nd and 3rd standard deviations to be perfect but the 1st standard deviation is too large. The data is skewed but not as severely as some of the data we have analyzed. Feb 6-12:36 PM 6
7 Book Chapter review problems: pages 136 and 137 Sep 23-11:27 AM Sep 23-1:28 PM 7
8 Sep 23-1:28 PM Sep 23-1:28 PM 8
9 Sep 23-1:29 PM Sep 23-1:29 PM 9
10 Sep 23-1:29 PM Standard deviations and percentiles 8 points Data transformations 4 points OGIVES 14 points Normal curve questions 40 points 10 multiple choice questions 40 points FRIDAY PART II - 20 points using the 4 Normality methods 20 points Feb 21-1:33 PM 10
11 Chapter 2 Review: Multiple Choice Feb 10-7:15 AM Sep 23-11:04 AM 11
12 Sep 24-10:05 AM Sep 24-10:05 AM 12
13 Sep 23-9:41 AM Sep 23-9:41 AM 13
14 Sep 23-9:41 AM Sep 23-9:41 AM 14
15 Sep 23-9:41 AM Sep 23-9:42 AM 15
16 Sep 23-9:42 AM Sep 23-9:42 AM 16
17 Sep 23-9:42 AM Sep 23-9:42 AM 17
18 Sep 23-9:42 AM Sep 23-9:42 AM 18
19 Sep 22-3:20 PM Sep 22-3:20 PM 19
20 Sep 22-3:22 PM Oct 2-3:06 PM 20
21 Oct 2-3:07 PM Sep 28-12:37 PM 21
22 Sep 29-9:20 AM Sep 22-3:43 PM 22
23 Sep 22-3:43 PM Sep 22-3:43 PM 23
24 Sep 22-3:43 PM Sep 22-3:44 PM 24
25 Sep 22-3:44 PM great white sharks is roughly symmetric. It is roughly bell shaped. It appears to be very roughly normal. Oct 4-9:17 AM 25
26 _ x = S x = 2.55 n = perfect ALMOST PERFECT Feb 6-12:33 PM perfect 1.00 almost perfect IQR s = 2.55 = 1.43 This value is very close to 1.34, meaning that the middle 50% of data spreads out almost exactly the number of standard deviations required to be considered normally distributed. Feb 6-12:32 PM 26
27 The normal probability plot shows no major deviations from linear (a straight line). The data set can be considered to be normally distributed. Sep 28-8:59 AM This data set should be considered Normally Distributed. All four of the methods provide an analysis that show that original data to be normally distributed. It is not a perfect match but the only concern is the outlier at the top of the data set. Feb 6-12:36 PM 27
28 OPTIONAL: extra MC practice page : 1-10 Oct 10-10:50 AM T2.1. Many professional schools require applicants to take a standardized test. Suppose that 1000 students take such a test. Several weeks after the test, Pete receives his score Mar 3-3:45 PM 28
29 T2.2. For the Normal distribution shown, the standard deviation is closest to > (a) 0 > (b) 1 > (c) 2 > (d) 3 > (e) 5 5-2=3 Mar 3-3:49 PM corrected by adding 0.1 ph units to all of the values and then multiplying the result by ( )(1.2) = 5.64 (1.10)(1.2) = 1.32 Mar 3-3:51 PM 29
30 60-20 = 40% Mar 3-3:51 PM distributed with a mean of 55 inches. If the snowfall in Chillyville exceeds 60 inches in 15% of the years, what is the standard deviation? Mar 3-3:52 PM 30
31 Sep 29-12:12 PM Mar 3-3:53 PM 31
32 T2.7. If the heights of a population of men follow a Normal distribution, and 99.7% have heights between 5 0 and 7 0, what is your estimate of the standard deviation of the heights in this 1 foot = 12 inches 12/3 = 4 inches Mar 3-3:53 PM Mar 3-3:54 PM 32
33 z = _ = Mar 3-3:54 PM z = _ = z = _ = Mar 3-3:55 PM 33
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