Honors Statistics - Kenston Local Schoolskenstonlocal.org/baugher/wp-content/uploads/2015/06/chapter-2...Honors Statistics Aug 23-8:31 PM ... Chapter 2 Modeling Distributions of data

Chapter 2 Section Review day 2016s Notes.notebook

1

February 10, 2016

Aug 23-8:26 PM

Honors Statistics

Aug 23-8:31 PM

3. Discuss homework C2#11

4. Discuss standard scores and percentiles


2

February 10, 2016

Feb 8-7:44 AM

Sep 6-2:27 PM


3

February 10, 2016

Sep 18-12:51 PM

Sep 6-2:28 PM

Chapter 2 Modeling Distributions of data


4

February 10, 2016

Oct 10-10:50 AM

Complete the SLTR worksheet

page 136-137: 1-4, 9-11

#10 use list FLIES and only do a

Normal probability plotChapter 2 Review Exercises ANSWERS IN BACK OF TEXTBOOK

Feb 6-12:38 PM

The distribution of St. Louis total runs is

NOT symmetric. It is skewed to the

right. It is NOT normally distributed.

Key


5

February 10, 2016

Feb 6-12:33 PM

x = 5.97 Sx = 3.13_

-3.42 -0.29 2.84 5.97 9.1 12.23 15.36

44

n = 58

55

58

2.84 9.14458 0.76 too

high

-0.29 12.235558 0.95 perfect

-3.42 15.36 5858

1.00 almost

perfect

First st dev off but in general pretty close

Feb 6-12:32 PM

IQRs = = 1.6 8-3

3.13

This value is too high, meaning that the

middle 50% of data spreads out too

many standard deviations to be

considered normally distributed.


6

February 10, 2016

Sep 28-8:59 AM

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.

Feb 6-12:36 PM

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.


7

February 10, 2016

Sep 23-11:27 AM

Book Chapter review problems: pages 136 and 137

Sep 23-1:28 PM


8

February 10, 2016

Sep 23-1:28 PM

Sep 23-1:28 PM


9

February 10, 2016

Sep 23-1:29 PM

Sep 23-1:29 PM


10

February 10, 2016

Sep 23-1:29 PM

Feb 21-1:33 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


11

February 10, 2016

Feb 10-7:15 AM

Chapter 2 Review: Multiple Choice

Sep 23-11:04 AM


12

February 10, 2016

Sep 24-10:05 AM

Sep 24-10:05 AM


13

February 10, 2016

Sep 23-9:41 AM

Sep 23-9:41 AM


14

February 10, 2016

Sep 23-9:41 AM

Sep 23-9:41 AM


15

February 10, 2016

Sep 23-9:41 AM

Sep 23-9:42 AM


16

February 10, 2016

Sep 23-9:42 AM

Sep 23-9:42 AM


17

February 10, 2016

Sep 23-9:42 AM

Sep 23-9:42 AM


18

February 10, 2016

Sep 23-9:42 AM

Sep 23-9:42 AM


19

February 10, 2016

Sep 22-3:20 PM

Sep 22-3:20 PM


20

February 10, 2016

Sep 22-3:22 PM

Oct 2-3:06 PM


21

February 10, 2016

Oct 2-3:07 PM

Sep 28-12:37 PM


22

February 10, 2016

Sep 29-9:20 AM

Sep 22-3:43 PM


23

February 10, 2016

Sep 22-3:43 PM

Sep 22-3:43 PM


24

February 10, 2016

Sep 22-3:43 PM

Sep 22-3:44 PM


25

February 10, 2016

Sep 22-3:44 PM

Oct 4-9:17 AM

great white sharks is roughly symmetric. It is roughly bell shaped. It appears to be very roughly normal.


26

February 10, 2016

Feb 6-12:33 PM

x = 15.59 Sx = 2.55_

7.94 10.49 13.04 15.59 18.14 20.69 23.24

30

n = 44

42

44

13.04 18.143044 0.68 perfect

10.49 20.694244 0.95 perfect

7.94 23.24 4444

1.00 almost

perfect

ALMOST PERFECT

Feb 6-12:32 PM

IQRs

= = 1.43 17.2-13.55

2.55

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.


27

February 10, 2016

Sep 28-8:59 AM

The normal probability plot shows no major

deviations from linear (a straight line). The

data set can be considered to be normally

distributed.

Feb 6-12:36 PM

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.


28

February 10, 2016

Oct 10-10:50 AM

OPTIONAL: extra MC practice

page 138-140: 1 - 10

Mar 3-3:45 PM

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


29

February 10, 2016

Mar 3-3:49 PM

T2.2. For the Normal distribution shown, the standard deviation is closest to

5-2=3> (a) 0

> (b) 1

> (c) 2

> (d) 3

> (e) 5

Mar 3-3:51 PM

corrected by adding 0.1 pH units to all of the values and then multiplying the result by

(4.60+0.1)(1.2) = 5.64

(1.10)(1.2) = 1.32


30

February 10, 2016

Mar 3-3:51 PM

60 - 20 = 40%

Mar 3-3:52 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?


31

February 10, 2016

Sep 29-12:12 PM

Mar 3-3:53 PM


32

February 10, 2016

Mar 3-3:53 PM

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 3-3:54 PM


33

February 10, 2016

Mar 3-3:54 PM

z = _500-470 = 0.27110

Mar 3-3:55 PM

z = _500-470 = 0.27110

z = _530-515 = 0.129116

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Honors Statistics - Kenston Local Schoolskenstonlocal.org/baugher/wp-content/uploads/2015/06/chapter-2...Honors Statistics Aug 23-8:31 PM ... Chapter 2 Modeling Distributions of data