MATH 2565 W 2007 Section M

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Tutorials before exams in TEL 2027 from 7 pm to x where x <= 10pm
Monday, April 23
Tuesday, April 24
Exam in TEL 2027
Thursday, April 26 from 7 pm to 10 pm


Links:






Math 2565 Introduction to Applied Statistics


Table of contents

News

  • No news is good news

General Information

The aim of this course to learn some basic concepts and tools in statistics and to have an introduction to the broad applications of statistics in modern business.

Instructor

Text

Groebner, D.F., P.W. Shannon, P. C. Fry, K. D. Smith (2005) Business Statistics: A Decision Making Approach, Updated 6th Edition, Prentice Hall.

Lab Access and Accounts

If you do not have an account to work in the lab, you should get one (see Lab Account Information (http://quartz.atkinson.yorku.ca/QuickPlace/aklabs/main.nsf/h_Toc/0D9FED7D5D3BFA1E85256EF400646740/?OpenDocument)) so you can use the lab during classes. Most group work can be done on your home machines or laptops since we are using free software and will collaborate using a wiki server.

Lectures and Tutorials

  • Lectures: Wednesdays: 7-10 in TEL 2027
  • Tutorials: Wendesdays: 6-7 in ACW 303

References

Course Work

[15] Approximately 5 wiki group assignments.
[50] Five 15-minute quizzes (best 4)
[30] Final exam
[5] Individual participation

Note that most of the course work except the exam will be done and posted on a wiki server and available for reference.

Class list and teams

Class photos, names, e-mail addresses and teams can be found at http://www.math.yorku.ca/~georges/Courses/2565. Note that for privacy a userid (fisher) and password (gates) are needed to access this page.

Assignments will be done on a wiki. Here is a page for you to practice with: MATH 2565 Practice Page.

Schedule

Week 1: January 3

Assignment

1. Send an e-mail message to georges@yorku.ca with the following information:
Your name
Previous mathematics and statistics courses
Programming languages
Academic program and year
What are your goals after you complete your undergraduate program?
Be sure to include 2565 in the subject of the message.
2. Download and install R on your home computer or laptop. For help see R: Getting started.
Try one of the tutorials (e.g. VR4:_Chapter_1_summary) and spend a few hours getting the feel of R.
Try the following in R:
  > data( Titanic )
  > Titanic
  > dd <- as.data.frame(Titanic)
  > dd
  > aggregate( dd['Freq'], dd[ c('Age','Survived') ], sum )
Be ready to discuss your answer to the following questions:
What percentage of children survived on the Titanic? What percentage of adults?
Can you find out what proportion of adult males?, adult females?
3. Readings for next week.
Read pp 1-22 of the handout from Statistics by Freedman, Pisani and Purves.
What would you answer to question 5 on p. 20?
Suppose you need surgery. You have a choice of going to Hospital A with a 10% rate of complications for surgery or to Hospital B with a 20% rate. How would you choose?
Read Chapter 1 of the text.

Material covered


Week 2: January 10

Topics

1. Experimental vs Observational data sets
If X and Y are correlated, what can it mean?
1) X causes Y?
2) Y causes X?
3) Another variable(s) Z(s) causes both X and Y?
a) Some Zs might be known and measurable. For these Zs we might be able to adjust using sophisticated statistical methods.
b) Some Zs might be known but hard or impossible to measure. This is more difficult to deal with.
c) Some Zs might not be discovered until the year 3000. We can't adjust statistically for these.
4) Selection: maybe there's no relationship but some data got thrown out or ignored and the data left created the impression of a relationship.
5) Chance: This is the one statisticians are really good at dealing with -- as you will learn in this course.
What if we have an 'experiment' with 'random allocation of X' to experimental units?
1) possible
2) No! We know what caused X. It was the coin toss or the random number generator that caused X.
3) Maybe. But it could only be by chance that differences in levels of any combination of Zs, known or not, measurable or not, would have a large impact on Y.
4) We can exclude this by careful checking.
5) Chance again.
So we are left with two options:
1) X causes Y, or
2) Chance.
We can use statistical analysis to measure chance. If the chance is very small then we may be left with X causes Y as the plausible explanation.
How should you react to causal claims based on data analyses?
1) Experimental data or observational? You might have to ask questions to answer this. Sometimes it isn't obvious from the appearance of the data.
2) If experimental: was allocation random or by judgment or haphazard? Was the study double-blind? Are there possible biases in measurements? Psychological factors that influence outcome? Does the claim match the nature of the experiment or is the claim stretching to something that does not correspond exactly to what was done in the experiment?
3) If observational:
a) Can you poke an obvious hole in the claim? E.g. is there a plausible alternative explanation that was not taken into account in the analysis? In this case, you've countered the claim.
b) What has the analysis adjusted for? Are these factors that can be measured with precision? What kinds of factors are not accounted for?
Some examples in the news: Toronto Star: Pulse (http://www.math.yorku.ca/~georges/Courses/2565/StatisticsInTheNews030926.html)
Which examples are experimental and which are observational?
Which conclusions are reasonable and which are not? Why?
References: Chapters 1 and 2 of FPP, Chapter 1 of GSFS.
2) Tools for collecting data
3) Populations, Samples and Sampling Techniques
4) Data Types and Data Measurement Levels
GSFS Chapter 1 Slides (http://www.math.yorku.ca/~georges/Courses/2565/lec1.pdf)

Summary

R scripts

Assignment

In class:
Log in to your wiki account.
Start R
Download data on Baseball players in 1987:
       > base.pop <- read.csv("http://wiki.math.yorku.ca/images/7/73/MATH_2565_Baseball_Data.csv")
       > base.pop
       > head( base.pop )
       > dim( base.pop )
       > summary( base.pop )
       > hist( base.pop$sal87 )
Take a sample of 30 baseball players
Find the mean salary of your sample. Warning: some values might be missing. You will to figure out what to do with this.
Add your wiki name and mean to the wiki page MATH 2565: Week 2 wiki data
While other complete the work, have a look at R:_Local_tutorial#Data_input
When everyone has finished, download the data created by the class with:
       > base.samples <- read.table( stdin(), header = T )
followed by cutting and pasting the data on the web into the R console.
Find the average of the averages.
Find the average for the population.
Is your average closer or farther in absolute distance from the population average than the average of averages?
Edit the wiki page by adding farther or closer next to your average.
Wiki Assignment:
For solutions to problems in the text book include a link to your solution in both MATH 2565 M Winter 2007 Solutions to Business Statistics and in your team page.
For solutions to other problems include a link to your solution in both MATH 2565 M Winter 2007 Assignment Solutions and in your team page.
Team Gates
Comment on the article on suicides and breast implant surgery in [1] (http://www.math.yorku.ca/~georges/Courses/2565/StatisticsInTheNews030926.html)
GSFS p. 12, Exer 1-2: 1.16, 1.20, 1.24, 1.29
GSFS p. 18, Exer 1-3: 1.32, 1.40
GSFS p. 22, Exer 1-4: 1.52, 1.55
GSFS p. 24, Chapter exercises: 1.62
Team Turing
Comment on the article on Tai-Chi and immunity in [2] (http://www.math.yorku.ca/~georges/Courses/2565/StatisticsInTheNews030926.html)
GSFS p. 12, Exer 1-2: 1.14, 1.19, 1.23, 1.28
GSFS p. 18, Exer 1-3: 1.35, 1.43
GSFS p. 22, Exer 1-4: 1.53, 1.56
GSFS p. 24, Chapter exercises: 1.60, 1.64
Team Babbage
Comment on the article on supportive spouses and chronic pain in [3] (http://www.math.yorku.ca/~georges/Courses/2565/StatisticsInTheNews030926.html)
GSFS p. 12, Exer 1-2: 1.14, 1.18, 1.22, 1.27
GSFS p. 18, Exer 1-3: 1.34, 1.42
GSFS p. 22, Exer 1-4: 1.54, 1.57
GSFS p. 24, Chapter exercises: 1.61, 1.65
Team Jobs
Comment on the article on cats and car accidents in [4] (http://www.math.yorku.ca/~georges/Courses/2565/StatisticsInTheNews030926.html)
GSFS p. 12, Exer 1-2: 1.17, 1.21, 1.25, 1.30
GSFS p. 18, Exer 1-3: 1.33, 1.41
GSFS p. 22, Exer 1-4: 1.58
GSFS p. 24, Chapter exercises: 1.59, 1.63

Week 3: January 17

  • Quiz 1

Material covered

  • Text: Chapter 2, Graphs, Charts, Tables. Describing Data.
  • Slides: Slides on Chapter 2 (http://www.math.yorku.ca/~georges/Courses/2565/lec2.pdf)
  • R script: Chapter 2

Assignment

Wiki Assignment:
For solutions to problems in the text book include a link to your solution in both MATH 2565 M Winter 2007 Solutions to Business Statistics and in your team page.
Use R whenever possible.
Team Gates
GSFS p. 44, Exer 2-1: 2.1, 2.5, 2.9, 2.13
GSFS p. 55, Exer 2-2: 2.23, 2.27, 2.31, 2.35
GSFS p. 64, Exer 2-3: 2.37, 2.41, 2.45
GSFS p. 66, Chap. 2 Exer.: 2.49, 2.53, 2.57
Team Turing
GSFS p. 44, Exer 2-1: 2.2, 2.6, 2.10, 2.14
GSFS p. 55, Exer 2-2: 2.20, 2.24, 2.28, 2.32
GSFS p. 64, Exer 2-3: 2.38, 2.42 2.46
GSFS p. 66, Chap. 2 Exer.: 2.50, 2.54, 2.58
Team Babbage
GSFS p. 44, Exer 2-1: 2.3, 2.7, 2.11, 2.15
GSFS p. 55, Exer 2-2: 2.21, 2.25, 2.29, 2.33
GSFS p. 64, Exer 2-3: 2.39, 2.43 2.47
GSFS p. 66, Chap. 2 Exer.: 2.51, 2.55, 2.59, 2.61, 2.64
Team Jobs
GSFS p. 44, Exer 2-1: 2.4, 2.8, 2.12, 2.16
GSFS p. 55, Exer 2-2: 2.22, 2.26, 2.30, 2.34
GSFS p. 64, Exer 2-3: 2.40, 2.44, 2.48
GSFS p. 66, Chap. 2 Exer.: 2.52, 2.56, 2.60

Week 4: January 24

Material covered

  • Text: Chapter 3, Describing Data Using Numerical Data.
  • Slides: Slides on Chapter 3 (http://www.math.yorku.ca/~georges/Courses/2565/lec3.pdf)
    • Caution: The slides show an oversimplified version of box and whisker plots. Use version in the text or lecture.
  • R script: Chapter 3

Assignment

Wiki Assignment:
For solutions to problems in the text book include a link to your solution in both MATH 2565 M Winter 2007 Solutions to Business Statistics and in your team page.
Use R whenever possible.
Team assignments are at http://www.math.yorku.ca/~georges/Courses/2565 (you might have to reload if your browser has cached the previous version)
Section Team Tapscott Team Yule Team Yates Team Wald
3-1, p. 93 2 10 4 12 6 14 8 16
3-2, p. 103 26 28 20 22 30 24 32
3-3, p. 110 38 44 40 48 34 42 36
Chapter, p. 114 52 60 68 54 62 70 56 64 72 50 58 66



Week 5: January 31

  • Quiz 2

Material covered

  • Text: Chapter 4, Sections 1 and 2.
  • Slides: Slides on Chapter 4 (http://www.math.yorku.ca/~georges/Courses/2565/lec4.pdf)
  • R script: None

Assignment

Wiki Assignment:
For solutions to problems in the text book include a link to your solution in both MATH 2565 M Winter 2007 Solutions to Business Statistics and in your team page.
Use R whenever possible.
Team assignments are at http://www.math.yorku.ca/~georges/Courses/2565 (you might have to reload if your browser has cached the previous version)
Section Team Tapscott Team Yule Team Yates Team Wald
4-1, p. 137 4 8 12 14 7 11 13 2 6 10 15 1 5 9
4-2, p. 156 18 22 26 30 34 38 16 20 24 28 32 36 17 21 25 29 33 37 19 23 27 31 35 29



Week 6: February 7

Material covered

Assignment

Wiki Assignment:
For solutions to problems in the text book include a link to your solution in both MATH 2565 M Winter 2007 Solutions to Business Statistics and in your team page.
Use R whenever possible.
Team assignments are at http://www.math.yorku.ca/~georges/Courses/2565 (you might have to reload if your browser has cached the previous version)
Section Team Tapscott Team Yule Team Yates Team Wald
4-1, p. 137 4 8 12 14 7 11 13 2 6 10 15 1 5 9
4-2, p. 156 18 22 26 30 34 38 16 20 24 28 32 36 17 21 25 29 33 37 19 23 27 31 35 29




Week 7: February 21

  • Class cancelled

Week 8: February 28

  • Quiz 3

Material covered


Wiki Assignment:
For solutions to problems in the text book include a link to your solution in both MATH 2565 M Winter 2007 Solutions to Business Statistics and in your team page.
Use R whenever possible.
Team assignments are at http://www.math.yorku.ca/~georges/Courses/2565 (you might have to reload if your browser has cached the previous version)
Section Team Calumet Team Founders Team Stong Team Winters
5-3, p. 210 40 44 48 52 56 60 43 47 51 55 59 63 41 45 49 53 57 61 42 46 50 54 58 62
Chap. 5 Exer. p. 220 82 86 84 88 85 89 83 87
6-1, p. 233 3 7 2 6 4 8 1 5
6-2, p. 248 14 18 22 26 11 15 19 23 12 16 20 24 13 17 21 25
6-3, p. 254 30 34 38 42 31 35 39 43 32 36 40 44 29 33 37 41
Chap. 6 Exer., p. 258 46 50 54 58 47 51 55 59 48 52 56 60 45 49 53 57

Week 9: March 7

  • Quiz 4
  • Note: Last day to drop: March 9

Material covered


Wiki Assignment:
For solutions to problems in the text book include a link to your solution in both MATH 2565 M Winter 2007 Solutions to Business Statistics and in your team page.
Use R whenever possible.
Team assignments are at http://www.math.yorku.ca/~georges/Courses/2565 (you might have to reload if your browser has cached the previous version)
Section Team Calumet Team Founders Team Stong Team Winters
7-1, p. 281 1 5 9 13 17 21 4 8 12 16 20 24 3 7 11 15 19 23 2 6 10 14 18 22
7-2, p. 288 28 32 36 37 25 29 33 38 26 30 34 39 27 31 35 40
7-3, p. 294 43 47 51 55 59 44 48 52 56 41 45 49 53 57 42 46 50 54 58
Chap. 7, p. 297 61 65 73 77 62 66 74 78 63 67 75 79 60 64 72 76
8-1, p. 324 1 5 9 13 17 2 6 10 14 18 3 7 11 15 19 4 8 12 16 20
8-2, p. 330 26 30 34 38 23 27 31 35 24 28 32 36 25 29 33 37
8-3, p. 336 42 47 43 48 40 45 41 46
Chap 8, p. 339 50 54 58 64 68 51 55 59 65 69 52 56 60 66 70 49 53 57 63 67

Week 10: March 14

Material covered

  • Text: Chapters 8, 9. Some sections omitted. List to come
  • Slides:


Wiki Assignment:
  • To be posted on Thursday, March 15.


Week 11: March 21

  • Quiz 5

Material covered


Wiki Assignment:
For solutions to problems in the text book include a link to your solution in both MATH 2565 M Winter 2007 Solutions to Business Statistics and in your team page.
Use R whenever possible.
Team assignments are at http://www.math.yorku.ca/~georges/Courses/2565 (you might have to reload if your browser has cached the previous version)
Section Team Calumet Team Founders Team Stong Team Winters
13-1, p. 510 4 8 12 3 7 11 2 6 10 1 5 9
13-2, p. 512 14 18 22 15 19 23 16 20 24 17 21 25
13-3, p. 541 28 32 29 33 30 34 31 35
Chap. 13, p. 544 41 45 49 40 44 48 39 43 47 42 46 50

Week 12: March 28

Tutorial