BNAD 276. STATISTICAL INFERENCE IN MANAGEMENT.
SUMMER 2017. UNIVERSITY OF ARIZONA

THIS IS THE COURSE CONTENT FOR ECON/BNAD/MGMT 276 IN 2017 PRE-SESSION SUMMER (15-DAY COURSE)

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Class Schedule
Monday to Friday: 1pm--3.50pm in MCLND 128

Office Hours
Monday to Thursday: 4pm--5pm in MCLND 401C

Course Materials
I do not strictly require any textbooks. You can use my lecture notes to study. I recommend the followings for those who want to get more basic and intuitive insights of statistics:

* Business Statistics: Communicating with Numbers by Sanjiv Jaggia and Alison Kelly (JK textbook)
This is one of the standard textbooks that is used for first course of business and economic statistics. The focus is on core topics but the book does do a good job of covering most of the topics that people will want to learn about this subject.

* Cartoon Guide to Statistics by Larry Gonick and Woollcott Smith
This book is perfect for people who want a simple introduction to statistics. The cartoons make the subject easy to comprehend and are actually quite fun. Even some very complex statistical ideas are made easy through the use of cartoons. If you want to learn all about basic statistics without putting in a lot of effort then this might be the best book to choose.

Course Syllabus
Syllabus

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Course Outline and Lecture Notes

Day 1. May 15: Data & Statistics. Descriptive Statistics I
Lecture note 1
Reference to JK: Ch. 1--2
Restaurant Data to graph the charts in the lecture.

Day 2. May 16: Descriptive Statistics II
Lecture note 2
Reference to JK: Ch. 2--3

Quiz 1 download
Due on Wednesday 17 May 2017.

Day 3. May 17: Quiz 1. Probability Theory I
Lecture note 3
Reference to JK: Ch. 4

Day 4. May 18: Probability Theory II
Lecture note 4
Reference to JK: Ch. 4

The following formula sheet will be handed out in the test 1:
Handed out formula sheet

Day 5. May 19: Midterm 1. Random Variables & Discrete Variable Probability Distribution
Lecture note 5
Reference to JK: Ch. 5
Exercises

Day 6. Monday, May 22: Discrete Variable Probability Distribution
Use lecture note 5
Reference to JK: Ch. 5

Day 7. May 23: Continuous Variable Probability Distribution I
Lecture note 6
Reference to JK: Ch. 6

Quiz 2 download
Due on Wednesday 24 May 2017.

Day 8. May 24: Submit Quiz 2. Continuous Variable Probability Distribution II
Use lecture note 6
Reference to JK: Ch. 6

Day 9. May 25: Sampling. Point Estimation. Sampling Distributions
Lecture note 7
Excel file to do simulation for sample mean and sample variance and sample proportion
Reference to JK: Ch. 7

Test 2 covers lecture notes 5 and 6 (i.e. discrete random variables and continuous random variables). Extra Practice Questions for Test 2:
Practice Questions for Test 2

The following handouts will be given in the test 2:
Handed out formula sheet
Z-Table

Day 10. May 26: Midterm 2. Interval Estimation
Lecture note 8
Reference to JK: Ch. 8
Supplement:
t-table

Day 11. May 29: Memorial Day. No Class

Day 12. May 30: Interval Estimation (cont'd). Hypothesis Testing I.
Hypothesis Test is in Lecture Note 9 below
Lecture note 9
Reference to JK: Ch. 9

Quiz 3 download
Due on Wednesday 31 May 2017.

Day 13. May 31: Quiz 3. Hypothesis Testing II
Continue lecture note 9
Reference to JK: Ch. 9, 10
Z-Table
t-table

Day 14. June 1: Simple Linear Regression. Comprehensive Review.
Reference to ASW: Ch. 14
Lecture Note 10

Day 15. June 2: Final Exam
The final exam conceptually covers everything from lecture notes 1 to 9, emphasizing the lecture notes 5--9 (discrete and continuous probability distribution and statistical inferences).
How to prepare for the Final Exam:
Do all questions in Test 1 (except question 31).
Do all questions in Test 2
All questions in Quiz 3
Do all execises and examples in lecture notes 7, 8, 9. You can choose to learn either critical value approach or p-value approach to test the hypothesis.
Important concepts: sample variance, sample standard deviation, sample mean, median, sample covariance, sample correlation coefficient, joint probability distribution table, recognize probability of some events, conditional probability, population/true variance, population/true mean, population/true standard deviation, discrete probability function, requirements for a valid probability functions, binomial distribution, Poisson distribution, uniform distribution, normal distribution, standard normal distribution, point estimation, sampling distribution, probability by using sampling distribution, interval estimation, hypothesis testing (two tailed, lower tailed, upper tailed)

Test 1 and test 2 in blanks for practice
Test 1
Test 2

The followings will be handed out in the final exam:
Z-Table
t-table
Handed out formula sheet
The first instruction page in the exam