Download 69 - School of Mathematics and Statistics

69.266*
BUSINESS STATISTICS I
Fall 2002
Instructor:
A. Woodside office: 3205 HP,
phone: 520-2600 ext. 2143
email: [email protected]
webpage: http://math.carleton.ca/~awoodsid
Text:
Business Statistics in Practice, ed 2, by Bowerman, O'Connell, Hand
Computer Manual: Learning SAS Version 8 (course pack manual sold in lab class or in bookstore)
A 3 1/2" diskette for saving your SAS programs and output.
References:
Statistics for Management and Economics, by Keller & Warrack
Introduction to Probability & Statistics, 10 ed: Mendenhall/Beaver/Beaver
Basic Business Statistics: Berenson & Levine
Statistics for Business & Economics: Anderson, Sweeney & Williams
Calculators:
Only NON-PROGRAMMABLE calculators may be used for tests and exams.
Timetable:
The course involves 3 hours of lectures each week and a one hour COMPULSORY
statistical computing lab most weeks.
Computer Lab:
3393 HP
Labs will start the week of Sept. 16
Assignments: There will be 4 or 5 assignments, depending on length. ALL assignments count toward the
term mark. Assignments will not all be worth the same amount. Your final
assignment mark will be the sum of your marks divided by the possible total of all the
assignments.
Midterms:
There will be 2 term tests of 1 1/2 hours each. Test 1 will be held on Friday, Oct. 4
sometime between 5:00 and 7:00pm, and Test 2 on Friday, Nov. 8 between 5:00
and 7:00pm. Locations will be given in class. Make sure you find out exactly
when and where a test will be held.
Marking Scheme:
Final Exam:
Lab assignments:
MidTerm:
NOTE:
50%
25%
25%
1.
At least 3 lab assignments must be handed in or an automatic grade of F
will be given for the course.
2.
A mark of at least 40% is required on the final exam in order to receive a
passing grade.
3.
Material covered in class may not always be the same as that in the text.
Some topics may be expanded and others not covered.
Solutions:
Solutions to all assignments, review problems, tests, etc. will be put on Reserve in the
Library. Ask for the 69.266 Reserve Binder at the Reserve Desk. There will also be
extra copies in 3203 HP (Mrs. Woodside's office).
Paul Menton Centre: Students with disabilities requiring special accomodation are encouraged to contact a
coordinator at the Paul Menton Centre to complete the necessary letters of
accomodation. After registering with the PMC, make an appointment to
come and discuss your needs with me at least two weeks prior to the first inclass test. Please note that the deadline for submitting Formal Examination
Accomodation Forms for December examinations to the Paul Menton Centre
is November 1, 2002.
COURSE OUTLINE (APPROXIMATE)
Weeks
1
Contents
Text Sections
Overview of Course:
Introduction to statistics:
what is statistics?, population, sample, descriptive statistics, statistical inference, types 1.1 - 1.4
of data
(defns. as
given in class)
Basic Probability:
random experiment, sample space, events; approaches to assigning probabilities
Chapter 3 +
(classical, relative freq., subjective); axiomatic definition & rules of probability;
class material
addition rule; Venn diagrams; contingency tables; conditional probability &
independence; multiplication rule; probablity trees; counting rules; Bayes Theorem;
to
Descriptive Statistics:
Graphical
Numerical
4
frequency distributions (freq., relative freq., percentage, cumulative);
histograms & polygons; stem & leaf displays; pie charts, bar charts, line
charts; scatter diagrams; graphical deception
measures of location and dispersion for populations and samples (mean,
median, mode, range, variance, standard deviation, C.V.) for both raw &
grouped data; shape of a distribution; Empirical rule; Tchebychef rule;
quantiles, IQR, box plots
2.1 - 2.7
Random Variables, Probability Distributions & Mathematical Expectation:
4.1, 4.2
random variables; probability distribution (of discrete r.v.); expected values, mean &
variance of discrete prob. distns.; rules of expected values & variance
Specific Discrete Probability Distributions:
4.3, 4.4
binomial, hypergeometric, binomial approximation to hypergeometric, Poisson distn., Appendix C
Poisson approximation to binomial
Weeks
Contents
Text Sections
5
Continuous Probability Distributions:
probability density function; P(a < Y < b) as area under density function; expected
values as integrals; uniform distribution; normal distribution; calculating normal
5.1 - 5.4
probabilities; normal approximations to binomial, Poisson distributions; exponential 5.5(if time)
distn.(if time)
to
Sampling & Sampling Distributions:
random sampling; concept of sampling distn.; sampling distn. of the sample mean,
Central Limit Theorem, finite population correction factor; sampling distn. of the
sample proportion; sampling distn. of the sample variance
8
9
to
6.1, 6.2 +
8.8
Estimation:
point estimators (unbiasedness, consistency, efficiency); interval estimators,
confidence interval for population mean variance known
7.1 +
Introduction to Hypothesis Testing:
concepts of hypothesis testing - null & alternative hypotheses, test statistic, critical
region, type I & type II errors, power of test(what it means, not calculation)
8.1
Single Population Inference:
tests about a single population mean variance known; tests about a single population
variance, confidence interval for variance; tests about a population proportion,
confidence interval for proportion; tests about a population mean, variance unknown
7.2, 7.4(p260262),
8.2 - 8.6, 8.9
Comparison of Two Populations:
tests about the difference in 2 population means, variances known, confidence interval
for difference in means; tests about the difference in 2 population means, variances
9.1, 9.2, 9.4
unknown, confidence interval variances unknown; paired t-test
Sample Size Determination:
for estimating a population mean; for estimating a population proportion
12
7.3, 7.4(p262264)
Testing for Normality (if time)
Catch-up and Review
WARNING: The above weekly schedule is subject to change. Make sure you keep up to date with any changes in
order of presentation, etc.