Download MAT 164. Semesters Offered: Fall, Spring, Summer. 3

Hagerstown Community College
OFFICIAL COURSE SYLLABUS DOCUMENT
COURSE:
MAT 165 – Statistics for Business and Economics
INSTRUCTOR:
Phone:
E-Mail:
Office:
Hours:
3 Credits
Mr. Crawford
301.790.2800 x-643
[email protected]
LRC-113
TR
MW
Other Hours by Appointment
SEMESTER/YEAR: Summer 2007
COURSE DESCRIPTION:
This course investigates the application of statistical tools to practical exercises and cases from the
disciplines of business and economics. While introductory statistical concepts will be reviewed; familiarity
with elementary statistics, normal distributions, and statistical notation is highly recommended. Exercises,
practical applications, and case problems will be used to guide student investigation of probability and
sampling distributions, interval estimation, hypothesis testing, comparison of means, and regression. Special
attention will be given to ANOVA, multiple regressions, and statistical methods for product and service
quality control. Corequisites: MAT 164. Semesters Offered: Fall, Spring, Summer. 3 Credits
TEXTBOOK:
Essentials of Modern Business Statistics, 2nd Edition, Anderson, Sweeny, & Williams; Thomson
Southwestern, 2004, ISBN # 0-324-18452-2
STUDENT LEARNING OUTCOMES:
1. Use computational techniques and algebraic skills essential for success in an academic, personal,
or workplace setting. (Computational and Algebraic Skills)
2.
Use visualization, special reasoning, as well as geometric properties and strategies to model and
solve problems. (Geometric Skills)
3.
Collect, organize, and display data as well as use appropriate statistical methods to analyze data
and make inferences and predictions. (Statistical Skills)
4.
Critically analyze and construct mathematical arguments. (Proof and Reasoning)
5.
Use technology, where appropriate, to enhance and facilitate mathematical understanding, as well
as an aid in solving problems and presenting solutions. (Technological Skills)
6.
Communicate and Understand mathematical statements, ideas and results, both verbally and in
writing, with the correct use of mathematical definitions, terminology and symbolism.
(Communication Skills)
7.
Work collaboratively with peers and instructors to acquire mathematical understanding and to
formulate and solve problems and present solutions. (Collaborative Skills)
COURSE CONTENT OBJECTIVES:
Numbers listed in trailing parentheses reference Mathematics Program Outcomes/Student Learning
Outcomes. Outcome # 7 promotes student success and empowers professional growth of HCC graduates;
therefore it is incorporated and emphasized throughout this course.
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
Define, identify, & discuss various types of data and error. (6)
Critically analyze statements made about a data set. (4, 6)
Summarize data in graph and chart formats. (1, 2, 3, 5, 6)
Construct cumulative and cumulative relative frequency distributions. (1, 2, 3, 6)
Use technology to summarize and interpret data. (3, 5)
Create crosstabulations both manually and using technology. (1, 3, 5)
Calculate measures of centrality and dispersion both manually and using technology. (1, 3, 5)
Calculate a z-score and use Chebyshev’s theorem. (1, 3, 4)
Calculate probability and conditional probability. (1, 3, 4, 5)
Construct a joint probability table. (1, 3, 4, 6)
Determine the validity of a discrete probability distribution. (1, 3, 4)
Calculate expected value & variance and use this information to make and justify decisions. (1, 3, 5, 6)
Use and interpret area as a measure of probability. (1, 2, 3, 5)
Calculate and interpret point estimates. (1, 3, 5)
Construct sample distributions and analyze them to evaluate statements made about data, as well as to make
and justify decisions. (1, 3, 4, 5, 6)
16. Calculate confidence intervals (1, 3)
17. Use confidence intervals to determine the relative strength or weakness of arguments. (3, 4)
18. Calculate and interpret interval estimates using t distributions. (1, 3, 5)
19. Determine sample size to enable statistically significant decision making. (1, 3, 4, 5)
20. Make connections between confidence interval, sample size, and margin of error. (3, 4, 6)
21. Perform hypothesis testing appropriate to conditions. (1, 3, 5, 6)
22. Determine estimated regression equations, coefficients of determination, t, & F tests to predict future events,
evaluate statements, and to make/justify decisions in linear and multiple regression situations. (1, 3, 4, 5, 6)
23. Use the chi-square test for independence. (1, 3)
24. Use between treatments and within treatments estimates of response variable variance and the F test to assess
the equality of multiple population means. (1, 3, 4, 5, 6)
25. Create an ANOVA table. (3, 5, 6)
26. Create process control charts, use them to evaluate operating conditions, and make decisions concerning future
actions. (1, 3, 5, 6)
27. Determine an appropriate sampling plan taking producers risk and consumer risk into account. (4, 5, 6)
COURSE POLICIES:
Academic Honor:
College Policy:
Upon admission to HCC all students sign a pledge to uphold an honor system which holds the
qualities of honesty and integrity in highest regard for the duration of their educational experience.
Academic integrity violations and procedures are published in the Student Handbook and may be obtained in
the Student Activities Office.
Section Policy:
Academic dishonesty is nothing less than fraud and theft of educational opportunity. It will not be
tolerated under any circumstances. In every case, the severest penalty possible will be sought.
Attendance:
College Policy:
Students are expected to attend all classes. In the case of absence due to emergency, or participation
in Official College functions, it is the student's responsibility to confer with the instructor about the absence
and missed course work. Further, it is the student's responsibility to withdraw officially from any class,
which he or she ceases to attend. Failure to do so will result in the recording of an "F" grade.
Section Policy:
An absence will only be considered excused if it is promptly (prior to the conclusion of the scheduled
class) communicated to the instructor and deemed (by the instructor) to be a legitimate priority/emergency.
Assessment: (explanation of cases, homework, & exams)
1
Informal Case Presentation
1
Formal Case Presentation
12
Weekly Homework Assignments
4
Multi-Chapter Exams
25 Points
75 Points
120 Points
400 Points
620 Total Points
Informal Case:
Formal Case:
Weekly Homework:
Multi-Chapter Exams:
Grading:
Grades earned by students will be calculated as the percentage of possible point earned. Letter grades
are assigned as follows;
A
90 – 100%
558 – 620 points
B
80 – 89 %
496 – 557 points
C
70 – 79 %
434 – 495 points
D
60 – 69 %
372 – 433 points
F
< 60 %
≤ 371 points
Special Needs:
College Policy:
Students who have special needs are encouraged to identify themselves to the coordinator of special
student services as early as possible. Reasonable accommodations based on current documentation are
provided to qualified students.
Hagerstown Community College is committed to providing support services for students with
disabilities. Mr. Chris Baer is the advisor and contact person in The Office of Special Student Services. He
can be reached at 301-790-2800 ext. 575 or via e-mail at [email protected].
Section Policy:
It is the student’s responsibility to discuss and coordinate their accommodations with the instructor.
In the absence of official confirmation of approved accommodations, accommodations will not be provided.
THE INSTRUCTOR RESERVES THE RIGHT TO MODIFY THE COURSE POLICIES,
CONTENT, AND/OR THE STUDENT ASSESSMENT PROCEDURES AS HE DEEMS
NECESSARY.
TOPICAL OUTLINE:
A. Data & Statistics
1. Applications
2. Data Types
3. Data Sources
4. Descriptive Statistics
5. Statistical Inference
6. Statistical Analysis
B. Descriptive Statistics: Tabular & Graphical Methods
1. Summarizing Qualitative Data
2. Summarizing Quantitative Data
3. Stem & Leaf
4. Crosstabs & Scatter Diagrams
C. Descriptive Statistics: Numerical Methods
1. Measures of Location
2. Measures of Variability
3. Measures of Relative Location & Detecting Outliers
4. Exploratory Data Analysis
5. Weighted Mean & Grouped Data
D. Probability
1. Event Probabilities
2. Probability Relationships
3. Conditional Probability
E. Discrete Probability Distributions
1. Random Variables
2. Discrete Probability Distributions
3. Expected Value & Variance
F. Continuous Probability Distributions
1. Uniform Probability Distribution
2. Normal Probability Distribution
G. Sampling & Sampling Distributions
1. Simple Random Sampling
2. Point Estimation
3. Sampling Distributions
4. Sampling Methods
H. Interval Estimation
1. Interval Estimation of Population Mean – Large Sample
2. Interval Estimation of Population Mean – Small Sample
3. Determining Sample Size
4. Interval Estimation of a Population Proportion
I.
Hypothesis Testing
1. Developing Null and Alternative Hypotheses
2. Type I & II Errors
3. One-Tailed Tests About a Population Mean: Large-Sample
4. Two-Tailed Tests About a Population Mean: Large Sample
5. Tests About a Population Mean: Small Sample
6. Tests About a Population Proportion
J.
Simple Linear Regression
1. Simple Linear Regression Model
2. Least Squares Method
3. Coefficient of Determination
4. Testing of Significance
5. Regression Tools
K. Multiple Regression
1. Multiple Regression Model
2. Least Squares Method
3. Multiple Coefficient of Determination
4. Qualitative Independent Variables
5. Testing for Significance
L. Comparisons Involving Proportions
1. Independence Testing
M. Comparisons Involving Means
1. ANOVA
2. ANOVA – Testing for the Equality of k Population Means
N. Statistical Methods for Quality Control
1. Statistical Process Control
2. 6 – Sigma
3. Acceptance Sampling