Applied Statistics
Math 332 – 01
3 sem. hrs.
Mon
11:00 – 11:50
Spring 2007
2:00-2:50 pm MWF
Room S304
Tue
11:00 – 11:50
1:00 – 1:50
Office Hours
Wed
11:00 - 11:50
Mr. Glen Just
Office S302 Ext. 2310
glen.just@ashford.edu
Thu
11:00 – 11:50
1:00 – 1:50
Fri
11:00 – 11:50
Ashford University Mission:
The mission of Ashford University is to provide accessible, affordable, innovative, high-quality learning
opportunities and degree programs that meet the diverse needs of individuals pursuing integrity in their lives,
professions, and communities.
Course Description:
This course covers tabulation and graphing techniques, measures of central tendency, measures of dispersion,
population and sample distributions, probability, central limit theorem, estimation, and parametric and nonparametric hypothesis testing. Students will use computer technology to analyze data, reach appropriate
conclusions and produce statistically valid projects. Prerequisite: Successful completion of the Mathematics,
Computer and Communication competencies.
Required Course Materials:
Textbook: Introductory Statistics, 7th ed., by Neil Weiss (Addison Wesley publ), bundled with student
version of Minitab statistical program. Computer: Students must possess a laptop with MS Office (at least
Word, Excel, Power Point), e-mail, web browser, and Minitab.
Course Design:
A. Instruction: Primary medium of instruction will be small group and class discussions. Students are
expected to read the material presented in the course text plus information from other sources. Students
are expected to understand and be able to explain the reasoning and theories behind statistical
procedures. Specific examples are presented in the course text that demonstrate the correct usage of
formulas and statistical techniques.
B. Assignments: Three case study problems will be assigned pertaining to the material covered in
course text. These case studies are worth 100 points each for the first two and 200 points for the third
one for a total of 400 possible points. Each case study must be completed by the specified due date in
the appropriate format (see evaluation rubric). Submitting an assignment that is not the work of the
individual student will result in a zero for the assignment. Subsequent attempts at plagiarism or any
other form of cheating will result in dismissal from the course and possible dismissal from the college
(see college catalog).
Math 332-Sect 1
Syllabus - Spring 2007
Page 2
C. Computer laboratory: In addition to the required coursework, a computer application lab will be
used for all students as part of the instruction and on an optional basis for enrichment. A statistical
program will be used to demonstrate the techniques and concepts learned in class. The program has the
capability of finding solutions to the assigned problems and will be used by the students to generate their
answers. The individual student is responsible for spending adequate computer time outside of the
normal class/lab sessions to learn the computer program. Student versions of the program are included
in the bundle with the course text when purchased through the university bookstore. Tutorials on using
the software are available through the Blackboard portal for this course.
Course Outcomes/Objectives: (assessments in parentheses).
A. Summarize statistical data numerically and graphically (discussions, projects).
B. Utilize probability in decision-making (discussions, projects).
C. Select and utilize appropriate parametric tests consistent with the type of data and the question to be
answered (discussions, projects).
D. Select and utilize appropriate non-parametric tests consistent with the type of data and the question
to be answered (discussions, projects).
E. Reach and defend conclusions using computer technology and a statistical software package
(projects).
Program Level Outcomes:
Mathematics Endorsement: This course meets the Iowa Department of Education “statistics” requirement for
teacher certification in elementary and secondary mathematics. Other Ashford University Programs: This
course meets the collateral specified requirements of statistics in the Accounting and Professional Accounting,
Business Administration degrees as well as the Liberal Arts degree with concentrations in Environment,
Science, Behavior and the Social Science degree with a concentration in Human Services. Assessment of
successful completion is made through the discussions and projects.
Institutional Outcomes: Graduates of Ashford University –
1.
2.
3.
4.
5.
6.
7.
8.
9.
Demonstrate the ability to read and think critically and creatively
Demonstrate the ability to communicate effectively in speech and writing.
Demonstrate the ability to communicate effectively through the use of technology
Demonstrate self-worth and respect the diversity in others
Understand the interdependence of life in all its forms
Demonstrate competence in their major fields of study
Share talents and resources in service to others
Are able to draw information from different fields of study to make informed decisions.
Recognize learning as a life long endeavor
Attendance Policy:
Each student is expected to attend the class regularly and contribute to the learning experience for all students
enrolled during class and through Blackboard discussions. Students are expected to ask questions, in class or
through Blackboard, on material that they do not understand and to actively offer answers to questions posed
during the class sessions and within the discussion board. There are no unexcused absences. In effect any
absence is considered excused, however, students who are not in class or do not meet regularly with their team
cannot participate and therefore their overall grade could suffer through their peer evaluations.
Math 332-Sect 1
Syllabus - Spring 2007
Page 3
Evaluation: Course grade will be determined by case studies and discussion questions.
A. Case study projects are prepared by teams typically consisting of four to six students. The MLA
formatted research papers are to be submitted using Blackboard no later than the date specified by the
instructor. Late assignments will only be accepted for full credit provided the instructor determines that
a valid reason existed for it being late. Otherwise, assignments will receive ten-percent lower credit for
each day it is late and assignments more than four days late will not be accepted. All written answers
must be in complete sentences. Assignments that do not meet the specified requirements will not
receive full credit. There will be 3 case studies for a total of 400 points. Each case study will be graded
using three evaluation rubrics (see evaluation rubrics below). One rubric will assess the written paper, a
second will assess the in class presentation and the third is a peer evaluation completed by the team
members. Turning in the work of another student as one's own or allowing your assignment to be copied
by another student is plagiarism and will result in a zero for the assignment. Subsequent attempts at
cheating or any kind will result in failure in the course and possible dismissal from the college (see
college catalog).
B. Discussion questions will be presented to the students at various times during the semester. These
questions might be presented during class, via email or on the Blackboard discussion page. Each student
is expected to thoughtfully respond to the discussion questions and the comments of other students. The
points awarded for the discussions will be determined by a combination of the number of postings, the
depth and range of the postings, and their uniqueness. The instructor will specify the point value of the
discussion question and the minimum postings to obtain a passing grade, e.g. at least three new postings
and at least two responses to other student postings. Students are expected to treat the comments made
by other students with respect and to use proper English when posting their comments. If a student does
not post his or her responses to the discussion question during the time it is available, he or she can
complete a 5 page MLA paper for each in-class discussion missed. The paper must be submitted within
48 hours of discussion and must contain at least three resources besides course text.
Grading scale: Final average will be obtained by dividing the total number of points accumulated by the student
by the number 5. Any student who does not participate in the final assessment activity (final case study) will
receive an automatic failure (school policy). The following grading scale will be used (the numbers
corresponding to the letter grades are given in percentages):
98 – 100 = A+
93 – 97 = A
90 – 92 = A-
Case studies
400
87 – 89 = B+
83 – 86 = B
80 – 82 = B-
Discussions
100
77 – 79 = C+
73 – 76 = C
70 – 72 = C-
----------------
-----
67 – 69 = D+
63 – 66 = D
60 – 62 = D-
Total
500
Below 60 = F
NOTE: Current University policy does not permit the recording of A+.
Math 332-Sect 1
Syllabus - Spring 2007
Page 4
Academic Integrity:
The academic community of the University believes that one of the goals of an institution of higher learning is to
strengthen academic integrity and responsibility among its members. To this end the University throughout its
history has emphasized the importance of sound judgment and a personal sense of responsibility in each student.
All members of the academic community are expected to abide by the highest standards of academic integrity.
Academic dishonesty is a serious offense at the University because it undermines the bonds of trust and personal
responsibility between and among students and faculty, weakens the credibility of the academic enterprise, and
defrauds those who believe in the value and integrity of the degree. Academic dishonesty may take several forms:
Cheating: Intentionally using or attempting to use unauthorized materials, information, or study aids in any
academic exercise (test, essay, etc.).
Fabrication: Intentional and unauthorized falsification or invention of any information or citation in an
academic exercise.
Facilitating academic dishonesty: Intentionally or knowingly helping or attempting to help another student
commit a breach of academic integrity.
Plagiarism: Representing the words or ideas of another as one’s own in any academic exercise.
A student who commits an act of academic dishonesty may face disciplinary action ranging from failure to
receive credit on an academic exercise to dismissal from the University. Procedures for implementing this policy
are listed in the student and faculty handbooks.
Accommodations:
In accordance with the Rehabilitation Act of 1973 and the Americans with Disabilities Act (ADA) of 1990,
Ashford University prohibits discrimination on the basis of a disability. Ashford University is committed to
providing an equal opportunity to access a full educational experience and reasonable accommodations will be
granted to students who qualify.
Students are responsible for disclosing disability information and requesting such accommodation through the
Campus Registrar, Sister Kathy Holland at 563-242-4153 x1261 or the University Registrar, Sheri Jones at 866974-5700 x2291or e-mail registrar@ashford.edu. Documentation for the disability must be provided annually
by a qualified health care professional. The determination of reasonable accommodation resides with the Office
of the University Registrar.
Math 332-Sect 1
Syllabus - Spring 2007
Page 5
Tentative Schedule of Classes
Notice: The topics indicated will be discussed in class on or near the dates indicated. This schedule for
the topics is tentative and may be altered as necessary during the semester. The related materials must
be read BEFORE the indicated class.
January
22
Introduction, Syllabus, Blackboard, 1.1 Two Kinds of Statistics
24
1.2 The Technology Center, 1.3 Simple Random Sampling,
26
1.4 Other Sampling Designs, 1.5 Experimental Design
29
2.1 Variables and Data, 2.2 Grouping Data,
31
2.3 Graphs and Charts, 2.4 Stem-and-Leaf Diagrams
February
02
2.5 Distribution Shapes, 2.6 Misleading Graphs
05
3.1 Measures of Center, 3.2 Sample Mean
07
3.3 Measure of Variation, 3.4 Five number Summary
09
3.5 Descriptive Measures, 4.1 Probability Basics
12
4.2 Events, 4.3 Rule of Probability, 4.4 Contingency Tables
14
4.5 Conditional Probability, 4.6 Multiplication Rule
16
4.7 Bayes' Rule, 4.8 Counting Rules
19
President’s Day – No Classes
21
5.1 Discrete Random Variables and Probability Distributions, 5.2 Mean and Standard Deviation
23
5.3 Binomial Distribution, 5.4 Poisson Distribution (opt. Hyper-Geometric distribution)
26
6.1 Normally Distributed Variables, 6.2 Areas Under the Standard Normal Curve
28
Presentations of case study 1
March
02
Presentations of case study 1 (continued)
05
6.3 Working with Normal Variables, 6.4 Assessing Normality
07
6.5 Normal Approximation to Binomial Distribution, 7.1 Sampling Error
09
7.2 Mean and Standard Deviation, 7.3 Sampling Distribution of the Mean
12
8.1 Estimating a Population Average, 8.2 Confidence Interval for  (known )
14
8.3 Margin of Error, 8.4 Confidence Interval for  (unknown )
16
9.1 Hypothesis Testing, 9.2 Terms, Errors, Hypotheses
19-23 Spring Break – No Classes
26
9.3 Test for Single Mean (known ), 9.4 Type II Error Probabilities (Power)
28
9.5 P-values, 9.6 Test for Single Mean (unknown )
30
9.7 Wilcoxon Signed Rank Test, 9.8 Which Procedure Should Be Used?
Math 332-Sect 1
Syllabus - Spring 2007
Page 6
April
02
10.1 Difference of Two Means (independent samples), 10.2 Inferences for Two Means (Independent
Samples, 1 = 2)
04
10.3 Inferences for Two Means (Independent Samples, 1  2), 10.4 Mann-Whitney Test
06
10.5 Inferences for Two Means (paired samples), 10.6 Paired Wilcoxon Signed Rank Test, 10.7 Which
Procedure Should Be Used?
09
11.1 Inferences for One Population Standard Deviation, 11.2 Inferences for Two Population Standard
Deviations
11
Presentations for case study 2
13
Presentations for case study 2 (continued)
16
12.1 Confidence Intervals for One Population Proportion, 12.2 Hypothesis Test for One Proportion, 12.3
Inferences for Two Proportions (independent samples)
18
13.1 Chi-Square Distribution, 13.2 Goodness of Fit
20
13.3 Contingency Tables, 13.4 Independence Test
23
14.1 Linear Equations with One Independent Variable, 14.2 Regression Equation
25
14.3 Coefficient of Determination, 14.4 Linear Correlation
27
15.1 Regression Model, 15.2 Analysis of Residuals, 15.3 Estimation and Prediction
30
15.4 Inferences in Correlation, 15.5 Tests for Normality
May
02
04
09
16.1 The F-Distribution, 16.2 One-Way ANOVA (Logic), 16.3 One-Way ANOVA (Procedure)
16.4 Multiple Comparisons, 16.5 Kruskal-Wallis Test
Presentations for case study 3 (1:00p to 3:00p)
Math 332-Sect 1
Syllabus - Spring 2007
Page 7
Statistics Research Paper Rubric
Group: _____________________________________
Members: ______________________________________________________________________
________________________________________________________________________________
Criteria
Introduction:
Overview – Topic identified
Problem(s) stated
Content:
Addressed the topic
Integrated appropriate research source(s)
Presented personal comments/observation/perspectives within context of topic
Accuracy and conclusions:
Reflected correct statistical methods
Summarized materials presented and made appropriate conclusion(s)
MLA Style: This paper must follow the current MLA guidelines:
No title Page
Body of Paper
Internal citations
Reference Page
Composition:
Outstanding-10 Clear, vivid writing. Paper speaks to topic in consistent and appropriate
voice, sharply focused, insightful, and persuasive, with an incisive, pleasing form. Very
carefully proofed and free of mechanical errors.
Very Good-8 Clear, logical writing. Vivid and persuasive. Thoughtful ideas coherently
presented; well-formed paper, carefully proofed with few mechanical errors.
Good-6 Simple, logical writing. Conventional in its details, thinking, and expression. Wellstructured paper, proofed yet errors are evident.
Poor – 4 Writing is not logical in places. Use of slang or inappropriate terminology.
Numerous spelling and grammar errors.
Unsatisfactory-2 Confused, unclear, wandering off topic. Fails to focus on topic.
Inappropriate voice. Not adequately proofed with substantial mechanical errors.
Graphics:
Related directly to the material presented
Clearly demonstrated relations, patterns, etc.
Reflected statistical statements and conclusions presented.
Color and labeling appropriate for aesthetics and clarity.
Total Points Possible
Max Pts
5
15
15
10
10
5
60
Earned
Math 332-Sect 1
Syllabus - Spring 2007
Page 8
(i)
Group Presentation Rubric
Topic: __________________________________ Date: _____________________________
Member names: ___________________________________________________________________________
___________________________________________________________________________
Team presentations are evaluated on the following aspects including audience engagement, instructional strategies, presentation style,
content, graphics, and teamwork. Each team member will be assessed individually (30 points).
Presentation
Component
NA
Excellent
5 Points
Good
3 Points
Acceptable
1 Point
Unacceptable
0 points
confident and fluent
introduction; clear
overview, but could be
more complete or
polished
well designed
handouts and
graphics, but too
much or too little, and
not on key points;
contact information
provided
introduction of
presenters, but
awkward – the
overview was sketchy
or unclear
handouts provided,
graphics were
present,
but were poor in
quality, inconsistent,
and not related;
inconsistent contact
information
fluent delivery, but
reading OR awkward
delivery but
spontaneous delivery;
use of terms, but not
well related, sporadic,
misused or
mispronounced
either thorough, but
biased, or incomplete
and slightly
unbalanced, poor
understanding of
overall material.
no introduction or
overview of topic
Overview:
introduction of
presenters and topic
confident introduction
of roles and
contribution; clear
purpose and overview
Handouts, visuals,
graphics,
references: attractive
& balanced layout,
legible fonts – follows
the principles of
design
well-designed
handouts, following
visual principles of
design that simplify or
summarize key ideas;
contact information
provided
Presentation style:
use effective verbal
and nonverbal
communication skills
(e.g., voice, volume,
inflection, eye contact,
vocabulary, etc.)
excellent verbal and
nonverbal style, good
projection with
inflection, spontaneous
speaking; fluent
vocabulary and
pronunciation without
pretension
thorough coverage of
topic per assignment
with balanced
treatment of
perspectives, balanced
contribution, good
understanding of
material.
generally good
delivery and
spontaneity but could
improve; good use of
terms but still uses
jargon or is awkward
with use of terms
prepared questions on
key areas, and
responsive to and elicit
participant reaction and
questions, equal
distribution of work.
prepared discussion
questions, reasonable
distribution of
workload.
discussion but without
clear organization
or purpose, some
disparity in work
distribution
little or no discussion,
unequal distribution of
work.
each team member
exhibited equal and
effective use of
equipment and
materials; attention to
set up and made ready
for next presentation
equipment was used
appropriately
unequal use of
equipment and
materials
– awkward
management of
equipment
little or no use of
equipment or
materials
Coverage and
accuracy: thorough
and balanced in
treatment of topic,
team members
demonstrate
understanding of the
material.
Discussion: team is
prepared to facilitate
class discussion,
stays within the
established time
frame, and is
receptive to feedback
Media utilization:
team exhibits fluency
in the use of AV
equipment and
materials.
Total:
generally thorough
and balanced, but
awkward, needs more
evidence, or better
sequencing,
clear roles, basic
understanding of
material.
no handout provided
(this includes
references), graphics
and visuals were not
related to topic; little
or no contact
information
poor style (long
pauses, reading
presentation,
“Umm…” and other
mannerisms, poor eye
contact, monotone,
etc.).
very incomplete,
significant gaps or
biased treatment of
topic, unclear of
implications of
findings, no
understanding of
material.
Points
Math 332-Sect 1
Syllabus - Spring 2007
Page 9
Statistics Research Project Peer Evaluation
(Based on group research, presentation, planning and delivery)



Use this form to evaluate each member of your team. Use this form to evaluate yourself
Honestly evaluate the degree to which each member reflects the stated concepts. For example place a checkmark
under (5) if you Strongly Agree that the individual meets the concept, (1) if you Strongly Disagree (e.g. the individual
does NOT meet the concept), etc.
You may provide written comments on the back of this form, especially in areas that receive low ratings.
Ratings will remain confidential.
Strongly
Agree
(5)
Agree
(4)
Neither
(3)
Disagree
(2)
Strongly
Disagree
(1)
Description
1. Devoted time to project
2. Took the project seriously
3. Researched the topic
4. Participated in face-to-face and electronic meetings
5. Did quality work
6. Cooperated with group; was a team player
7. Was dependable; met group deadlines/assignments
8. Generated ideas
9. Showed initiative
10. Contributed to learning experience
11. Brought integrity to the project
12. Encouraged participation of all members
13. Treated group members with respect
Add number of marks in each column and multiply that number by its value. For
example, 7 marks in “strongly agree” multiplied by 5 = 35.
Complete the calculation above for each column. Add all of the numbers from each column and write it here ________
Now divide the total by 13 and place the divided number here _______ (should be between 1 and 5 inclusively)
Points received for each team member (for this evaluation) will be divided by the number of team members. The final peer evaluation
score will be doubled (max = 10) and may be different for each team member.
Group member’s name:
_____________________________________________________
Evaluator’s name:
_____________________________________________________
IMPORTANT! These evaluations are due within 24 hours after your presentation.
If you fail to submit the evaluations on time, YOUR grade will be reduced.
Adapted from Group Personality and Performances, by S. L. Bichard, M. Roberts, and J. Sutherland.
Published in Journal of Advertising Education, Fall 2000.