This course introduces students to statistical methods used in professional careers. Students will learn to analyze, present, and interpret data sets using graphical and numerical methods. They will analyze large real-world data sets using statistical software. The course learning outcomes include analyzing and comparing data sets, using linear regression and hypothesis testing, and applying statistical concepts to modeling and inference. Students must complete a required project on simple regression analysis involving data collection, analysis, and presentation.
1. COLLEGE OF ARTS & SCIENCES
2012 - 2013
STAT220Introduction to Statistics
Credit Hours: 3
Contact Hours: 45
Prerequisite(s): MATH125
Co-requisite(s):
Cross-List:
Course Description
This course introduces students to statistical methods common to professional careers. Students
learn how to use the collection, analysis, presentation and interpretation of data. Students will
learn to use graphical and numerical methods to summarize data sets. Analysis of large, real-
world data sets will be performed using statistical software. Note: Online sections will have a
$75.00 book fee included with tuition charges.
Learning Outcomes
After successfully completing this course, the student will be able to:
1. Analyze a data set using graphic and numeric descriptive methods.
2. Compare data sets using appropriate graphic and numeric measures.
3. Use simple linear regression and correlation to study the relationship between two
quantitative variables.
4. Design, perform, and interpret the results of basic hypothesis tests.
5. Construct appropriate confidence intervals and interpret the results.
6. Use discrete and continuous probability distributions for modeling and inference.
7. Understand the effect of sampling size and technique on statistical inference.
8. Apply Minitab and other software as appropriate to the course content.
Required Textbooks and Additional Materials
978-0-321-50024-3
Elementary Statistics - With CD
Triola, Mario F.
11TH 10 / Addison-Wesley Longman, Inc.
2. DU Excellence System
The Davenport University Excellence System consists of nine learning outcomes that
demonstrate professional competencies necessary for graduates to engage in life-long learning
and succeed in their chosen profession. These learning outcomes are reinforced throughout the
curriculum of each academic program and are assessed at the course and program levels, where
appropriate. The Excellence System covers:
Global and Intercultural Competence
Civic and Social Responsibility
Ethical Reasoning and Action
Critical and Creative Thinking
Analysis and Problem Solving
Leadership and Teamwork
Information and Technology Proficiency.
Written Communication
Professional Communication
Academic Integrity
Davenport University recognizes the principles of honesty and truth as fundamental to ethical
business dealings and to a vibrant academic community of faculty and students. All members of
an academic community shall be confident that each person's work has been responsibly and
honorably acquired, developed and presented. The work that a student submits shall be a fair
representation of his/her ability, knowledge and skill. The University expects students to respect
and exhibit these principles as they form the basis of the quality of the institution and the quality
of Davenport’s graduates.
As stated in the Student Code of Conduct, the University may discipline a student for academic
dishonesty which is defined as any activity that tends to undermine the academic integrity of the
institution. Academic dishonesty includes, but is not limited to: cheating, fabrication, facilitating
academic dishonesty, interference, plagiarism, or violation of course rules. Definitions,
procedures, and sanctions for these violations may be found in the Student Code of Conduct.
A minor violation occurs the first time the student has a breach of academic integrity and
typically involves an assignment or activity that does not represent a significant part of the
course grade. For example, the student knowingly and intentionally cheats on a weekly
assignment; copies a source without proper citation; etc.
A major violation occurs as a first violation on an assignment or activity that is a significant part
of the course grade, such as an exam or major paper, or as the result of a second minor violation.
Students are expected to review the complete Academic Integrity policy in the University catalog
under Academic Policies and Procedures.
3. The University utilizes Turnitin.com plagiarism detection software. All papers will be submitted
to Turnitin.com where they will be compared against the entire Internet and against a database of
previously submitted student papers.
ADA Statement
Students with disabilities may request accommodations as provided within federal law. In order
for the University to adequately review each case, requests should be made to the Disability
Services Coordinator prior to the start of the semester. Requests made after the start of the
semester should be completed as early in the semester as possible to prevent delays in
accommodation. Students may contact their advisor or go to the Davenport University website
for the name of the Disability Services Coordinator for the location where they attend.
Military Assistance
Davenport University recognizes the extraordinary contributions of the members of our armed
services. Service members and their dependents should check the DU website for educational
benefits. Davenport University is committed to ensuring continuity of study for every active
service member who is prohibited from completing a semester as planned due to reassignment or
deployment. Service members should work with their DU military specialist prior to deployment
to ensure proper preparation and handling of DU financial records and academic coursework so
that academic re-integration is as seamless as possible upon return.
Student Responsibilities
Students are bound by all policies of Davenport University and should familiarize themselves
with these through reading the catalog and student handbook. Students should review the tuition
refund policy found on the DU website.
All students must complete the final assessment for the course, such as the final exam, project, or
presentation. Students who do not complete the final assessment will receive a grade of F.
Students are expected to be adequately prepared for each class session. It is reasonable to expect
at least two hours of outside study for every hour spent in the classroom.
Students are expected to assist in maintaining a classroom environment that is conducive to
learning. Free discussion, inquiry, and expression are encouraged. Behavior that interferes with
the instructor’s ability to conduct the class or the ability of students to benefit from that
instruction is not acceptable.
Alternative Delivery Statement
Alternative delivery formats require considerably more student time outside of class and
maintain the same level of assignments and academic rigor as the traditional classroom
format.“Blended inseat w/online” is an example of an alternative delivery format.
Scheduled Class Meeting Times
The state dictates minimal contact hour requirements that are rigidly upheld by the University.
Some of that instructional time is used for tests. The University's expectation is that classes will
meet for the entire assigned time.
4. Attendance Requirement
Regular attendance and active participation are essential elements in the learning process.
Therefore, Davenport has implemented a mandatory attendance policy effective Fall 2012 for
any 100- or lower level course.
For in-seat classes, attendance will be taken on a daily basis starting the first class meeting. An
absence is defined as missing more than one-half of a class period. Any unexcused absence will
start the process for administrative withdrawal from the course.
Attendance for online students will be defined as participating in at least one graded academic
activity each week. Postings not related to the graded discussion topics, emails, or other forms of
communication not related to the actual course assignments will be reviewed but may be
disqualified for attendance purposes.
A student requesting permission to be absent must notify the instructor within 24 hours of
missing the class. Failure to do so will initiate the withdrawal process, and merely notifying the
instructor does not guarantee that permission will be granted. For complete details and
ramifications, students are expected to read the full Attendance Policy available on the DU
website.
Standardized Grade Scale
The following grading scale is a University standard for courses in this area of study:
A 100 – 93 C+ 79 – 77
A- 92 – 90 C 76 – 73
B+ 89 – 87 C- 72 – 70
B 86 – 83 D+ 69 – 67
B- 82 – 80 D 66 – 63
F 62 – 0
5. STAT220 Required Assessment
Simple Regression Analysis Project (L.O. 1, 2, 6)
The Simple Regression Analysis Project is a required assignment for STAT220: Introduction to
Statistics. It represents 15% of the student’s course grade. The project requires that students not
only perform the statistical procedures but also discuss the implication of these procedures to the
underlying problem. Students demonstrate not just the mere mechanics of statistics, but an
understanding of the significance of statistical data. The project may be an individual or group
project.
DATA COLLECTION
One component of the Simple Regression Analysis Project involves data collection. Instructors
may allow students to use existing data sets or require students to gather data by developing a
survey that they create, on a topic of their choosing. Students may be encouraged to survey their
place of work, or choose a topic related to their majors, if possible. Instructors also have the
option of requiring that students obtain data from federal or state government websites, i.e.,
census or labor data.
The data set should have the following properties:
-The sample size should be at least 30 observations
-There are at least two quantitative variables to be used for the simple linear regression.
Additional quantitative variables can be gathered if the student wishes to investigate which
independent variable may be a better predictor of the dependent variable
DATA ANALYSIS
The Simple Regression Analysis Project requires students to perform each of the following:
Use histograms, box plots, dot plots, and descriptive statistics to study the center, variation,
distribution, outliers (if any), and trend (if applicable) for each of the quantitative variables
(students should decide not only whether the data are symmetric or skewed, but whether the data
are sufficiently symmetric to make the assumption of normality)
Carry out a scatter plot, correlation, and simple linear regression to examine whether evidence
of a relationship between two variables exists, how strong that relationship is, and whether the
regression equation should be used for predictive purposes
DATA SUMMARY AND PRESENTATION
As students complete their data analysis, they will also research previous studies on their topic.
Students will summarize the data results in a written report. In addition, they will present the
results to the class in an oral presentation.
Requirements of written report:
-Two to four pages of written text, not counting appropriate front and end matter, and graphics
-Typed, double-spaced with 12-point font, one inch margins
6. -Formatted according to the Publication Manual of the American Psychological Association
-Free from spelling, punctuation, or usage errors
Requirements of oral report:
Oral presentation of significant length (the length of the presentation will vary depending on
whether the report is an individual or group effort—generally, 3-5 minutes per student is
appropriate)
If the project was completed as a group effort, all members of the group must participate in the
oral report
Individual speakers are evaluated for overall cohesiveness and flow of the presentation
Appropriate visual aids, including computerized visual aids (i.e., Powerpoint), should be used in
the oral report
EVALUATION
The Simple Regression Analysis Project is worth 15% of the student’s course grade. An
instructor may divide those percentage points as he or she sees fit, according to different
components of the project. For example:
Simple Regression Analysis Project Total: 15% of course grade
Completeness of Statistical Analysis 2% of course grade
Correctness of Statistical Analysis 7% of course grade
Quality of Writing 3% of course grade
Oral report 3% of course grade