Spring 2015
Location: Dawson Weaver 37-A
Tuesday Evenings 6:00pm to 10:00pm
Mark Hobneck
mhobneck@ben.edu
PRE-ASSIGNMENT:
Read the first two chapters in the Charles H. Brase and Corrinne P. Brase textbook Understandable Statistics
prior to our first class meeting. Start compiling a notebook with key terms, definitions and statistical formulas.
PSYC 250 – Basic and Applied Statistics
I.
Course Description
Acquaints students with descriptive statistical techniques (including measures of central tendency and variability,
correlation, regression and large and small sample estimation) as well as inferential statistical procedures (t, z and
ANOVA designs, nonparametric tests and multiple regression). Focus will be on how these statistical procedures
can be directly applied to real-life situations. Prerequisite: MATH-S105 or S110. 3 Credit Hours
II.
TEXTBOOK AND MATERIALS
Understandable Statistics, Tenth Edition, by Charles H. Brase and Corrinne P. Brase; Houghton Mifflin Company;
Boston, New York. ISBN 978-0-8400-4838-7
Reference Textbook and Materials:
The text books listed below contain material that is relevant and beneficial as a supplement to the required text
book. The student does not need to purchase these books but can call upon them as for additional reference.
Basic Statistics using Excel ® for Office XP.
III.
MISSION STATEMENT
Benedictine University is dedicated to the education of undergraduate and graduate students from diverse ethnic,
racial and religious backgrounds. As an academic community committed to liberal arts and professional education
distinguished and guided by our Roman Catholic tradition and Benedictine heritage, we prepare our students for a
lifetime as active, informed and responsible citizens and leaders in the world community.
Course Philosophy:
The application of statistical tools in the real world requires the understanding of the basic concepts of data
gathering through identification of the population being studied, sampling techniques used to gather the data,
categorization of the data, distribution identification of the data, application and development of summary statistics,
inferences about the population and or sample identified, hypothesis development and testing, and finally
interpretation of the results.
Each of these steps is critical as they will guide you towards an acceptable interpretation and conclusion. Beside
developing and interpreting your own analysis of data you’ll need to understand how others arrive at their
conclusions through the process of statistical design and be able to interpret the result of others. Through a good
fundamental understanding of the components presented in this class the student should be able to determine
what constitutes a good study of scientific data and what does not.
Therefore it is the primary objective of this course to give students the basic understanding of how statistics are
used to further their understanding of behavioral applications where data is gathered and inferences are made on
that data.
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IV.
GOALS, OBJECTIVES, AND STUDENT LEARNING OUTCOMES
Upon successful completion of this course, each student will be able to perform the following:
A. Goals:
To develop an understanding, appreciation, and competency with the basic concepts of descriptive and
inferential statistics as they are used in the modern world in business and the natural and social
sciences.
B. Course Objective:



Use data gathered from other studies and determine whether the statistical analysis came from a
good design, or a poorly designed experiment.
Study how one can use statistical analysis to mislead or distort a conclusion.
Examine how probability, although uncertain in nature can be used to make predictions about future
events.
C. Student Learning Outcomes: Upon completion of the course:





Students will understand the terminology and basic concepts of inferential and descriptive statistics.
Students will understand the issues involved in the collection, presentation, and analysis of statistical
data.
Students will understand and be able to calculate measures of central tendency, variation, and position
for sets of statistical data.
Students will understand and be able to use rules of probability and probability distributions.
Students will understand the standard normal distribution, its properties, and its uses in calculating
probabilities,finding confidence intervals, and hypothesis testing.
V.
TEACHING METHODS/DELIVERY SYSTEM
Generally, the teaching method will primarily be in a lecture format. The beginning of each course will always start
with questions and answers about material we covered earlier, and we will always go over any questions regarding
homework or assignments that were assigned. However, other methods of content delivery will be applied, such
as how to use Microsoft Excel. Microsoft Excel will be used to perform the same calculations that you learned
manually in the classroom. Students will be responsible for learning how to use technology to perform calculations
and make decisions.
VI.
COURSE REQUIREMENTS
Attendance Policy
Attendance is mandatory and will be checked before each class. Since this class only meets ten nights, missing
one class constitutes missing a week of classes. Except for emergencies an absence of two weeks will lower your
grade one letter grade. Missing three classes will result in an “F” in the course. Missing two classes in a row may
also result in an “F” in the course.
This course is highly accelerated, and students will need to take a great deal of responsibility for their own learning
outcomes. Attendance is required in each class meeting for the full period of time. Any absence must be due to
extraordinary circumstances and will rquire documentation for it to be considered excused. Documentation must
be provided immediately in order to determine what, if any, accommodations are reasonable or possible. Class
attendance will directly impact your final grade, and each undocumented absence will be considered unexcused
and will result in a 20% reduction in the final grade for the course.
Due to theaccelerated nature of the course, should you experience a medical condition which prevents you from
attending any class(es), appropriate medical documentation must be provided immediately so it may be
determined what, if any, accommodations are reasonable or possible.
Benedictine University at Springfield Student Academic Honesty Policy
The search for truth and the dissemination of knowledge are the central missions of a university. Benedictine
University at Springfield pursues these missions in an environment guided by our Roman Catholic tradition and our
Benedictine heritage. Integrity and honesty are therefore expected of all University students. Actions such as
cheating, plagiarism, collusion, fabrication, forgery, falsification, destruction, multiple submission, solicitation, and
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misrepresentation are violations of these expectations and constitute unacceptable behavior in the University
community.
Student’s Responsibility
Though there is no formal honor code at Benedictine University at Springfield, students are expected to exhibit
academic honesty at all times. Violations against academic honesty are always serious and may result in
sanctions that could have profound long-term effects. The final responsibility for understanding the Academic
Honesty Policy of the institution, as well as the specific policies for individual courses normally found in syllabi,
rests with students. If any doubt exists about what constitutes academic dishonesty, students have the
responsibility to talk to the faculty member. Students should expect the members of their class to be academically
honest. If students believe one or more members of the class have been deceitful to gain academic advantage in
the class, students should feel comfortable to approach the faculty member of the course without prejudice.
Violations of the Academic Honesty Policy will be reported to the Office of the Dean of Academic Affairs. Along
with a verbal warning, the following are consequences a student may face for academic dishonesty:
 a failing grade or “zero” for the assignment;
 dismissal from and a failing grade for the course; or
 dismissal from the Institution.
VII.
Means of Evaluation
Homework checks, using technology problems, quizzes, chapter exams and a comprehensive final exam will be
used as the primary means of evaluation. Listed below are the details of each type of evaluation measures and
the weight that will be assigned to each means of evaluation. Students are encouraged to hand in material on
time. Late homework or assignments will only count for half of their original weight.
Quizzes 25%
There will be in class quizzes for every chapter covered in class. These quizzes will be short enough to be
completed in class and will cover the most important topics in each chapter.
Chapter Exams 35%
Make up exams will not be provided. Students are expected to take the hourly chapter exams on schedule. The
student will have one week to complete the chapter exams. Exams will consist of three chapters tested at the
same time.
Final Exam 40%
The final exam will be comprehensive and mandatory. This will be a classroom exam but students will be allowed
to use formula sheets and handouts and statistical tables will be handed out.
Grading Summary
Quizzes
Chapter Exams
Final Exam
25%
35%
40%
100%
Grading Scale
A = 100% - 90%
B = 89% - 80%
C = 79% - 70%
D = 69% - 60%
F = 59% - 0%
If a student believes that an error has been made in reporting a grade, an appeal must be made in writing to the
instructor and must be initiated within 60 calendar days after the end of the term for which the grade in question
was reported. The appeal should contain specific information about why it is believed the grade reported is
inaccurate. See the Student Handbook for additional details.
Add/Drop Dates
Please refer to the current Academic Calendar for add/drop dates.
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Incomplete Request
To qualify for an “I” grade, a minimum of 75% of the course work must be completed with a passing grade, and a
student must submit a completed Request for an Incomplete form to the Registrar’s Office. The form must be
completed by both student and instructor, but it is the student’s responsibility (not the instructor’s) to initiate this
process and obtain the necessary signatures.
Student Withdrawal Procedure
It is the student’s responsibility to officially withdraw from a course by completing the appropriate form, with
appropriate signatures, and returning the completed form to the Advising Office. Please refer to the Student
Handbook for important financial information related to withdrawals.
VIII.
IX.
Topical Course Outline
Topical Course Outline Updated (12/15/2014)
Pre-Class Assignment:
Read the first two chapters in the Charles H. Brase and Corrinne P. Brase textbook Understandable Statistics
prior to our first class meeting. Start compiling a notebook with key terms, definitions and statistical formulas.
Tuesday: March 17, 2015
Chapter 1: Getting Started.
Chapter 2: Organizing Data.
Assignments
Chapter 1: Getting Started
1.1
What is Statistics?
1.2
Random Samples
1.3
Introduction to Experimental Design
1, 3, 7 ,9
1, 3, 11, 15
1, 3, 5
Chapter 2:
2.1
Frequency Distributions and Histograms
2.2
Bar, Circle and Time Series Graphs
2.3
Stem-and-leaf displays
1, 3, 5, 11
5, 7, 9, 13, 15, 17
1, 5, 7
Tuesday: March 24, 2015
Quiz Chapters 3
Chapter 3: Averages and Variation.
Chapter 4: Elementary Probability Theory.
Assignments
Chapter 3: Averages and Variation.
3.1
Mode, Median, and Mean
3.2
Measures of Variation
3.3
Instructor’s Notes
Chapter 4: Elementary Probability Theory.
4.1
What is Probability
4.2
Probability Rules and Compound Events
4.3
Counting Techniques
1, 5, 9, 13, 17, 21
1, 3, 5, 9, 17
1, 7, 9, 13, 15
1, 5, 7, 9,11, 17, 19, 23
1, 7, 9, 13, 15, 17, 19, 21, 23, 25, 27, 29
Tuesday: March 31, 2015
Quiz Chapter 4
Exam Chapters 3 – 4
Chapter 4: Elementary Probability Theory.
Chapter 5: The Binomial Probability Distribution and Related Topics.
Assignments
Chapter 5:
5.1
Random Variables and Probability Distributions
1, 3, 5, 7, 9, 13, 15
4
5.2
5.3
5.4
Binomial Probabilities
Additional Binomial Probability Properties
Geometric and Poisson Distributions
1, 3, 5, 9, 11, 13, 23
1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21
1, 5, 9, 13, 17, 21, 23, 25, 27
Tuesday: April 7, 2015
Quiz Chapter 4
Chapter 5: The Binomial Probability Distribution and Related Topics.
Chapter 6: Normal Distributions.
Assignments
Chapter 6:
6.1
Graphs of Normal Probability Distributions
6.2
Areas Under the Standard Normal Distribution
31, 33, 35, 37, 39, 41, 43, 45, 47
6.3
Areas Under Any Normal Curve
6.4
Sampling Distributions
6.5
The Central Limit Theorem
6.6
Normal Approximation to Binominal Distribution
5, 7, 9, 11
3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29,
1, 5, 9, 13, 17, 21, 25, 29, 31, 33, 39
3, 7, 13, 15
5, 7, 9, 11
1, 3, 5, 7, 13, 15
Tuesday: April 14, 2015
Quiz Chapter 5
Chapter 6: Normal Distributions.
Chapter 7: Estimation.
Assignments
Chapter 7:
7.1
Estimating µ When σ is Known
7.2
Estimating µ When σ is Unknown
7.3
Estimating p in the Binomial Distribution
7.4
Estimating the difference in Means and Proportions
1, 5, 7, 9, 11
1, 3, 5, 7
1, 3, 7, 11, 15
1, 5, 9, 13, 17
Tuesday: April 21, 2015
Quiz Chapter 6
Exam Chapters 4 – 6
Chapter 7: Estimation.
Chapter 8: Hypothesis Testing.
Assignments
Chapter 8:
8.1
Introduction to Statistical Tests
5, 7, 9, 11, 13
8.2
Testing the Mean µ
1, 7, 15
8.3
Testing a Proportion p
1, 7, 11
8.4
Tests Involving Paired Differences (Dependent Samples) 1, 7
8.5
Testing Involving Independent Samples
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Tuesday: April 28, 2015
Quiz Chapter 7
Chapter 8: Hypothesis Testing.
Chapter 9: Correlation and Regression.
Assignments
Chapter 9: Correlation and Regression
9.1
Scatter Diagrams and Linear Correlation
9.2
Linear Regression and Coefficient of Determination
9.3
Inferences for Correlation and Regression
9.4
Multiple Regression
7, 13
1, 5, 15
1, 5
1, 7
5
Tuesday: May 5, 2015
Quiz Chapter 8
Exam Chapter 7 – 8
Chapter 9: Correlation and Regression.
Chapter 10: Chi-Square and F Distribution.
Assignments
Chapter 10: Chi-Square and F distribution
10.1
Chi-Square: Test of Independence and Homegeneity
10.2
Chi-Square: Goodness of Fit
10.3
Testing and Estimating a Single Variance
10.4
Testing Two Variances
10.5
One-Way ANOVA: Comparing Several Means
10.6
Introduction to Two-Way ANOVA
1
1, 5
1, 5
1, 5
1, 5
5
Tuesday: May 12, 2015
Chapter 11: Nonparametric Statistics
Assignments
Chapter 11: Nonparametric Statistics
11.1
The Sign Test for Matched Pairs
11.2
The Rank Sum Test
11.3
Spearman Rank correlation
11.4
Test for Randomness
5, 11, 13
13
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11
Final Exam Review Session
Tuesday: May 19, 2015
Exam Chapters 9 – 11
X.
Americans with Disabilities Act (ADA)
Benedictine University at Springfield provides individuals with disabilities reasonable accommodations to
participate in educational programs, activities, and services. Students with disabilities requiring accommodations
to participate in campus-sponsored programs, activities, and services, or to meet course requirements, should
contact the Resource Center as early as possible: springaccess@ben.edu or (217) 717-9253.
XI.
Assessment
Goals, objectives, and learning outcomes that will be assessed in the class are stated in this syllabus in Sections
IV and VI. Instructor will use background knowledge probes, one-minute papers, reflective essays and/or other
Classroom Assessment Techniques as deemed necessary in order to provide continuous improvement of
instruction.
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