Nathan M. Bisk College of Business
MGT 5006 Introductory Managerial Statistics, CRN 26310 (3 credits)
Spring 2019 Course Syllabus
Instructor: Dr. Leonard Howell
Meeting Times: Thursday, 5:00 p.m. – 8:00 p.m.
Class Location: Progress Center Building 7, Room 122
Required Textbook: Statistics for Managers using Microsoft Excel with MyStatLab Access Card Package, 8th Ed., Levine, Stephan, Szabat; Pearson/Prentice Hall. ISBN-10: 0134465970
This course addresses methods of collecting, analyzing and interpreting data for managerial decision-making. Includes data presentation, measures of central tendency, dispersion and skewness; fundamentals of probability; discrete and continuous probability distributions; sampling methods and sampling distributions; and confidence interval estimation of parameters and tests of hypotheses. . Microsoft Excel and the free statistical analysis package R/RStudio will be used extensively to analyze data sets and illustrate learning points.
This is an introduction to the techniques of collection, analysis, and interpretation of data that are useful for managerial decision making. Topics include: data presentation; measures of central tendency, dispersion, and correlation; fundamentals of probability; discrete and continuous probability distributions; sampling theory; and statistical inference. At the conclusion of this course, the student will be able to:
Midterm Exam: 35%
Final Exam: 35%
A conventional grading scale will be used (90-100=A, 80-89=B, 70-79=C, 60-69=D, <60=F). A grade of “I” (incomplete) may be assigned only if a student in a good standing (passing) has been officially excused due to hospitalization or serious sickness, or other extenuating circumstances beyond their control, in which case, any due materials must be completed in accordance with the FIT guidelines for removing an Incomplete (I) grade.
NOTE: first install R, then RStudio
Classes are conducted in-class. Students are expected to have access to a computer with internet connection to access course instructional materials and complete MyStatLab assignments. Students are expected to read the textbook and posted materials, participate in class discussions and should regularly log on CANVAS to check for new postings.
Assignments and Expectations:
Academic dishonesty includes, but is not limited to: plagiarism, collaborating with others on individual assignments or projects, viewing or copying another student’s solutions during exams, submitting completed coursework for more than one course (without consent of instructors), deliberate falsification of data, interference with other students' work, and copyright violations (including both document and software copyrights). Please familiarize yourself with the university policy on academic honesty. If at any time you have a question regarding integrity or plagiarism, ask the instructor for clarification.
Dishonest assignments (e.g., where plagiarism has occurred) will be dealt with under the University policy on Academic Misconduct. Access to this policy, including the factors that constitute a dishonest assignment is available at http://www.fit.edu/current/plagiarism.pdf. Students are encouraged to familiarize themselves with the definitions of academic misconduct.
Full and detailed acknowledgement (e.g. notation, and/or bibliography) must be provided if contributions are drawn from literature in preparation of reports and assignments. Student written work must properly cite and reference original work, author(s), etc. Citation and referencing must conform to either APA (American Psychological Association) or AMA (American Marketing Association) formats both in the body of your paper and the attached reference section.
The primary method of communication will be through the class e-mail on CANVAS. It is the student’s responsibility to stay current with all postings to the class web site on CANVAS. A hardcopy of homework solutions to textbook problems will be turned in at the beginning of class on their due date. MyStatLab homework assignments are done on-line and a hardcopy will not be submitted during class. Students unable to attend class can either have another student submit their homework for them or submit via email.
Computing, Information Retrieval, and Writing Expectations
What is Title IX?
Title IX of the Educational Amendments Act of 1972 is the federal law prohibiting discrimination based on sex under any education program and/or activity operated by an institution receiving and/or benefiting from federal financial assistance. Behaviors that can be considered “sexual discrimination” include sexual assault, sexual harassment, stalking, relationship abuse (dating violence and domestic violence), sexual misconduct, and gender discrimination. You are encouraged to report these behaviors.
Reporting: Florida Tech can better support students in trouble if we know about what is happening. Reporting also helps us to identify patterns that might arise – for example, if more than one complainant reports having been assaulted or harassed by the same individual.
Florida Tech is committed to providing a safe and positive learning experience. To report a violation of sexual misconduct or gender discrimination, please contact Linda Jancheson, Title IX Coordinator at 321-674-7277 or firstname.lastname@example.org.
This outline is subject to change, and additions may be made throughout the semester.
Week Text Material Topic
Week 1 Course Overview Slides available on CANVAS
Chapter 1 Defining and Collecting Data
Week 2, 3 Chapter 2 Visualizing Data
Week 4 Chapter 3 Numerical Descriptive Measures
Week 5 Chapter 4 Basic Probability
Week 6 Chapter 5 Discrete Probability Distributions
Week 7 Chapter 6 Normal Distribution, Other Continuous Dist.
Week 8 Midterm Exam Covers Chapters 1-5.
Week 9 Chapter 7 Sampling Distributions
Week 10, 11 Chapter 8 Confidence Interval Estimation
Week 12, 13 Chapter 9 Fundamentals of Hypothesis Testing:
One Sample Tests
Week 14 Review, Study Week
Week 15 Final Exam Covers Chapters 6 - 9.