Download MAT 2030 JY01 J17SP Probability and Statistics

Johnson State College
External Degree Program
MAT-2030-JY01 Probability and Statistics
Syllabus – Spring 2017
Instructor: Stephen Gerard
90 Barrows Rd
Stowe, VT 05672
Faculty Contact information:
Email address: [email protected]
(802) 730-2448
Dates: Jan. 16 to April 30 (no class April 3 to 7)
Location: Online using Moodle (http://myjsc.jsc.edu)
ADA Statement: Students with disabilities who believe that they may need accommodations in
this class are encouraged to contact JSC’s Learning Specialist in Academic Services, as soon as
possible to ensure that accommodations, if needed, are implemented in a timely fashion. Please
call 802-635-1264 or email [email protected].
Academic Honesty: (from JSC Catalog) Students are expected to conform to the highest
standards of academic honesty in all of their academic work at Johnson State College. Academic
dishonesty in any form is prohibited and unacceptable. Acts of dishonesty for which a student
may be disciplined include, but are not limited to, receiving or providing unauthorized assistance
on an examination and plagiarizing the work of others in writing assignments. The American
Heritage Dictionary defines plagiarism in the following way: “To steal or use (the ideas or
writings of another) as one’s own.” Students are responsible for knowing what specific acts
constitute plagiarism; if students are uncertain as to whether a particular act constitutes
plagiarism, they should consult with their instructors before turning in assigned work.
Textbook:
There is no textbook for this course. All course materials will be available online.
Students must have regular access to Excel (MAC or PC, computer or cloud-based). Excel is
available through JSC at no cost to students. Instructions for obtaining it are on the course
introduction.
Course Description:
This course, an introduction to the basic ideas and techniques of probability and statistics, is designed
to prepare students to interpret quantitative information. Topics to be covered include descriptive
statistics, probability, probability distributions and the normal distribution, as well as correlation and
regression lines. There is an introduction to inferential statistics, including estimation and hypothesis
testing.
NOTE: This online course makes extensive use of Excel to do computation. Students should have at
least basic skills in Excel. The class will provide instruction in how to use Excel for statistical
computations, but students lacking basic Excel skills can easily get lost early in class.
Excel is available through JSC at no cost to students.
Course Objectives:
The successful student will be able to:
1. Outline the general development of statistical science and list a number of common
applications of statistical methodology.
2. Distinguish between descriptive and inferential statistics.
3. Create and apply various techniques used to describe data such as pie charts, bar graphs,
frequency tables and histograms.
4. Define three common measures of central tendency (mean, median, and mode), and
demonstrate the ability to calculate each manually from a series of small data sets.
5. Describe common methods of measuring variability, including range, percentiles,
variance, and standard deviation, and calculate each from a series of small data sets.
6. Explain the Normal Probability Distribution, techniques of sampling, the Central Limit
Theorem, and the concept of standard error, and compute probabilities associated with
normally distributed samples.
7. Test hypotheses about the value of the mean, assuming the normal distribution and large
sample results.
8. Select and perform common statistical tests, including one- and two-tailed tests.
9. Interpret and evaluate the validity of statistical data and reports.
10. Demonstrate proficiency in understanding, interpreting, evaluating and applying
quantitative data and information.
Methods:
This is an introduction to the use of probability and statistics to obtain, organize, summarize and
analyze large sets of data in order to interpret and draw conclusion from them. Students will
demonstrate competence with the basic tools, concepts and language of the field.
Since we are limited in what may be done by hand, this course uses Excel as a tool for doing the
basic processes. Students must have access to Excel 2013 or Excel for Mac 2011. These are available
to JSC students free. Students do not need to be highly fluent with Excel, but should understand the
basic functions and working of Excel.
Each week there will be an online written ‘lecture’ and one or more videos for the Excel application
of the material. Problems are provided with the answers provided to check understanding of the
material. There will be one or more forums for asking questions or discussing the material. There are
weekly online quizzes (paralleling the assigned problems) and assigned problems to be submitted.
Evaluation criteria:
There will be at least 10 quizzes worth about 60% of your final grade. In addition, there will be a
series of Excel exercises worth about 30-35% of your grade. Participation on the discussion board
will be worth 5-10%. The specific %s may vary, but that will be the general weighting of grades.
Instructor reserves the right to grade higher than a student’s specific percentage might indicate, but
the student will receive at least the grade associated with a given %.
Grading criteria:
Grade Points
A 90% – 100%
B 80% – 89%
C 70% – 79%
D 60% – 69%
F < 59%
Content Outline and reading Assignments:
Week Date
1
1/16
Content
Unit 1 - Organizing and Understanding Data
Getting to know Excel
2
1/23
Unit 2 - Summarizing and Graphing Data
Using Excel to graph distributions
3
1/30
Unit 3 - Describing, Exploring and Comparing Data
Excel for Descriptive statistics
4
2/6
Integrating descriptive statistics
Moving Averages & Correlation
5
2/13
Unit 4 - Introduction to Probability
6
2/20
Unit 5 - Discrete Probability Distributions
7
2/27
Unit 6 - The Normal Distribution
8
3/6
Developing skills with probability tools
9
3/13
Unit 7 Introduction to correlation and regression
10
3/20
Unit 8 Problem-solving with tools covered so far 8 - Sampling and Estimation
11
3/27
Unit 9 Sampling and Estimation
4/3
Break
12
4/10
Unit 10 - Hypothesis Testing
13
4/17
Unit 11 - Inferences from Two Samples
14
4/24
Final Exam