Western New Mexico University
Course Syllabus
Math 321 Statistics (3 credits)
Fall Semester, 2009 – online
Instructor
Stanley P. Thompson
Email: (1) thompsons1@wnmu.edu
(2) stan@shellmonster.com
Course Web Page: http://www.wnmu.edu (Select the Blackboard link on
the lefthand side of the browser and use your Mustang Express email/password
to log into the Blackboard/VISTAT tool)
Instructor’s Personal Web Page: http://www.shellmonster.com. Information
on your instructor may be found here.
Telephone Number: (575) 8947485 (9 am to 5 pm MST, MF)
Preferred Contact: Please contact via email (1).
Class Location and Format:
This is an online, Internetbased course using WNMU’s Blackboard/VISTA
(Bb) tool.
Class Hours: N/A
Class Web Site:
The course website is located at http://www.wnmu.edu through Bb.
Course Description:
Analysis and collections of data; measures of central tendency; measures
of variability; standard error; standard scores; correlation predictive
indices; measures of reliability; practical applications in mathematics,
science, business, education and social sciences.
A first course in college statistics emphasizing a realworld approach
using Microsoft Excel®. Prerequisites: Math 111 (Intermediate Algebra),
or equivalent. (NMCCN MATH 2113).
Required Textbook:
Elementary Statistics Using EXCEL, 4th Ed., Mario R. Triola. (ISBN:0321564960)
Suggested Textbooks (Not required, but good information):
Student Solutions Manual. (ISBN:0321564979)
Excel Guide for Finite Mathematics and Applied Calculus, 2nd. Ed., Revathi
Narasimhan. (ISBN: 0618293604
Data Analysis with Microsoft EXCEL, Berk and Carey. (ISBN:0534407145)
Mathematical Modeling with Microsoft Excel, Neuwirth and Arganbright.
(ISBN:0534420850
Elementary Statistics, Johnson and Kuby. (ISBN:0534399150)
Mind of Statistics, Utts and Heckard. (ISBN:0534393055)
Required Software:
Since this is an online course, there are some minimum hardware and software
requirements to complete the course. For recommended operating system
requirements and web browser compatibility, see http://www.wnmu.edu/My
Online Courses.
For all browsers, JavaScript and cookies must be enabled. To use Chat
and Whiteboard, Java must also be enabled.
To complete this course, you will need the following software:
a. Microsoft Word, PowerPoint (you may download the Microsoft PowerPoint
Viewer from the ‘Student’s Textbook Page’) and Excel
(2000 or newer)
b. Adobe Acrobat Reader® (free download at http://adobe.com/products/acrobat/readstep2.html.)
c. WinZip® (download at http://winzip.com ) or similar product. This
is not required, but suggested.
d. Use of WNMU’s Bb tool (http://www.wnmu.edu.)
Textbooks and software may be purchased at the WNMU bookstore, in person
or online via : http://www.wnmu.edu.) Or you may purchase via other online
resources such as http://www.amazon.com or http://www.half.ebay.com.
Technical Support:
If you are having technical problems with Bb, you can contact free technical
support through one of the following ways:
a. Phone: (575) 5386046
b. EMail: webct@WNMU.edu
c. Web: http://www.wnmu.edu/My Online Courses
Any course content related questions should be directed to your assigned
instructor. Please refer to thompsons1@wnmu.edu.
Exit Competencies:
Upon completion of this course, the student will have proficiency in
the following:
a. How to use statistics to get information from data.
b. To use Microsoft Excel® to produce statistical results.
c. Summarize data using graphical techniques so that information can
be extracted.
d. Understand various numerical descriptive techniques, which allow the
statistical practitioner to be more precise in describing various characteristics
of a sample or population.
e. To develop probabilitybased tools that are at the basis of statistical
inference.
f. Expand the concepts and techniques of probability by understanding
random variables and probability distributions.
g. Describe continuous random variables and their distribution.
h. Discuss the basic concepts and techniques of sampling and several
different sampling plans.
i. Show how the sampling distribution provides a key to statistical inference.
j. How the concepts and foundations of estimation and hypothesis testing
allow one to make inferences about populations.
Course Expectations:
Students should expect to spend at least 9 hours per week on this course.
This includes readings, viewing course content, completing homework assignments,
posting to the discussion area, etc.
All announcements/changes/due dates will be posted on Bb: It is the student’s
responsibility to check their Bb account and course calendar for communications
and changes to the course several times a week. A grade of Failing (<50%)
will be given for assignments not completed by their due date. No late
assignments or quizzes will be accepted unless specifically authorized
by the instructor.
Exams: Your instructor will arrange for proctoring any closedbook exams.
Common locations include local libraries and Extended University branch
centers.
Course Outline:
Module 1:
Introduction to Statistics
Objective: Student should be able to define parameter, statistic, quantitative
data, qualitative (or categorical or attribute) data. Students should be able
to determine whether basic statistical calculations are appropriate for a particular
data set. Show proficiency in Microsoft Excel.
Reading: Ch. 1.1 – 1.3, 1.5
Assignment: Online participation, Install Excel Addins: Data Analysis; Data
Desk/XL (DDXLversion 2.2.1 for Office 2007). Homework problems: Sec 1.3: Types
of Data 1.3.15, ; Sec 1.5: Excel Project (page 45).
Module 2:
Introduction to Statistics (continued)
Objective: Students should be able to define voluntary response sample and
determine that statistical conclusions based on data from such a sample are
generally not valid. Students should better develop an ability to assess the
validity of graphs and other statistical results. Students should be able to
define random sample and simple random sample, and determine whether a particular
sample is a random sample and/or a simple random sample.
Reading: Ch. 1.4 – 1.5
Assignment: Homework problems: Sec 1.4: Critical Thinking 1.4.15; Sec 1.5:
Collecting Sample Data 1.5.15.
Module 3:
Summarizing and Graphing Data
Objective: Students should be able to define frequency distribution and determine
whether a potential frequency distribution actually satisfies the necessary
requirements. They should also develop the ability to construct a histogram
and make a conclusion about the nature of a distribution by examining a histogram.
Students will become aware that there are many different types of graphs being
used for depicting data, and some graphs are much more effective than others.
Reading: Ch. 2.1 – 2.4
Assignment: Homework problems: Sec 2.2: Frequency Distributions 2.2.15; Sec
2.3: Histograms 2.3.15; Sec 2.4: Statistical Graphics 2.4.15.
Module 4:
Statistics for Describing, Exploring, and Comparing Data
Objective: Students should have developed the ability to measure the center
of data by finding the mean, median, and mode. They should be able to determine
whether an outlier has a substantial effect on the mean, median and mode. They
should have developed the ability to measure variation in a set of sample data
by finding values of the range, variance, and standard deviation. They should
have developed the ability to interpret values of the standard deviation by
applying the range rule of thumb to determine whether a particular value is
unusual, and they should be able to interpret a value of a standard deviation
by determining the minimum usual value and maximum usual value.
Reading: Ch. 3.1 – 3.3
Assignment: Homework problems: Sec 3.2: Measures of Center 3.2.15; Sec 3.3:
Measures of Variation 3.3.15.
Module 5:
Statistics for Describing, Exploring, and Comparing Data (continued)
Objective: Students should have developed the ability to compute a zscore
and use the result to determine whether a given value x is unusual. They should
be able to define percentiles and quartiles. They should have developed the
abilities to describe and identify outliers, to construct a boxplot from a
given set of sample data, and describe the nature of the distribution by examining
the boxplot.
Reading: Ch. 3.4
Assignment: Homework problems: Sec 3.4: Measures of Relative Standing and Boxplots
3.4.15.
Module 6:
Correlation and Regression
Objective: Students should be able to use paired data to find the value of
the linear correlation coefficient r, and determine whether the result leads
to the conclusion that there is a linear correlation between two variables.
They should be able to use paired sample data to determine the equation of
the regression line. Also, they should have developed the ability to find the
best predicted value of a variable given some value of another variable.
Reading: Ch. 10.1 – 10.3
Assignment: Homework problems: Sec 10.2: Correlation 10.2.15; Sec 10.3: Regression
10.3.15.
Module 7:
Probability
Objective: Students should identify probability values as values between 0
and 1. they should determine whether an event is unusual by assessing the probability
value, and they should have developed the ability to calculate probabilities
of events. They should be able to describe the classical definition of probability
by including the statement that it requires equally likely outcomes. They should
be able to define the complement of an event and calculate the probability
of that complement. They should have developed the ability to calculate the
probability that in a single trail, some event A occurs or some event B occurs
or they both occur. Students should be able to apply the addition rule by correctly
adjusting for events that are not disjoint. They should have developed the
ability to calculate the probability of an event A occurring in a first trail
and an event B occurring in a second trial. They should be able to apply the
multiplication rule by adjusting for events that are not independent. Finally,
the should be able to distinguish between independent events and dependent
events.
Reading: Ch. 4.1 – 4.4
Assignment: Homework problems: Sec Basic Concepts of Probability 4.2.15; Sec
4.3: Addition Rule 4.3.15; Sec 4.4: Multiplication Rule 4.4.15.
Module 8:
Midterm examination
Objective: To gauge student’s progress through the first half of the
semester.
Reading: None
Assignment: MidTerm Examination.
Module 9:
Discrete Probability Distributions
Objective: Students should be able to define random variable and probability
distribution. They should be able to determine when a potential probability
distribution actually satisfies the necessary requirements. Given a particular
probability distribution, students should be able to compute the mean and standard
deviation, then use those results to determine whether results are unusual.
Students should be able to describe a binomial probability distribution and
find probability values for a binomial distribution. They should have developed
the ability to compute the mean and standard deviation for a binomial distribution,
then use those results to determine whether results are unusual.
Reading: 5.1  5.4
Assignment: Homework problems: Sec 5.2: Random Variables 5.2.15; Sec 5.3:
Binomial Probability Distributions 5.3.15; Sec 5.4: Mean, Variance and Standard
Deviation for the Binomial Distribution 5.4.15.
Module 10:
Normal Probability Distributions
Objective: Students should have developed the ability to describe a standard
normal distribution. They should be able to find the probability of some range
of values in a standard normal distribution. They should be able to find zscores
corresponding to regions under the curve representing a standard normal distribution.
They should have developed the ability to describe a normal distribution. They
should be able to find the probability of some range of values in a normal
distribution. They should be able to find x scores corresponding to regions
under the curve representing a normal distribution.
Reading: Ch. 6.1 – 6.3
Assignment: Homework problems: Sec 6.2: The Standard Normal Distribution 6.2.15;
Sec 6.3: Applications of Normal Distributions 6.3.15.
Module 11:
Normal Probability Distributions (continued)
Objective: Students should have developed the ability to describe a sampling
distribution of a statistic, and determine whether a statistic serves as a
good estimator of the corresponding population parameter. Students should be
able to describe the central limit theorem. They should be able to apply the
central limit theorem by finding the probability that for some collection of
sample values, the sample mean falls within some specified range of values.
They should also be able to identify conditions for which it is appropriate
to use a normal distribution for the distribution of sample means.
Reading: Ch. 6.4 – 6.5
Assignment: Homework problems: Sec 6.4: Sampling Distributions and Estimators
6.4.15; Sec 6.5: 6.5.15.
Module 12:
Estimates and Sample Sizes
Objective: Students should be able to construct a confidence interval estimate
of a population proportion and interpret such confidence interval estimates.
Students should also be able to identify the requirements necessary for the
procedure that is used, and they should be able to determine whether those
requirements are satisfied. The should also be able to determine critical values
that correspond to various levels of confidence and be able to determine the
sample size necessary to estimate a population proportion. They should be able
to construct a confidence interval estimate of a population mean when given
sample data and a known value of a population standard deviation. They should
be able to interpret such confidence interval estimates and be able to identify
the requirements necessary for the procedure that is used, and they should
be able to determine whether those requirements are satisfied. Students should
also be able to determine critical values that correspond to various levels
of confidence. Lastly, they should be able to determine the sample size necessary
to estimate a population mean.
Reading: Ch. 7.1 – 7.3
Assignment: Homework problems: Sec 7.2: Estimating a Population Proportion
7.2.15; Sec 7.3: Estimating a Population Mean: Sigma Known 7.3.15.
Module 13:
Estimates and Sample Sizes (continued)
Objective: Students should be able to construct a confidence interval estimate
of a population mean. They should be able to interpret such confidence interval
estimate. They should also be able to identify the requirements necessary for
the procedure that is used, and they should be able to determine whether those
requirements are satisfied. Students should also be able to determine critical
values that correspond to various levels of confidence. They should be able
to construct a confidence interval estimate of a population standard deviation
or variance, and they should be able to interpret such confidence interval
estimates. Students should also be able to identify the requirements necessary
for the procedure that is used, and they should be able to determine whether
those requirements are satisfied. Students should also be able to determine
critical values that correspond to various levels of confidence.
Reading: Ch. 7.4 – 7.5
Assignment: Homework problems: Sec 7.4: Estimating a Population Mean: Sigma
Not Known 7.4.15; Sec 7.5: Estimating a Population Variance 7.5.15.
Module 14:
Hypothesis Testing
Objective: Students should be able to identify the null ad alternative hypotheses
when given some claim about a population proportion, mean, standard deviation,
or variance. They should be able to calculate a test statistic, determine critical
values, Pvalues, and state a final conclusion that addresses the original
claim.
Reading: Ch. 8.1  8.2
Assignment: Homework problems: Sec 8.2: Basics of Hypothesis Testing 8.2.110.
Module 15:
Thanksgiving Recess – No class
Module 16:
Hypothesis Testing (continued)
Objective: Students should be able to conduct a formal hypothesis test of a
claim made about a population proportion, a population mean, and about a population
standard deviation or variance. The procedure should include statements of
the null and alternative hypotheses, determination of the test statistic, critical
value(s) or Pvalue, conclusion of rejecting the null hypothesis or failing
to reject the null hypothesis, and a final conclusion that addresses the original
claim.
Reading: Ch. 8.3; 8.5 – 8.6
Assignment: Sec 8.3: Testing a Claim About a Proportion 8.3.15; Sec 8.5: Testing
a Claim About a Mean: Sigma Not Known 8.5.13; Sec 8.6: Testing a Claim About
a Standard Deviation or Variance 8.6.12.
Module 17:
Final Examination (details to be announced)
Assessment and Grading Criteria
This is an intensive, undergraduatelevel course with regular and firm deadlines.
Weekly Homework Assignments: You will be assigned homework each week, except
for the week of the midterm, Thanksgiving holiday and the final. Details on
the homework can be found under the assignments icon. Homework format will
normally utilize Microsoft Excel workbooks (sheets). Examples will be posted
on the Bb course for you to study. You must submit your module (week) assignments
by the end of each module (week) period to be considered for grading. Solutions
will be posted in Bb following the submission deadline. Normally, this will
be in the following module (week). Homework is worth 310 total points or 31%
of the final grade.
Weekly Discussion Topics: Discussions are, in essence, the equivalent of ‘class
participation’ in an online course. The instructor will begin facilitation
of these class discussions. Each discussion topic will last for oneweek. Discussions
start on Mondays and will end on the following Sunday. (You can find out the
start and end times for each discussion topic in the course calendar.)
Please log into the class and participate in the discussion at least four times
during the oneweek window. You are expected to participate in all of the discussion
topics presented during the semester.
Please take care in composing your discussion postings; the idea is to have
a conversation with the instructor and other students in the class, much as
you would in a facetoface class. (The discussion area should not be a series
of unrelated postings.) You are encouraged to share your ideas, ask questions,
and comment/respond appropriately to other students’ comments. The instructor
will evaluate your discussion postings in terms of both quality and quantity
as part of the course grade. The discussion postings are worth 140 points or
14% of the final grade.
During the first two weeks of the course you will have an opportunity to interact
casually with other students in the class to form virtual study groups. Students
in this class often find it is essential to pair up with other students in
the class to discuss module work. However, submitted homework assignments and
exams are expected to by your own work.
Please use the discussion area as your primary way of asking questions regarding
the class. Often other students will have the same questions, so it is a quicker
and more efficient way for you to get your questions answered.
If you need to contact the instructor with a personal problem or question,
you may use the email page of communications. This contact is only visible
to you and the instructor.
MidTerm Examination: You will have an openbook midterm examination for this
course. No collaboration is allowed. Please see the course calendar for the
module (week) of this exam. Further details will be announced prior to this
period using our Bb course. The midterm examination is worth 200 points or
20% of the final grade.
Final Examination: The final examination will also be an openbook examination
and will encompass the whole course. As with the midterm examination, no collaboration
is allowed. Further details will be announced prior to this period using our
Bb course. The weight of the final examination is 350 points or 35% of the
final grade.
Course Evaluation
You may be asked to complete a midterm and final course evaluation survey
online for this course. These surveys are completely anonymous and provide
useful information to improve this course for next semester’s students.
These surveys will be listed on the calendar and will appear in the quizzes
section of the course. If you have any questions or concerns about the survey,
please ask the instructor.
Course Policies
Academic Integrity: Each student is expected to maintain the highest standards
of honesty and integrity in academic and professional manners. The University
reserves the right to take disciplinary action, up to and including dismissal,
against any student who is found guilty of academic dishonesty or otherwise
fails to meet these standards.
Access to Education: Qualified students with disabilities needing appropriate
academic adjustments should contact the instructor as soon as possible to ensure
your needs are met in a timely manner. For information on assistive technology
available for student use and additional information on services available
through Student Accessibility Services, see http://www.wnmu.edu/Special%20Needs%202/specialneeds.htm.
Audit: A student may register for a course as an auditor, providing permission
of the instructor is obtained. A student has the first four weeks of the semester
to change a course to audit status. No changes in audit status will be processed
after the fourth week of class. Students are charged the normal tuition rate
for auditing a course.
Collaboration: Collaborate work, such as studying or discussing module assignments
and materials with other class members, is highly encouraged with the strict
understanding that any submitted homework and exams will be your work only.
Students are encouraged to collaborate with each other using the Bb email
discussion area tools.
Copyright: All materials in this course fall under copyright laws and should
not be downloaded, distributed, or used by students for any purposes outside
of this course.
Privacy and Bb Tracking Notice: Bb or the course web site automatically records
all students activities, including, your first and last access to the course,
the pages you have accessed, the number of discussion messages you have read
and sent, chat room discussion text, and posted discussion topics. This data
is accessed by the instructor to evaluate class participation and to identify
students having difficulty using Bb features.
Incompletes, Withdrawals, and Drops: I give out incompletes only under extreme
circumstances. If you are running into problems with the course, please contact
me as early as possible so you do not fall behind.
This course falls under all WNMU policies for last day to drop courses, etc.
please see http://www.wnmu.edu/student.htm or the WNMU Course Catalog for information
on WNMU services and policies. Please see the WNMU academic calendar for course
dates, the last day to drop courses without penalty, and for financial disenrollment
dates.
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