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SOUTHWESTERN MICHIGAN COLLEGE
SCHOOL OF ARTS AND SCIENCES
Dowagiac, Michigan
COURSE SYLLABUS
FALL Semester 2013
COURSE TITLE:
CREDITS/CONTACTS:
FINAL EXAM
INFORMATION:
COURSE NO.:
SECTION
NO.:
STATISTICS
Credit Hours:
Lecture hours/weekly:
Laboratory hours/weekly:
Weekly Contact Hours:
MATH 150
1323
4
4
0
4
Thursday, December 12
INSTRUCTOR:
Andrew Dohm, 713E Daugherty, (269) 782-1255, [email protected]
OFFICE
HOURS:
M W = 10:20 – 11:20 am, T TH F = 12:40 – 1:40 pm
PREREQUISITE:
Minimum grade of C in MATH 101 or MATH 102 and READ 100 or
satisfactory test scores.
COURSE DESCRIPTION:
Introduces the central ideas and the application of statistical inference.
Surveys graphic presentation, frequency distributions, sampling and
probability, regression and correlation, interval estimation, hypothesis testing,
and goodness of fit.
DEPARTMENT CHAIR:
Dr. Keith Howell, 713C Daugherty, (269) 782-1250, [email protected]
COURSE OUTCOMES:
See Page #3
TEXTBOOK:
REQUIRED:
ADDITIONAL REQUIRED
RESOURCES:
Elementary Statistics, 12th Edition
by Mario Triola
MyStatLab Access Code
Scientific Calculator
ATTENDANCE POLICY:
Regular on-time attendance in this course is expected. Many things happen
during class time that adds to your educational experience. If you are absent,
you are still responsible for the work assigned for that day and any other
information covered that day. If you do miss class, I assume you have a good
reason for being gone. I do not need a doctor’s note or other documentation
letting me know why you were absent. If a major emergency arises, let me
know.
TESTING POLICY:
There will be no makeup tests without prior approval. If you miss a test and I
do not hear from you by the end of that day, you will receive a zero for that
test. All tests will be taken in class and are timed. If you feel that you need
extra time or accommodations you must make arrangements through Special
Populations.
FEEDBACK POLICY:
In most cases, you can expect graded assignments and assessments to be
returned the next class period following their submission.
1
METHOD OF INSTRUCTION:
Interactive demonstrations, cooperative groups, discussions.
EVALUATION METHOD:
MyStatLab
Projects
Discussion Posts
Tests (5)
Comprehensive Final Exam
GRADING SCALE:
The following grading scale will be in effect for this course:
30%
20%
5%
25%
20%
A
93.4-100%
C
73.4-76.7%
A-
90-93.3%
C-
70-73.3%
B+
86.8-89.9%
D+
66.8-69.9%
B
83.4-86.7%
D
63.4-66.7%
B-
80-83.3%
D-
60-63.3%
C+
76.8-79.9%
F
0-59.9%
To satisfy Core Curriculum requirements, students must earn a grade of “C”
or higher in this class.
CLASSROOM BEHAVIOR:
Students are expected to assist in maintaining a classroom environment that is
conducive to learning. In order to assure that all students have the
opportunity to gain from time spent in class; students are prohibited from
engaging in any form of distraction. Inappropriate behavior in the classroom
shall result, minimally, in a request to leave class.
ACCEPTABLE USE OF
PERSONAL
COMMUNICATION
TECHNOLOGY:
All cell phones, laptops, and other technological devices not required for class
must be turned off and may not be brought out during class. Your instructor
will make every effort to identify devices, software, and necessary protocols
for usage throughout the course. In all cases, utilizing devices that detract
from a productive classroom experience is unacceptable and will not be
permitted. If you are expecting an urgent call, please alert the instructor at the
beginning of class and exit the classroom prior to answering. If you are found
to be in violation of these policies, you may be asked to leave during that
class session; multiple violations may be referred to the appropriate Dean for
disciplinary action. Your instructor has the right to modify this policy to meet
the needs of the course.
HONESTY POLICY:
Cheating or plagiarizing will absolutely not be tolerated at Southwestern
Michigan College. Any student found cheating or plagiarizing material in any
manner may be assigned a failing semester/session grade in this course. A
second such incident while at SMC could result in suspension or expulsion
from the institution. A student found in violation of this section of the
syllabus will not be allowed to drop this course. Additional detail regarding
cheating and/or plagiarism may be found elsewhere in this syllabus. For more
detailed information consult the SMC Code of Student Conduct.
NOTICE:
Representative student work will be used as a part of SMC’s on-going
curriculum assessment program.
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COURSE GOALS &
OUTCOMES:
*Goals for students in an introductory statistics course
Students should believe and understand why:
 Data beat anecdotes.
 Variability is natural, predictable, and quantifiable.
 Random sampling allows results of surveys and experiments to
be extended to the population from which the sample was taken.
 Random assignment in comparative experiments allows causeand-effect conclusions to be drawn.
 Association is not causation.
 Statistical significance does not necessarily imply practical
importance, especially for studies with large sample sizes.
 Finding no statistically significant difference or relationship does
not necessarily mean there is no difference or no relationship in
the population, especially for studies with small sample size.
Students should recognize:
 Common sources of bias in surveys and experiments.
 How to determine the population to which the results of
statistical inference can be extended, if any, based on how the
data were collected.
 How to determine when a cause-and-effect inference can be
drawn from an association based on how the data were collected
(e.g., the design of the study).
 That words such as “normal," “random,” and “correlation” have
specific meanings in statistics that may differ from common
usage.
Students should understand the parts of the process through which statistics
works to answer questions, namely:
 How to obtain or generate data.
 How to graph the data as a first step in analyzing data, and how
to know when that’s enough to answer the question of interest.
 How to interpret numerical summaries and graphical displays of
data—both to answer questions and to check conditions (to use
statistical procedures correctly).
 How to make appropriate use of statistical inference.
 How to communicate the results of a statistical analysis.
Students should understand the basic ideas of statistical inference, including:
 The concept of a sampling distribution and how it applies to
making statistical inferences based on samples of data (including
the idea of standard error).
 The concept of statistical significance, including significance
levels and p-values.
 The concept of confidence interval, including the interpretation
of confidence level and margin of error.
Finally, students should know:
 How to interpret statistical results in context.
 How to critique news stories and journal articles that include
statistical information, including identifying what’s missing in
the presentation and the flaws in the studies or methods used to
generate the information.
 When to call for help from a statistician.
*American Statistical Association. (2012). Guidelines for assessment and instruction in statistics
education: College report. 11-13.
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Learning Outcomes
Upon completion of each section, students should be able to:
1-2
1. Describe the difference between statistical significance and
practical significance.
2. Define voluntary response sample and determine that statistical
conclusions based on data from such a sample are generally not
valid.
1-3
1. Define parameter, statistic, quantitative data, categorical data.
2. Determine whether basic statistical calculations are appropriate for
a particular data set.
1-4
1. Define simple random sample.
2. Describe the importance of sound sampling methods and the
importance of good design of experiments.
2-2/3
2-4
3-2
3-3
3-4
4-2
4-3
4-4
5-2
1. Define frequency distribution and determine whether a potential
frequency distribution actually satisfies the necessary requirements.
2. Construct a histogram and make a conclusion about the nature of
a distribution by examining a histogram.
1. Construct a dotplot, stemplot, and scatterplot.
2. Determine that the scale used in a graph can distort the
impression created, and they should know that objects of area or
volume should not be used to depict values that are one-dimensional
in nature.
1. Measure the center of data by finding the mean, median, and
mode.
2. Determine whether an outlier has a substantial effect on the mean,
median, and mode.
1. Measure variation in a set of sample data by finding values of the
range, variance, and standard deviation.
2. Interpret values of the standard deviation by applying the range
rule of thumb to determine whether a particular value is unusual.
3. Interpret a value of a standard deviation by determining the
minimum usual value and maximum usual value.
1. Compute a z score and use the result to determine whether a given
value x is unusual.
2. Define percentiles and quartiles.
3. Construct a boxplot from a given set of sample data.
1. Identify probability values as values between 0 and 1.
2. Determine whether an event is unusual and/or unlikely, and they
should have developed the ability to calculate probabilities of events.
3. Describe the classical definition of probability by including the
statement that it requires equally likely outcomes.
4. Define the complement of an event and calculate the probability
of that complement.
1. Calculate the probability that in a single trial, some event A
occurs or some event B occurs or they both occur.
2. Apply the addition rule by correctly adjusting for events that are
not disjoint.
1. Calculate the probability of an event A occurring in a first trial
and an event B occurring in a second trial.
2. Apply the multiplication rule by adjusting for events that are not
independent.
3. Distinguish between independent events and dependent events.
1. Define random variable and probability distribution.
2. Determine when a potential probability distribution actually
satisfies the necessary requirements.
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5-3
5-4
6-2
6-3
6-4
6-5
6-6
7-2
7-3
7-4
3. Compute the mean and standard deviation of a given probability
distribution then use those results to determine whether results are
unusual.
1. Describe a binomial probability distribution and find probability
values for a binomial distribution.
1. Compute the mean and standard deviation for a binomial
distribution then use those results to determine whether results are
unusual.
1. Describe a standard normal distribution.
2. Find the probability of some range of values in a standard normal
distribution.
3. Find z scores corresponding to regions under the curve
representing a standard normal distribution.
1. Describe a normal distribution.
2. Find the probability of some range of values in a normal
distribution.
3. Find x scores corresponding to regions under the curve
representing a normal distribution.
1. Describe a sampling distribution of a statistic, and determine
whether a statistic serves as a good estimator of the corresponding
population parameter.
1. Describe the central limit theorem.
2. 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.
3. Identify conditions for which it is appropriate to use a normal
distribution for the distribution of sample means.
1. Examine histograms, outliers, and normal quartile plots to
determine whether sample data appear to be from a distribution that
is approximately normal.
2. Examine a normal quartile plot and determine whether it depicts
data from a normal distribution.
1. Construct a confidence interval estimate of a population
proportion and interpret such confidence interval estimates.
2. Identify the requirements necessary for the procedure that is used,
and they should be able to determine whether those requirements are
satisfied.
3. Determine critical values that correspond to various levels of
confidence.
4. Determine the sample size necessary to estimate a population
proportion.
1. Construct a confidence interval estimate of a population mean and
interpret such confidence interval estimates.
2. Identify the requirements necessary for the procedure that is used,
and they should be able to determine whether those requirements are
satisfied.
3. Determine critical values that correspond to various levels of
confidence.
4. Determine the sample size necessary to estimate a population
mean.
1. Construct a confidence interval estimate of a population standard
deviation or variance and interpret such confidence interval
estimates.
2. Identify the requirements necessary for the procedure that is used,
and they should be able to determine whether those requirements are
satisfied.
3. Determine critical values that correspond to various levels of
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confidence.
8-2
8-3
8-4
8-5
10-2
10-3
10-5
10-6
1. Identify the null and alternative hypotheses when given some
claim about a population proportion, mean, standard deviation, or
variance.
2. Calculate a test statistic, determine critical values, P-values, and
state a final conclusion that addresses the original claim.
1. Conduct a formal hypothesis test of a claim made about a
population proportion. The procedure should include statements of
the null and alternative hypotheses, determination of the test statistic,
critical value(s) or P-value, conclusion of rejecting the null
hypothesis or failing to reject the null hypothesis, and a final
conclusion that addresses the original claim.
1. Conduct a formal hypothesis test of a claim made about a
population mean. The procedure should include statements of the
null and alternative hypotheses, determination of the test statistic,
critical value(s) or P-value, conclusion of rejecting the null
hypothesis or failing to reject the null hypothesis, and a final
conclusion that addresses the original claim.
1. Conduct a formal hypothesis test of a claim made 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 P-value,
conclusion of rejecting the null hypothesis or failing to reject the null
hypothesis, and a final conclusion that addresses the original claim.
1. 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.
1. Use paired sample data to determine the equation of the
regression line.
2. Find the best predicted value of a variable given some value of
another variable.
1. Interpret results from statistical software to determine whether a
multiple regression equation is suitable for making predictions.
2. Compare results from different combinations of predictor
variables and identify the combination of predictor variables that
results in the best multiple regression equation.
1. Use paired data to identify the linear, quadratic, logarithmic,
exponential, and power models. They should be able to determine
which model fits best.
11-3
1. Use categorical data summarized as frequencies in a table with a
least two rows and at least two columns to conduct a formal test of
independence between the row variable and column variable.
12-2
1. Conduct a hypothesis test of equality of three or more population
means by interpreting results from statistical software.
1. Apply the method of two-way analysis of variance to (1) test for
an interaction between two factors, (2) test for an effect from the row
factor, and (3) test for an effect from the column factor. The
hypothesis tests can be conducted by interpreting results from
technology, and the sample data are categorized into groups using
two factors.
12-3
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COURSE COMPONENTS:
MyStatLab
MyStatLab (MSL) is a text-specific, easily customizable online course that
integrates interactive multimedia instruction with textbook content. This
system provides a rich and flexible set of course materials, featuring freeresponse tutorial exercises for unlimited practice and mastery. You can also
use online tools such as video lectures, animations, and a multimedia textbook
to independently improve your understanding and performance.
PRE Assignments (MSL)
PRE assignments will be assigned for each chapter section in the curriculum.
The assignments consist of the following parts:
Video – brief discussion of the main idea(s) of the chapter section.
Power Point – slides that summarize the content of each section.
Animated Activities/Applets – many sections include activities that guide you
through important concepts using animated figures and graphics.
Reading Assessments – questions about the content of the section.
You will be required to view the media before being allowed to answer the
reading assessment questions. PRE assignments are due before we discuss
the material in class. This will ensure you have studied the content and will
be prepared to apply it during our class sessions. PRE assignments can be
completed after they are due with a 50% penalty per day on the work
submitted after the due date and time. These assignments are prerequisites for
the Problem Sets.
Problem Sets (MSL)
Every chapter section includes an end-of-section problem set.
End of Section Problems – selected problems designed to apply the concepts
learned in the section.
MSL provides many levels of assistance for these problems: etext, links to
Statdisk and StatCrunch, “Help me solve this”, and Student Solutions Manual.
Think of this as the practice that will strengthen your knowledge of the
material. Problem sets can be completed after they are due with a 25%
penalty per day on the work submitted after the due date and time.
Chapter Review Quizzes (MSL)
Each chapter will conclude with a quiz containing a few homework problems.
This will assess whether or not you have met the objectives of the chapter.
Weekly Discussion Posts (MSL)
There is a discussion board in MSL where you will be asked to post an
interested statistic you have researched. Each week has a theme covering
major topics like the economy, jobs, global warming/climate change, green
energy, education, health care, distracted driving, sports, etc. You will also be
required to comment on another student’s post. This is designed to give you
exposure to a wide array to statistical resources and information.
Statdisk
Statdisk is statistical software designed to accompany the textbook. You have
access to a Student Laboratory Manual and Workbook for Statdisk through
MSL. 3-5 activities will be assigned every chapter out of this manual. This
will give you exposure to using a piece of software to organize, display, and
interpret statistical data. Each Statdisk assignment will require the
submission of a written report through our Moodle course page.
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Unit Tests
Each unit (a unit typically consists of 2 or 3 chapters) concludes with an inclass written test.
Capstone Group Project
You will be asked to create a survey, administer the survey, collect results,
organize those results, run some statistics on the data, and present a summary
of your findings.
Comprehensive Final Exam
You will be given an outcomes referenced final exam at the end of the
semester.
CLASS PREPARATION:
1.
2.
3.
4.
5.
6.
Read the assigned textbook sections.
Study the definitions, graphics, and examples.
Watch the video for the section.
Review the PowerPoint for the section.
Explore the animated activities and applets.
Answer the reading assessment questions.
OTHER EXPECTATIONS AND
RESPONSIBILITIES:

Submit all assignments complete, according to the instructions, and on
time.
Attend and be prepared for class by completing all assigned reading and
PRE assignments in advance.
Actively participate in lectures, discussions, and activities.
All questions, perspectives, and opinions are important and valuable –
you are encouraged to share and discuss.
Ask for clarification when you don’t understand.
Complete all assigned homework during the week. Ask questions when
you incorrectly answer homework problems.
Never, never, never get behind.






COURSE RATIONALE:
Taking a course is like embarking on a journey. A journey filled with
explorations, trials, perseverance, and personal growth. This course might be
a little different from other courses you have taken. My goal is the have you
learn, not just earn a grade. I believe the best way to promote this is by using
active learning techniques. Active learning centers around you being actively
engaged in the learning process. Information that would typically be given in
lecture format has been off loaded as homework. Instead of lecturing, expect
to be involved in classroom activities that aim to increase your conceptual
understanding of the material and gauge your progress towards meeting the
course outcomes. I see myself as more of the coach that will guide you
through the learning process and motivate you to do well. I believe in
challenging my students to reach very high standards of performance and in
providing them with the resources they need to reach those standards. Expect
to gain more than just content knowledge is this course. Learning how to learn
is critical. The ability to seek out information, process it, organize it, and use
it will help you become a life-long learner. Things like creativity and
innovation, critical thinking and problem solving, communication and
collaboration, and information, media, and technology skills are also
important. Those skills are woven into our journey through this course.
NOTICE: Information in this syllabus was, to the best knowledge of the instructor, considered correct and complete
when distributed for use at the beginning of the semester. The instructor, however, reserves the right, acting within
the policies and procedures of Southwestern Michigan College, to make changes in course content or instructional
techniques.
8
COURSE OUTLINE & ASSIGNMENTS
DATE
9/3
TEXT
SECTIONS
1-1, 1-2
9/5
TOPICS

Introduction, Statistical and Critical
Thinking
1-3, 1-4


Types of Data
Collecting Sample Data
9/10
2-1, 2-2, 2-3, 24


Frequency Distribution and Histograms
Graphs that Enlighten and Deceive
9/12
3-2, 3-3
9/17
3-3, 3-4




Measures of Center
Measures of Variation
Measures of Variation
Measures of Relative Standing and
Boxplots
9/19
9/24
Ch. 1, 2, 3
4-1, 4-2, 4-3, 44
Review/TEST 1
 Basics of Probability and the Addition
Rule
 Multiplication Rule: Basics
9/26
5-1, 5-2, 5-3


Probability Distributions
Binomial Probability Distributions
10/1
5-4

Parameters for Binomial Probability
Distributions
10/3
10/8
Ch. 4, 5
6-1, 6-2, 6-3
Review/TEST 2
 The Standard Normal Distribution
 Applications of Normal Distributions
10/10
6-4, 6-5, 6-6



Sampling Distribution and Estimators
The Central Limit Theorem
Assessing Normality
10/15
7-1, 7-2, 7-3


Estimating a Population Proportion
Estimating a Population Mean
ASSIGNMENTS
Read the Syllabus, 1-2 PRE
1-2 HW
DP 1
1-3 PRE, 1-4 PRE
1-3 HW
1-4 HW
Ch. 1 Review Quiz
2-2 PRE, 2-3 PRE, 2-4 PRE
2-2 HW
2-3 HW
2-4 HW
SD: 2-1, 2-2, 2-5, 2-6, DUE:
Ch. 2 Review Quiz
DP 2
3-2 PRE, 3-3 PRE
3-2 HW
3-4 PRE
3-3 HW
3-4 HW
SD: 3-1, 3-2, 3-3, 3-4, DUE:
Ch. 3 Review Quiz
DP 3
4-2 PRE, 4-3 PRE, 4-4 PRE
4-2 HW
4-3 HW
4-4 HW
SD: 4-1, 4-2, 4-12, 4-13, DUE:
Ch. 4 Review Quiz
DP 4
5-2 PRE, 5-3 PRE
5-2 HW
5-3 HW
5-4 PRE
5-4
SD: 4-3, 4-8, 4-10, Tech Proj (p. 240),
DUE:
Ch. 5 Review Quiz
DP 5
6-2 PRE, 6-3 PRE
6-2 HW
6-3 HW
DP 6
6-4 PRE, 6-5 PRE, 6-6 PRE
6-4 HW
6-5 HW
6-6 HW
SD: 4-16, 6-3, 6-4, DUE:
Ch. 6 Review Quiz
7-2 PRE, 7-3 PRE
7-2 HW
SD: 7-5, 7-8, 7-14, 7-15, DUE:
DP 7
9
10/17
7-3, 7-4


10/22
10/24
Ch. 6, 7
8-1, 8-2, 8-3
10/29
8-3, 8-4
Review/TEST 3
 Basics of Hypothesis Testing
 Testing a Claim about a Proportion
 Testing a Claim about a Proportion
 Testing a Claim about a Mean
10/31
8-4, 8-5


11/5
11/7
11/12
Ch. 8
10-1, 10-2, 103
10-3, 10-5
Review/TEST 4
 Correlation
 Correlation and Regression
 Correlation and Regression
 Multiple Regression
11/14
10-6, 11-3


Nonlinear Regression
Contingency Tables
11/19
12-1, 12-2, 123


One Way ANOVA
Two Way ANOVA
11/21
11/26
12/3
12/5
Ch. 10, 11, 12
Review/TEST 5
Group Project Presentations
Group Project Presentations
Review for Comprehensive Final Exam
Estimating a Population Mean
Estimating a Population Standard
Deviation of Variance
Testing a Claim about a Mean
Testing a Claim about a Standard
Deviation or Variance
7-4 PRE
7-3 HW
7-4 HW
SD: 7-22, 7-23, 7-26, 7-28, DUE:
Ch. 7 Review Quiz
DP 8
8-2 PRE, 8-3 PRE
8-2 HW
8-4 PRE
8-3 HW
SD: 8-1, 8-5, 8-13, DUE:
DP 9
8-5 PRE
8-4 HW
8-5 HW
Ch. 8 Review Quiz
DP 10
10-2 PRE, 10-3 PRE
10-2 HW
10-5 PRE
10-3 HW
10-5 HW
SD: 10-3, 10-10, 10-11, 10-13, DUE:
DP 11
10-6 PRE, 11-3 PRE
10-6 HW
11-3 HW
SD: Internet Proj (CPI), DUE:
Ch. 10 Review Quiz
12-2 PRE, 12-3 PRE
12-2 HW
12-3 HW
SD: 12-1, 12-8, DUE:
DP 12
DP 13
PRE = Preliminary Assignment in MyStatLab, always due before that class STARTS!
HW = Section Homework in MyStatLab, check system for due dates.
SD = Statdisk Experiments from Student Lab Manual and Workbook.
DP = Discussion Post, see “Discussions” in MyStatLab.
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