SOUTHWEST COLLEGE –STAFFORD CAMPUS
Department of Mathematics
Statistic Course Syllabus
Math 1342, CRN #46458: MTWTHFs: 10:30AM –12:30PM SW Hub. 223
Summer II 2013
INSTRUCTOR
Ernest Nwachukwu
CONTACT PHONE #
EMAIL ADDRESS
(713) 718 7770
Ernest.Nwachukwu@hccs.edu
Attendance policy:
Students are expected to attend classes regularly. If some special situation arises, which
calls for your missing classes, then please keep me informed. If I am not notified and your
absences exceed 12.5% of the number of classes, you will be administratively withdrawn
immediately.
Tardiness (lateness to class) policy:
Every student is expected to be in class on time. If a student is late on the examination day,
the student will not be given extra time.
Withdrawal policy:
Any student who is contemplating withdrawing from the class is encouraged to do so on or
before the final day for withdrawal. The final day for withdrawal is on the HCC schedule.
If astudent withdraws after the final day for withdrawal, the student will get an “F”.
Home Work policy:
Assignments will be given every week but usually will not be collected. For a student to get
the best out of this class, it is very important that the student solves problems in the
textbook. If a student fails to do assignments, it is not likely that the student will pass the
examination.
Exam Policy:
Cheating is not allowed in the examination. If a student is caught cheating in an
examination, the student will lose all the marks for that examination. College policies on
cheating will be enforced. These are clearly outlined in the HCCS Student Handbook.
Make-up policy:
There will be no make-up of any test. An exception to this can be allowed if there is a case of
medical emergency and with a valid proof. There will be no make-up of the final
examination.
Grading policy:
Each of the first four examinations is worth 20%; and the final examination is worth 40%
of the final course grade. The final course grade (call it FCG) will be calculated using the
formula:FCG = Average of the best five grades (final counting double).
Letter grade will be assigned to the FCG.
Grade legend: 90% - 100% - A, 80% - 89% - B, 70% - 79% - C, 60% - 69% - D, below
60% - F.
Final Examination :
The final examination consists of 33 multiple-choice problems. The problems cover only
the material required in this course.
Catalog Description: MATH 1342 Statistics. Topics include histograms, probability, binomial
and normal distributions, and their applications, correlation and prediction, and tests of statistical
hypotheses. Prerequisite: MATH 1314 or its equivalent or an acceptable placement test score. 3
credit (lecture).
Prerequisites: MATH 1314 or its equivalent or an acceptable placement test score.
BEGINNING OF SEMESTER ADVISEMENT
Students are advised about the pre-requisites for the above class and how they are related to their
major and the next class to take in mathematics.
END OF SEMESTER ADVISEMENT
Students are advised on the future courses in mathematics and how they are related to their
majors. All questions were answered.
FINAL GRADE OF FX
Students who stop attending class and do not withdraw themselves prior to the
withdrawal deadline may either be dropped by their professor for excessive
absences or be assigned the final grade of “FX” at the end of the semester.
Students who stop attending classes will receive a grade of “FX”, compared to an
earned grade of “F” which is due to poor performance. Logging into a DE course
without active participation is seen as non-attending.
Please note that HCC will not disperse financial aid funding for students who
have never attended class. Students who receive financial aid but fail to attend
class will be reported to the Department of Education and may have to pay back
their aid. A grade of “FX” is treated exactly the same as a grade of “F” in terms of
GPA, probation, suspension, and satisfactory academic progress.
EGLS3 -- Evaluation for Greater Learning Student Survey System
At Houston Community College, professors believe that thoughtful student
feedback is necessary to improve teaching and learning. During a designated
time, you will be asked to answer a short online survey of research-based
questions related to instruction. The anonymous results of the survey will be
made available to your professors and division chairs for continual improvement
of instruction. Look for the survey as part of the Houston Community College
Student System online near the end of the term.
Course Intent: This course is intended for students primarily in health sciences and business
rather than math or science majors. It consists of concepts, ideas, and utilization using statistics
rather than a theory course.
Audience: This course is for students who require a statistics course as a prerequisite for further
study.
Course Objectives: Upon completion of this course, a student should be able to:
MATH 1342: Statistics
Student Learning Outcomes
1. Understand basic concepts and
vocabulary for probability and
statistics.
Course Objectives
1.1 Demonstrate knowledge of statistical
terms.
1.2 Understand the difference between
descriptive and inferential statistics.
1.3 Identify types of data, measurement
level of variables, and four basic
sampling techniques.
2. Organize, analyze, and utilize
2.1 Construct the relative frequency
appropriate methods to draw
table from a given set of ungroup
conclusions based on sample data
data.
by using tables, graphs, measures 2.2 Know and use the different graphs:
of central tendency, and measures
histogram, frequency polygon,
of dispersion.
Ogives, Pareto, and pie to present
data.
2.3 Compute the mean, median, mode,
midrange, range, variance, and
standard deviation.
2.4 Identify the various measures of
position such as percentiles, deciles,
and quartiles.
2.5 Find the total number of outcomes in
a sequence of events using tree
diagram and multiplication rule.
Student Learning Outcomes
3. Collect univariate and bivariate data,
interpret and communicate the results
using statistical analyses such as
confidence intervals, hypothesis tests,
and regression analysis.
4. Calculate probabilities for binomial and
normal probability distributions and find
specific values for binomial and normal
probabilities
Course Objectives
3.1 Understand the use of permutation and
combination rules.
3.2 Determine sample spaces and find the
probability of an event using classical
probability.
3.3 Find the probability of compound events
using addition and/or multiplication rules.
3.4 Find the conditional probability of an event
3.5 Construct a probability distribution for a
random variable
3.6 Find the mean, variance, and expected
value for a probability distribution function.
3.7 Find the mean, variance, and standard
deviation for binomial distribution.
3.8 Identify the properties of the normal
distribution.
3.9 Find a confidence interval for the mean
when s is known or n > 30.
3.10 Determine the minimum sample size for
finding a confidence interval for the mean.
3.11 Find a confidence interval for the mean
when s is unknown and n < 30.
3.12 Find a confidence interval for proportion.
3.13 Determine the minimum sample size for
finding a confidence interval for a proportion.
3.14 Find a confidence interval of variance and
standard deviation.
4.1 Find the exact probability for X successes in
n trial of a binomial experiment.
4.2 Find the area under the normal curve, given
various z values.
4.3 Find probabilities for a normally distributed
variable by transforming it into a standard
normal variable.
4.4 Find specific data values for given
percentages using the standard normal
distribution.
4.5 Apply the central limit theorem to solve
problems involving sample means.
4.6 Use the normal approximation to compute
probabilities for a binomial variable.
Student Learning Outcomes
1. Successfully perform testing of
hypotheses using Standard Normal
values and t–distribution values.
Course Objectives
5.1 Understand the definitions used in
hypothesis testing.
5.2 State null hypothesis and alternative
hypothesis.
5.3 Understand the terms: type I error and type II
error, test criteria, level of significance, test
statistic.
5.4 Find the critical values for the z-test, t-test,
and c-test.
5.5 Test hypothesis for means (large and small
sample), proportions, variance, and standard
deviation.
5.6 Draw scatter plot for a set of ordered pairs.
5.7 Compute the correlation coefficient and the
coefficient of determination.
5.8 Compute the equation of the regression line
by using the least square method.
5.9 Test a distribution for goodness of fit using
chi-square.
5.10 Test independence and homogeneity using
chi-square.
5.11 Use the one-way ANOVA technique to
determine if there is a significant difference
among three or more means.
5.12 Determine the difference in means using the
Scheffe’ or Tukey test if the null hypothesis is
rejected in the ANOVA.
Textbook: Elementary Statistics Picturing the World, 5th Edition. Ron Larson & Betsy
Farber. Publishers, Prentice Hall.
Course Outline:
Unit 1 – Introduction to Statistics
Sections: 1.1-1.3.
This unit begins with an introduction to Statistics. This includes An Overview of Statistics, Data
Classification, Data Collection and Experimental Design.
Unit 2 - Data Description
Sections: 2.1-2.5.
This unit begins with an introduction to central dispersion and position measures. Topics include
mean, median, mode, dispersion shapes, midrange, range, variance, standard deviation,
coe ff ici ent of var iati on, Chebyshe v’ s t heor em, z -scores, quartiles, and outliers.
Unit 3 – Probability and Counting Techniques
Sections: 3.1-3.5
This unit begins with an introduction to probability as a chance concept. The basic concepts of
probability are covered in the unit. These concepts include probability experiments, sample
spaces, the addition and multiplication rules, probabilities of complementary events, and
conditional probabilities. Topics include the tree diagrams, multiple rules, permutations, and
combinations.
Unit 4 - Probability Distributions
Sections: 4.1-4.2.
This unit begins with the concepts and applications of what is called a probability distribution.
Topics include: Mean and Variance of Binomial Distribution.
Unit 5 - Normal Probability Distribution
Sections: 5.1-5.5.
This unit begins with an introduction to Normal Distribution. Topics include properties of the
Normal Distribution, the Standard Normal Distribution, applications of the Normal Distribution,
the Central Limit Theorem, and Normal Approximation to the Binomial Distribution.
Unit 6 - Confidence Intervals and Sample Size
Sections: 6.1-6.4.
This unit begins with an introduction to Confidence Intervals. Topics include Confidence
intervals for the Mean (Large Samples)and Sample Size, Confidence Intervals for the Mean
(Small Samples), Confidence Intervals and sample size for Proportions and error of the estimate.
Confidence Intervals for Variance and Standard Deviations.
Unit 7 - Hypothesis Testing with One Sample
Sections: 7.1-7.4.
This unit begins with an introduction to the concepts involved in statistical hypothesis testing.
Topics include Hypothesis Testing for the Mean (Large Samples), Hypothesis Testing for the Mean
(Small Samples), Hypothesis Testing for Proportions.
Unit 8 – Correlation and Regression:
Sections: 9.1 – 9.2
This unit begins with an introduction to correlation. Topics include correlation, linear Regression.
Unit 9 – Chi-Square Tests
Sections: 10.1-10.2
This unit begins with an introduction to Goodness-of-Fit Test. Topics include Independence,
Resource Materials: Any student enrolled in Math 1342 at HCCS has access to the Academic
Support Center where they may get additional help in understanding the theory or in improving
their skills. The Center is staffed with mathematics faculty and student assistants, and offers
tutorial help, video tapes and computer-assisted drills. Also available is a student’s Solutions
manual which may be obtained from the bookstore.
Americans With Disabilities Act (ADA): Students with Disabilities: Any student with a
documented disability (e.g. physical, learning, psychiatric, vision, hearing, etc.) who needs to
arrange reasonable accommodations must contact the Disability Services Office at the respective
college at the beginning of each semester