NORTHEAST COLLEGE
Department of Mathematics
Introduction to Statistics
Math 1342
CRN: 14224
Professor:
HOMEPAGE:
EMAIL ADDRESS:
Elkhatib
http://learning.nec.hccs.edu/members/tleduc
Melkhatib55@gmail.com
Prerequisite
A student who enrolls in this course must have a passing grade in MATH-1314.
Course Description
This course is designed to be a beginning course and serve as a prerequisite for
further study in courses requiring knowledge of statistics. Principles of both
descriptive and inferential statistics are discussed, illustrated, and applied in
situations close to most of students’ experience. The mathematics involved
requires that students have a proficiency in algebra. This is a three credit hours
course.
Textbook: Ron Larson and Elizabeth Farber; Elementary Statistics: Picturing the
World; Pearson, Fifth Edition, 2012. ISBN-13: 9780321693624.
Course Goals
The student will:









Learn the nature and implication of basic principles of statistics and how
they play an important role in our daily lives.
Organize and summarize data and represent graphically the important
information contained in a data set.
Compute numerical quantities that measure the central tendency and
dispersion of a set of data.
Understand the basic properties of probability.
Determine probabilities using postulates, rules of probability and various
probability distribution tables.
Distinguish between discrete and continuous random variables.
Compute the mean and standard deviation of a probability distribution.
Test hypotheses by using the appropriate distribution and construct
confidence intervals about means, standard deviations, and proportions.
Study the sampling distribution of some useful statistics.




Learn a method for estimating some population parameters.
Understand and apply the basic concepts of statistical inference to the
decision making process.
Fit a least-squares line to a set of data and interpret the coefficient of
correlation.
Learn to use a statistical software package in assisting statistical
computations of measures of central tendency, comparison, and
variability, graphing, simulations, probability distributions, confidence
intervals, hypothesis testing, analysis of variance, and chi-square tests.
Grading
Your grade will be determined based upon the total points earned on
examinations. There is no provision for doing extra or outside work to improve
your grade.
The course average will be calculated as follows:
Major Exams (3 @ 18%) 54%
MyMathlab
12%
Final Exam
34%
Total
100%
The final course grade will be determined by the following scale:
A = 90.0% to 100%
B = 80.0% to 89.9%
C = 70.0% to 79.9%
D = 60.0% to 69.9%
F < 60.0%
Exams: There will be three major exams and a final exam during the semester.
All the exams are multiple choices and online (via MyMathlab). Make-up
exams will not be given in the course for any reasons. Only one MISSED major
exam will be substituted by the final exam grade. Missing a second exam will
result in an automatic zero.
Online Exam Policy
1) ONLY ONE ATTEMPT IS ALLOWDED.
2) YOU HAVE EXACTLY TWO AND HALF HOURS TO FINISH THE TEST.
3) NO EXCEPTION.
You should plan for plenty of time to take the test, when you start then you must
finish it, since you can't restart at all.
Test time is Eastern time (ET).
Begin of the semester you have to send me an acknowledge statement to show
that “you have read, understood, and accepted the online exam policy”.
EXAM SCHEDULE
Test Number
Date
Chapters covered
Exam 1
TBA
Chapters 1, 2, and 3
Exam 2
TBA
Chapters 4, 5, and partial 6
Exam 3
Partial chapter 6, Chapters 7, and 9
Final
Comprehensive
Notice: This is a tentative the date is subject to change.
ALL EXAMS are on MyMathLab.
Each exam is allowed two and half hours limit and ONLY ONE ATTEMPT.
Homework: All homework will be online via MyMathLab and assigned through
the calendar section. Homework contributes 12% of course grade, dateline is
assigned for every sections of homework. Student must observe the
homework dateline. It is essential that the student does the homework and
reads the assigned material properly in order to achieve a good grade.
MyMathLab: This course is computer oriented. All homework and exams are
posted in MyMathLab; therefore, students must use the MyMathLab program
to access the exams and homework. To register to MyMathlab program
students have to buy a MyMathLab package.
Warning: MyMathlab program is MANDATORY for this course; you will be
dropped out of this course if you have not registered to the MyMathlab .
Instruction to log-in the MyMathLab: Students should register to MyMathLab
at latest one week before the class starts to get familiar with it.
Students: Go to www.coursecompass.com
Click the Log in button for students, and enter the login name and
password you created during registration.
Above is the instruction to log in the MyMathLab. You also need the course ID
following.
Course ID:
Will be given at the first day of class
Course Name:
Math 1342 – Introduction to Statistics
Description:
This is a MyMathlab for student homework of class Math
1342, CRN: 14224; Summer 2 ,2014
Textbook ISBN:
9780321715418
Help Phone for MyMathLab: 1-800-677-6337. Mon-Sat 8:00 am-8:00 pm
ADA
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. Faculty is
authorized to provide only the accommodations requested by the Disability
Support Services Office.
For questions, contact Donna Price at 713-718-5165 or the Disability Counselor
at your college. Visit the ADA Web site at
http://www.hccs.edu/students/disability/index.htm
Faculty Handbook/Faculty Orientation is also available at
http://www.hccs.edu/students/disability/faculty.htm
Tuition Notice:
Students who repeat a course for a third or more times may soon face significant
tuition and fee increases at HCC and other Texas public colleges and
universities, please ask your instructor or counselor about opportunities for
tutoring or other assistance prior to considering course withdrawal or if you are
not receiving passing grades.
Academic dishonesty:
Cheating can result in dismissal from the entire Houston Community College.
Any student who cheats will be dropped from the course with a grade of ‘F”. Any
talking or referring to books or notes during a test will be considered cheating.
Course Outline
1. Introduction to Statistic
1.1. An Overview of Statistics
1.2. Data Classification
1.3. Data Collection and Experimental Design
2. Descriptive Statistics
2.1. Frequency Distributions and Their Graphs
2.2. More Graphs and Displays
2.3. Measures of Central Tendency
2.4. Measures of Variation
2.5. Measures of Position
Part Two. Probability & Probability Distributions
3. Probability
3.1. Basic Concepts of Probability and Counting
3.2. Conditional Probability and the Multiplication Rule
3.3. The Addition Rule
3.4. Additional Topics in Probability and Counting
4. Discrete Probability Distributions
4.1. Probability Distributions
4.2. Binomial Distributions
4.3. More Discrete Probability Distributions
5. Normal Probability Distributions
5.1. Introduction to Normal Distributions and the Standard Normal Distribution
5.2. Normal Distributions: Finding Probabilities
5.3. Normal Distributions: Finding Values
5.4. Sampling Distributions and the Central Limit Theorem
5.5. Normal Approximations to Binomial Distributions
Part Three. Statistical Inference
6. Confidence Intervals
6.1. Confidence Intervals for the Mean (Large Samples)
6.2. Confidence Intervals for the Mean (Small Samples)
6.3. Confidence Intervals for Population Proportions
6.4. Confidence Intervals for Variance and Standard Deviation
7. Hypothesis Testing with One Sample
7.1. Introduction to Hypothesis Testing
7.2. Hypothesis Testing for the Mean (Large Samples)
7.3. Hypothesis Testing for the Mean (Small Samples)
7.4. Hypothesis Testing for Proportions
7.5. Hypothesis Testing for Variance and Standard Deviation
Part Four. More Statistical Inference
9. Correlation and Regression
9.1 Correlation
9.2. Linear Regression
9.3. Measures of Regression and Prediction Intervals