NORTH CENTRAL TEXAS COLLEGE

COURSE SYLLABUS

 

 

COURSE AND INSTRUCTOR INFORMATION

 

 

Course title:  Elementary Statistical Methods

Course prefix, number, and section number:  MATH 1342.502

Semester/Year of course:  Spring 2022

Semester start and end dates: (16-wk) 1/18/2022 – 5/14/2022

Modality:  Face to Face

Class meeting location, days, and times: TR 8-9:20

 

Semester credit hours:  3 (Lecture hours: 48)

 

Course description:  Collection, analysis, presentation and interpretation of data, and probability. Analysis includes descriptive statistics, correlation and regression, confidence intervals and hypothesis testing. Use of appropriate technology is recommended.

 

Course prerequisites:  Meet TSI college-readiness standard for Elementary Statistics; or equivalent

 

Required course materials:  Fundamentals of Statistics: Informed Decisions Using Data 6^th edition, Michael Sullivan III, 2022, Pearson

MyLab Statistics (e-text included in MyLab Statistics)

TI-30X IIS or TI 83-84 calculator is required

NOTE: Phone calculators will not be allowed on exams.

 

Name of instructor: Cary Crawford

Office location: Flower Mound Campus Faculty Offices Room 107

Telephone number:

E-mail address: ccrawford@nctc

Office hours for students: Mon/Wed 12:30-2:00; Tue/Thu 11-12

 

STUDENT HOURS (OFFICE HOURS)

Each week instructors have time set aside to meet with students outside of class. (Traditionally these times have been called “office hours”.) This is a time when a student may ask questions regarding the class, or discuss a particular problem/topic with an instructor one-on-one.  Student hours may be held in-person or online.  See below for instructions on where/when/how instructors will offer student hours in this class.

 

Email me at ccrawford@nctc.edu to set up an appointment or come by my office during the
above listed times.

MATH TUTORING LAB

 

Students who need help with any math class can visit the NCTC Mathematics Lab to receive assistance.  There are math tutors available on every campus and online.  Sign up for an appointment or see the most current tutoring hours for all campuses at http://www.nctc.edu/student-services/student-success/tutoring/mathematics-lab.html

 

SYLLABUS CHANGE DISCLAIMER

 

 

The faculty member reserves the right to make changes to this published syllabus if it is in the best interest of the educational development of this class. Any such changes will be announced as soon as possible in person and/or writing.

 

 

SUMMARY OF COURSE ASSIGNMENTS

 

 

List of graded assignments: 

 

Section Title                                                                              *Due Date

1.1         Introduction to the Practice of Statistics                                            Jan 21

1.2         Observational Studies versus Designed Experiments                      Jan 23

1.3 - 1.4  Simple Random Sampling and other Sampling Techniques          Jan 26

2.1         Organizing Qualitative Data                                                                  Jan 28

2.2         Organizing Quantitative Data                                                               Jan 30

3.1         Measures of Central Tendency                                                            Feb 2

3.2         Measures of Dispersion                                                                        Feb 4

              EXCEL #1                                                                                                   Feb 6

              TEST 1                                                                                                       Feb 8

3.3         Measures of Central Tendency/Dispersion from Grouped Data    Feb 13

3.4         Measures of Position and Outliers                                                      Feb 16

3.5         The five number Summary and Boxplots                                           Feb 18

              EXCEL #2                                                                                                   Feb 20

4.1         Scatter Diagrams and Correlation                                                       Feb 23

4.2         Least Squares Regression                                                                     Feb 25

5.1         Probability Rules                                                                                     Feb 25

              EXCEL #3                                                                                                   Feb 27

5.2         The Addition Rule and Complements                                                 Feb 27

              TEST 2                                                                                                       Mar 3

EXCEL #4                                                                                                   Mar 6

5.3         Independence and the Multiplication Rule                                       Mar 9

5.4         Conditional Probability and the General Multiplication Rule              Mar 11

SPRING BREAK   SPRING BREAK                                                                          Mar 14-18

5.5         Counting Techniques                                                                             Mar 20

              EXCEL #5                                                                                                   Mar 20

5.7         Putting it All Together                                                                           Mar 23

6.1         Discrete Random Variables                                                                  Mar 25

6.2         The Binomial Probabliity Distribution                                                Mar 25

              EXCEL #6                                                                                                   Mar 27

              TEST 3                                                                                                       Mar 30

7.1         Properties of the Normal Distribution                                                Apr 6

7.2         Applications of the Normal Distribution                                            Apr 8

              EXCEL #7                                                                                                   Apr 10

8.1         Distribution of the Sample Mean                                                        Apr 13

8.2         Distribution of the population proportion                                        Apr 15

9.1         Estimating a Population Proportion                                                    Apr 17

9.2         Estimating a Population Mean                                                             Apr 20

10.1       Language of Hypothesis Testing                                                          Apr 22

              EXCEL #8                                                                                                   Apr 24

10.3       Hypothesis Testing for Population Mean                                           Apr 27

              Test 4                                                                                                        May 3

              FINAL EXAM                                                                                             May 10

                            

 

Homework: 10% of overall grade

Excel Assignments: 15% of overall grade

Exams: 75% of overall grade

The final exam may also be used to replace the lowest unit test grade.

 

 

Final grade scale:  90 – 100% = A;   80 – 89% = B; 70 – 79% = C;  60 – 69% = D;  Below 60% = F

 

Late work policy: Homework may be completed late for 20% off (regardless of how late it is).  Excel assignments will be counted off 10% per day it is late.

I will allow one make-up exam IF you notify me ahead of time.  If you do not notify me ahead of time, and you miss an exam, you will receive a zero (which may be replaced by the final exam grade)

 

SEE CANVAS FOR THE COMPLETE COURSE CALENDAR, OUTLINE, DETAILED DESCRIPTION OF GRADED WORK, AND OTHER RELATED MATERIAL.

 

 

COURSE POLICIES

 

Academic Integrity Policy:

Scholastic dishonesty shall include, but is not limited to cheating, plagiarism, academic falsification, intellectual property dishonesty, academic dishonesty facilitation, and collusion.  The use of online math solvers with submitted work is considered academic dishonesty.  Faculty members may document and bring charges against a student who is engaged in or is suspected to be engaged in academic dishonesty.  See Student Handbook, “Student Rights & Responsibilities: Student Code of Conduct ([FLB(LOCAL)]”.  

Consequences for academic dishonesty may include:

1. Zero on the assignment
2. Failing grade for the course

 

Attendance Policy:

Regular and punctual attendance is expected of all students in all classes for which they have registered. All absences are considered to be unauthorized unless the student is absent due to illness or emergencies. It is the student’s responsibility to provide documentation as to the emergency for approval by the faculty member. Approved college-sponsored activities are also excused absences. The instructor is responsible for judging the validity of any reason given for an absence. Valid reasons for absence, however, do not relieve the student of the responsibility for making up required work. Students will not be allowed to make up an examination missed due to absence unless the absence is documented and excused by the instructor. Student will be dropped from a class by the Registrar upon recommendation of the instructor who feels the student has been justifiably absent or tardy a sufficient number of times to preclude meeting the course’s objectives. Persistent, unjustified absences from classes or laboratories will be considered sufficient cause for College officials to drop a student from the rolls of the College. From Board Policy FC (LOCAL)

 

Withdrawal Policy

A student may withdraw from a course on or after the official date of record. It is the student’s responsibility to initiate and complete a Withdrawal Request Form.

 

Last day to withdraw from the course with a “W” is: (16-wk) Monday, April 4, 2022

 

Student Learning Outcomes:  At the successful completion of this course the student will be able to:

1. Explain the use of data collection and statistics as tools to reach reasonable conclusions.
2. Recognize, examine, and interpret the basic principles of describing and presenting data.
3. Compute and interpret empirical and theoretical probabilities using the rules of probabilities and combinatorics.
4. Explain the role of probability in statistics.
5. Examine, analyze, and compare various sampling distributions for both discrete and continuous random variables.
6. Describe and compute confidence intervals.
7. Solve linear regression and correlation problems.
8. Perform hypothesis testing using statistical methods.

 

Core Objectives:

X            Critical Thinking

X            Communication

X            Empirical and Quantitative

Teamwork

Personal Responsibility

Social Responsibility

 

COLLEGE POLICIES

 

STUDENT HANDBOOK

Students are expected to follow all rules and regulations found in the Student Handbook.

https://www.nctc.edu/_documents/academics/student-handbook.pdf

 

ADA STATEMENT

NCTC will adhere to all applicable federal, state and local laws, regulations and guidelines with respect to providing reasonable accommodations to afford equal educational opportunity. It is the student’s responsibility to contact the Office for Students with Disabilities to arrange appropriate accommodations.  See the OSD Syllabus Addendum.

STUDENT SERVICES

NCTC provides a multitude of services and resources to support students.  See the Student Services Syllabus Addendum for a listing of those departments and links to their sites.

 

 

QUESTIONS, CONCERNS, or COMPLAINTS