KERN COMMUNITY COLLEGE DISTRICT – CERRO COSO COLLEGE

MATH C121H COURSE OUTLINE OF RECORD

1. DISCIPLINE AND COURSE NUMBER:

   MATH C121H

2. COURSE TITLE:

   Elementary Probability and Statistics - Honors

3. SHORT BANWEB TITLE:

   Elem Prob/Stats:Honors

4. COURSE AUTHOR:

   Bernsten, Dean

5. COURSE SEATS:

   -

6. COURSE TERMS:

   70 = Fall

7. CROSS-LISTED COURSES:

8. PROPOSAL TYPE:

   CC Course Revision

9. START TERM:

   30 = Spring, 2012

10. C-ID:

11. CATALOG COURSE DESCRIPTION:

    Elements of descriptive statistics, measures of central tendency, dispersion and presentation of data. Concepts of probability, random variables and normally distributed random variables. Sampling error, sampling processes and the distribution of sample means. Hypothesis testing of means and proportions for one and two populations. Linear regression, the least squares criterion, descriptive and inferential methods using linear regression. One and two way analysis of variance. The honors section provides more content and requires greater intensity and depth of study than the non-honors class.

12. GRADING METHOD

    Default:

    S = Standard Letter Grade

    Optional:

    A = Audit;P = Pass/No Pass

13. TOTAL UNITS:

    5

14. INSTRUCTIONAL METHODS / UNITS & HOURS:

    Method

    Min Units

    Min Hours

    Lecture

    5

    90

    Lab

    0

    0

    Activity

    0

    0

    Open Entry/Open Exit

    0

    0

    Volunteer Work Experience

    0

    0

    Paid Work Experience

    0

    0

    Non Standard

    0

    0

    Non-Standard Hours Justification:

15. REPEATABILITY

    Type:

    Non-Repeatable Credit

16. MATERIALS FEE:

    No

17. CREDIT BY EXAM:

    No

18. CORE MISSION APPLICABILITY:

    UC Transfer;Associate Degree Applicable (AA/AS);Certificate of Achievement (COA);CSU Transfer;Career Technical Education (CTE)

19. STAND-ALONE:

    No

20. PROGRAM APPLICABILITY

    Required:

    Elective:

    Business Administration (AA Degree Program)
    Business Administration AA (AA Degree Program)
    Computer Information Systems (AS Degree Program)
    Computer Information Systems AS (AS Degree Program)
    Computer Information Systems Associate of Science Degree (AS Degree Program)
    Computer Information Systems Associate of Science Degree (AS Degree Program)
    Computer Information Systems Cert (Certificate)
    Computer Information Systems- (Certificate of Achievement)
    General Education ()
    Liberal Arts: Mathematics & Science (AA Degree Program)
    Liberal Arts: Social & Behavioral Sciences (AA Degree Program)
    Liberal Arts: Social & Behavioral Sciences AA (AA Degree Program)
    Mathematics AA (AA Degree Program)
    

21. GENERAL EDUCATION APPLICABILITY

    Local:

    CC GE Area IV: Language and Rationality = Analytical Thinking;
    

    IGETC:

    IGETC Area 2: Math Concepts and Quantitative Reasoning = 2A: Mathematic;
    

    CSU:

    CSU GE Area B: Physical and its Life Forms(mark all that apply) = B4 - Mathematics/Quantitative Thinking;
    

    UC Transfer Course:

    CSU Transfer Course:

22. STUDENT LEARNING OUTCOMES Upon completion of the course, the student will be able to

    1. Demonstrate the limitations of statistical methods.
    2. Demonstrate basic literacy in the areas of probability and statistics.
    3. Demonstrate the ability to choose and apply appropriate statistical tech­niques to real world data problems.
    4. Demonstrate the ability to follow and evaluate a statistical line of reason­ing.
    5. Demonstrate an appreciation of the importance of inferential statistics to the evolution of twenty-first century thought.

23. REQUISITES

    Prerequisite:

    
    Acceptance for the honors program or eligibility for this honors course as determined in consultation with the instructor.
    
    MATH C055
    

24. DETAILED TOPICAL OUTLINE:

    Lecture:

    The Mathematics Department has adopted the following best practices for teaching this course:  offering or awarding extra-credit is forbidden, the allowance of multiple attempts at exams is forbidden, and an approved on-site proctor for online course exams is required.

    I. Introduction

     

    II. Organizing Data

    a. Grouping

    2. Graphing

     

    III. Descriptive Measures

    a. Measures of central tendency

    b. Measures of dispersion

    3. Population vs sample statistics

     

    IV. Probability

    a. Basic rules

    b. Conditional probability

    3. Independence

     

    V. Discrete Random Variables

    a. Basics

    2. Binomial coefficients and distribution

     

    VI. Normal Distribution

    a. Standard normal curve

    b. Normally distributed populations

    3. Normally distributed random variables

     

    7. Sampling Distribution of the Mean

     

    VIII Estimating Means and Proportions

    a. Estimating population means

    b. Confidence intervals

    c. Sample size

    4. Estimating population proportions

     

    IX. Hypothesis Testing: Means and Proportions

    a. Intro

    b. Z - test

    c. T - test

    4. Tests for population proportions

     

    X. Hypothesis Testing: Two Populations

    a. Two population means

    2. Two population proportions

     

    XI. Descriptive Methods in Linear Regression

    a. Review of linear equations

    b. The regression equation

    c. Coefficient of determination

    d. Linear correlation

    e. Regression

     

    XII. Analysis of Variance

    a. Introduction to Fisher's F-distribution

    b. One-way analysis of variance (ANOVA)

    c. Two-way analysis of variance

    4. Discussion two-factor procedures

     

    XIII. Tutorials, Seminars and Projects Specific to the Honors Section

    1. Discussion of current media releases dealing with statistical data

    2. Treatment of more advanced statistical tests and their applicability

    3. Demonstrations of several statistical software packages.

    4. Individual student projects exploring a particular facet of the subject followed by a defense of the paper to the group.

25. METHODS OF INSTRUCTION--Course instructional methods may include but are not limited to

    1. Case Study;
    2. Computational Work;
    3. Discussion;
    4. Lecture;
    5. Outside reading;
    6. Presentations (by students);
    7. Project-based learning;
    8. Written work;

26. OUT OF CLASS ASSIGNMENTS: Out of class assignments may include but are not limited to

    A. Daily homework assignments Example: Students work mathematics problems assigned from the text and from hand-outs to reinforce concepts and skills discussed in lecture. B. Online Course Management System Example: Assignments on Course Compass C. Term paper dealing with an approved statistical topic (honors only).

27. METHODS OF EVALUATION: Assessment of student performance may include but is not limited to

    A. Daily in-class assignments
    Example: Students work mathematics problems assigned from the text and from hand-outs to reinforce concepts and skills discussed in lecture.
    B. Weekly Quizzes
    Weekly quizzes over the previous week’s lecture material, homework, and in-class assignments assess the student’s understanding.
    C. Chapter Exams
    Chapter exams over the previous chapter’s lecture material, homework, and in-class assignments assess the student’s understanding.
    D. Term Paper
    Term paper on a subject mutually agreed upon by the student and instructor.
    

28. TEXTS, READINGS, AND MATERIALS: Instructional materials may include but are not limited to

    Textbooks

    Triola, M.. (2010) Elementary Statistics, 11th, Addison-Wesley Publishing Company
    

    Manuals

    Periodicals

    Software

    Other

29. METHOD OF DELIVERY:

    Online with some required face-to-face meetings (“Hybrid”);iTV – Interactive video = Face to face course with significant required activities in a distance modality ;Online course with on ground testing;Face to face;

30. MINIMUM QUALIFICATIONS:

    Chemistry (Masters Required);Engineering (Masters Required);Mathematics (Masters Required);Physics/Astronomy (Masters Required);

31. APPROVALS:

    Origination Date

    11/17/2011

    Last Outline Revision

    02/24/2012

    Curriculum Committee Approval

    02/24/2012

    Board of Trustees

    05/03/2012

    State Approval

    UC Approval

    70 = Fall 2001

    UC Approval Status

    Approved

    CSU Approval

    70 = Fall 2001

    CSU Approval Status

    Approved

    IGETC Approval

    70 = Fall 2001

    IGETC Approval Status

    Approved

    CSU GE Approval

    70 = Fall 2001

    CSU GE Approval Status

    Approved

• Data Element Changes

• Data Justification

• Course Element Changes

• Course Change Justification

• Course ID (CB00)

  CCC000355488

• TOP Code (CB03)

  1701.00 - Mathematics, General;

• Course Credit Status (CB04)

  D - Credit - Degree Applicable;

• Course Transfer Status (CB05)

  A = Transferable to both UC and CSU

• Course Units of Credit Maximum High (CB06):

  5

• Course Units of Credit Minimum Low (CB07):

  5

• Course Basic Skills (BS) Status (CB08):

  N = Course is not a basic skills course.

• SAM Code (CB09):

  E = Non-Occupational;

• Cooperative Education Course Status (CB10):

  Not part of Coop Work Exp;

• Course Classification Code (CB11):

  Liberal Arts and Sciences;

• Course Special Status (CB13):

  N - Not Special;

• CAN Code (CB14):

• CAN-Code Seq (CB15):

• Course Prior to College Level (CB21):

  Not Applicable;

• Course Non-Credit Category (CB22):

  Not Applicable, Credit Course;

• Funding Agency Category (CB23):

  Not Applicable

• Course Program Status (CB24):

  1 - Program Applicable;