12/22/2024 3:29:11 AM	MATH 15 Course Outline as of Fall 1999	Changed Course
CATALOG INFORMATION
Discipline and Nbr:  MATH 15	Title:  ELEM STAT COMPUTER
Full Title:  Elementary Statistics with Computer
Last Reviewed:10/28/2024

Units		Course Hours per Week			Nbr of Weeks	Course Hours Total
Maximum	4.00	Lecture Scheduled	4.00		17.5 max.	Lecture Scheduled	70.00
Minimum	4.00	Lab Scheduled	0		6 min.	Lab Scheduled	0
		Contact DHR	0			Contact DHR	0
		Contact Total	4.00			Contact Total	70.00
		Non-contact DHR	0			Non-contact DHR Total	0

Total Out of Class Hours:  140.00

Total Student Learning Hours: 210.00

Title 5 Category:  AA Degree Applicable
Grading:  Grade or P/NP
Repeatability:  05 - May Be Taken for a Total of 4 Units
Also Listed As: 
Formerly: 

Catalog Description:

Computer investigation, exploration and simulations of concepts in statistics, descriptive statistics, probability theory including the uniform, binomial, hypergeometric, Poisson, normal, chi-square and Student's t distributions, central limit theorem, estimation of population parameters from a sample, hypothesis testing including parametric and nonparametric methods, confidence intervals, correlation and linear regression, introduction to analysis of variance computer simulations and Monte Carlo methods.

Prerequisites/Corequisites:
Math 155.

Recommended Preparation:

Limits on Enrollment:

Schedule of Classes Information
Description:

Computer investigation, exploration and simulations of concepts in statistics: descriptive statistics, probability theory, central limit theorem, estimation, hypothesis (parametric & non-parametric), confidence intervals, correlation and linear regression, analysis of variance.

(Grade or P/NP)
Prerequisites:Math 155.
Recommended:
Limits on Enrollment:
Transfer Credit:CSU;UC.
Repeatability:05 - May Be Taken for a Total of 4 Units

ARTICULATION, MAJOR, and CERTIFICATION INFORMATION

Associate Degree:		Effective:	Fall 1981	Inactive:
Area:	B MC	Communication and Analytical Thinking Math Competency
CSU GE:	Transfer Area			Effective:	Inactive:
	B4	Math/Quantitative Reasoning		Fall 1990
IGETC:	Transfer Area			Effective:	Inactive:
	2A	Mathematical Concepts & Quantitative Reasoning		Fall 1993
CSU Transfer:	Transferable	Effective:	Fall 1989	Inactive:	Fall 2025
UC Transfer:	Transferable	Effective:	Fall 1989	Inactive:
C-ID:
CID Descriptor: MATH 110	Introduction to Statistics	SRJC Equivalent Course(s): STATC1000 OR PSYC9

Certificate/Major Applicable: Not Certificate/Major Applicable

COURSE CONTENT

Outcomes and Objectives:
At the conclusion of this course, the student should be able to:

1. Apply graphic displays of data and frequency distrributions.

Define mean, median, mode, percentiles, variability, standard

deviation.

3. Apply laws of probability and Baye's formula.

4. Define combinations, permutations, sample space, probability

distributions.

5. Apply Central limit theorem.

6. Calculate sampling distributions of means, proportions, standard error

confidence intervals.

7. Apply hypothesis testing for mean, proportion, variance.

8. Apply goodness to fit and independence, required sample size,

correlation and linear regression, introduction to analysis of variance.

9. Apply statistics software package for evaluation of data and inference.

Topics and Scope

1.  Statistical Description.

    Graphic display of data, frequency distributions, mean, medium,

    mode, percentiles, variability, standard deviation, Chebyshev's

    Theorem.

2.  Counting and Probability Distributions.

    Sample space, laws of probability, Bayes' Formula, combinations,

    permutations, probability distributions (including the uniform,

    binomial, hypergeometric, Poisson, normal, chi-square, and Student's

    t), normal approximation to bionomial.

3.  Statistical Inference.

    The sampling distributions of means proportions, standard error,

    Central Limit Theorem, confidence intervals, hypothesis testing

    (parametric and extended nonparametric), mean, proportion, variance,

    large and small samples, goodness of fit and independence, required

    sample size, correlation and linear regression, introduction to

    analysis of variance.

4.  Uses of Computer and Electronic Calculator.

    Use of statistics software package, evaluation of data, Monte Carlo

    methods of simulations.

Assignments:

1.  The student will have daily outside reading, problem set assignments

   from required text(s), or instructor chosen supplementary materials.

2.  Instructional methodology may include, but not limited to: lecture,

   demonstrations, oral recitation discussion, supervised practice,

   independent study, outside project or other assignments.

Methods of Evaluation/Basis of Grade.

Writing: Assessment tools that demonstrate writing skill and/or require students to select, organize and explain ideas in writing.		Writing 0 - 0%
None
This is a degree applicable course but assessment tools based on writing are not included because problem solving assessments and skill demonstrations are more appropriate for this course.
Problem solving: Assessment tools, other than exams, that demonstrate competence in computational or non-computational problem solving skills.		Problem Solving 25 - 75%
Homework problems, Exams
Skill Demonstrations: All skill-based and physical demonstrations used for assessment purposes including skill performance exams.		Skill Demonstrations 20 - 40%
Performance exams
Exams: All forms of formal testing, other than skill performance exams.		Exams 5 - 25%
Multiple choice
Other: Includes any assessment tools that do not logically fit into the above categories.		Other Category 0 - 15%
PROJECT - ORAL OR WRITTEN

Representative Textbooks and Materials:

Text(s) required of each student will be selected by the department,

a committee of the department, or the responsible instructor from the

books currently available. Choices in the past have included:

STATISTICS, Triola, (7th) 1997 Addison-Wesley

STATISTICS, Bluman (3RD) 1997 WC Brown

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