SRJC Course Outlines

9/24/2022 8:45:52 AMMATH 15 Course Outline as of Fall 1999

Changed Course
CATALOG INFORMATION

Discipline and Nbr:  MATH 15Title:  ELEM STAT COMPUTER  
Full Title:  Elementary Statistics with Computer
Last Reviewed:10/22/2018

UnitsCourse Hours per Week Nbr of WeeksCourse Hours Total
Maximum4.00Lecture Scheduled4.0017.5 max.Lecture Scheduled70.00
Minimum4.00Lab Scheduled06 min.Lab Scheduled0
 Contact DHR0 Contact DHR0
 Contact Total4.00 Contact Total70.00
 
 Non-contact DHR0 Non-contact DHR Total0

 Total Out of Class Hours:  140.00Total 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:
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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: Untitled document
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:
 B4Math/Quantitative ReasoningFall 1990
 
IGETC:Transfer Area Effective:Inactive:
 2AMathematical Concepts & Quantitative ReasoningFall 1993
 
CSU Transfer:TransferableEffective:Fall 1989Inactive:
 
UC Transfer:TransferableEffective:Fall 1989Inactive:
 
C-ID:
 CID Descriptor: MATH 110 Introduction to Statistics SRJC Equivalent Course(s): MATH15 OR PSYCH9

Certificate/Major Applicable: Not Certificate/Major Applicable



COURSE CONTENT

Outcomes and Objectives:
Upon completion of the course, students will be able to:
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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
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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:
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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:
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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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