8/31/2024 11:28:26 PM |
| Changed Course |
CATALOG INFORMATION
|
Discipline and Nbr:
MATH 15 | Title:
ELEM STAT COMPUTER |
|
Full Title:
Elementary Statistics with Computer |
Last Reviewed:1/9/2024 |
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:
00 - Two Repeats if Grade was D, F, NC, or NP
Also Listed As:
Formerly:
Catalog Description:
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Computer investigation, exploration and simulations of concepts in Computer investigation, exploration and simulations of concepts in statistics, descriptive statistics, probability theory including the statistics, descriptive statistics, probability theory including the uniform, binomial, hypergeometric, Poisson, normal, chi-square and uniform, binomial, hypergeometric, Poisson, normal, chi-square and Student's t distributions, central limit theorem, estimation of population Student's t distributions, central limit theorem, estimation of population parameters from a sample, hypothesis testing including parametric and parameters from a sample, hypothesis testing including parametric and nonparametric methods, confidence intervals, correlation and linear nonparametric methods, confidence intervals, correlation and linear regression, introduction to analysis of variance computer simulations regression, introduction to analysis of variance computer simulations and Monte Carlo methods. and Monte Carlo methods.
Prerequisites/Corequisites:
Math 155.
Recommended Preparation:
Limits on Enrollment:
Schedule of Classes Information
Description:
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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:00 - Two Repeats if Grade was D, F, NC, or NP
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 | |
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IGETC: | Transfer Area | | Effective: | Inactive: |
| 2A | Mathematical Concepts & Quantitative Reasoning | Fall 1993 | |
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CSU Transfer: | Transferable | Effective: | Fall 1989 | Inactive: | |
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UC Transfer: | Transferable | Effective: | Fall 1989 | Inactive: | |
|
C-ID: |
CID Descriptor: MATH 110 | Introduction to Statistics | SRJC Equivalent Course(s): MATH15 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:
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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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