| 11/27/2024 11:52:51 AM |
| Changed Course |
| CATALOG INFORMATION
|
| Discipline and Nbr:
MATH 15 | Title:
ELEMENTARY STATISTICS |
|
| Full Title:
Elementary Statistics |
| 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:
00 - Two Repeats if Grade was D, F, NC, or NP
Also Listed As:
Formerly:
Catalog Description:
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Exploration of concepts in statistics, descriptive statistics, probability theory, Central Limit Theorem, estimation of population parameters from a sample, hypothesis testing, correlation and linear regression, introduction to analysis of variance, and computer simulations.
Prerequisites/Corequisites:
Completion of MATH 161 OR MATH 156 OR MATH 154 OR MATH 155 or AB705 placement into Math Tier 1 or higher
Recommended Preparation:
Limits on Enrollment:
Schedule of Classes Information
Description:
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Exploration of concepts in statistics, descriptive statistics, probability theory, Central Limit Theorem, estimation of population parameters from a sample, hypothesis testing, correlation and linear regression, introduction to analysis of variance, and computer simulations.
(Grade or P/NP)
Prerequisites:Completion of MATH 161 OR MATH 156 OR MATH 154 OR MATH 155 or AB705 placement into Math Tier 1 or higher
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 | |
| |
| 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:
Both Certificate and Major Applicable
Approval and Dates
| Version: | 010 | Course Created/Approved: | 10/31/1989 |
| Version Created: | 9/20/2018 | Course Last Modified: | 8/17/2024 |
| Submitter: | Ivana Gorgievska | Course Last Full Review: | 10/28/2024 |
| Version Status: | Approved Changed Course | Prereq Created/Approved: | 10/28/2024 |
| Version Status Date: | 10/22/2018 | Semester Last Taught: | Summer 2024 |
| Version Term Effective: | Summer 2019 | Term Inactive: | Fall 2024 |
COURSE CONTENT
Student Learning Outcomes:
At the conclusion of this course, the student should be able to:
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1. Use numerical and graphical methods to summarize, display, and interpret data sets.
2. Estimate population parameters from sample statistics.
3. Perform one and two sample hypothesis tests for population means and proportions.
Objectives:
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At the conclusion of this course, the student should be able to:
1. Create and use graphic displays of data and frequency distributions.
2. Identify the standard methods of obtaining data and identify advantages and disadvantages of
each method.
3. Distinguish among different scales of measurement and their implications.
4. Define mean, median, mode, percentiles, variability and standard deviation, and compute
each for sets of data.
5. Use laws of probability.
6. Apply concepts of sample space and probability distributions, including calculation of the
mean and variance of a discrete distribution, and calculation of probabilities using normal
and t distributions.
7. Distinguish between sample and population distributions, and apply the Central
Limit Theorem to calculate sampling distributions of means, proportions and standard error.
8. Compute and interpret confidence intervals and required sample size.
9. Identify the basic concept of hypothesis testing including Type I and II errors.
10. Select the appropriate technique for testing a hypothesis and interpret the result.
11. Perform hypothesis testing for mean, proportion and variance.
12. Determine and interpret levels of statistical significance including p-values.
13. Implement goodness of fit test, and the test for independence.
14. Use linear regression and Analysis of Variance (ANOVA) for estimation and inference, and
interpret the associated statistics.
15. Use statistical software for evaluation of data and inference.
16. Process data sets from disciplines including business, social sciences, psychology, life
sciences, health sciences and education.
Topics and Scope
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I. Statistical Description
A. Graphic display of univariate and bivariate data
B. Levels of measurement
C. Frequency distributions
1. Shapes of distributions
2. Empirical rule
D. Measures of central tendency
E. Measures of variation
F. Measures of relative position
G. Correlation
II. Probability Theory
A. Sample space and laws of probability
B. Random variables and expected value
C. Probability distributions including, but not limited to
1. Binomial
2. Normal
3. Student
4. Chi squared
III. Statistical Inference
A. Sampling methods and experimental design
B. Sampling distributions of means and proportions
C. Standard error
D. Central Limit Theorem
E. Estimation and confidence intervals
F. Hypothesis testing
1. Tests of proportions and means, including t-tests for one and two populations
2. Chi square tests: goodness of fit and independence
3. P-values, significance, type I and type II errors
G. Required sample size
H. Correlation and linear regression
I. Introduction to ANOVA (analysis of variance)
IV. Use of Statistical Software
A. Analysis and evaluation of data
B. Methods of simulations
V. Use Data Sets from Disciplines, such as:
A. Business
B. Social sciences
C. Behavioral sciences
D. Life sciences
E. Health sciences
F. Education
Assignments:
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1. Reading outside of class (0-50 pages per week)
2. Problem set assignments from required text(s) or supplementary materials chosen by the
instructor (8-16)
3. Exams (2-4) and a final exam; quizzes (0-20)
4. Projects, e.g. computer activities, surveys or data collection and analysis (0-2)
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 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
10 - 30% |
| Problem sets | |
| Skill Demonstrations: All skill-based and physical demonstrations used for assessment purposes including skill performance exams. | Skill Demonstrations
0 - 0% |
| None | |
| Exams: All forms of formal testing, other than skill performance exams. | Exams
70 - 80% |
| Objective exams, quizzes, final | |
| Other: Includes any assessment tools that do not logically fit into the above categories. | Other Category
0 - 10% |
| Projects | |
Representative Textbooks and Materials:
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Elementary Statistics: Picturing the World. 6th ed. Larson, Ron and Farber, Betsy. Pearson. 2015
Elementary Statistics. 12th ed. Triola, Mario. Pearson. 2014 (classic)
Elementary Statistics, A Step by Step Approach. 9th ed. Bluman, Allan. McGraw-Hill. 2013 (classic)
Modern Elementary Statistics. 12th ed. Freund, John and Perles, Benjamin. Pearson. 2007 (classic)
OTHER REQUIRED ELEMENTS
| Student Preparation |
| Matric Assessment Required: | M | Requires Math Assessment |
| Prerequisites-generate description: | U | User Generated Text |
| Advisories-generate description: | NA | No Advisory |
| Prereq-provisional: | N | NO |
| Prereq/coreq-registration check: | Y | Prerequisite Rules Exist |
| Requires instructor signature: | N | Instructor's Signature Not Required |
| | | |
| BASIC INFORMATION, HOURS/UNITS & REPEATABILITY |
| Method of instruction: | 02 | Lecture |
| | 72 | Internet-Based, Delayed Interaction |
| | 71 | Internet-Based, Simultaneous Interaction |
| Area department: | MATH | Mathematics |
| Division: | 73 | Science, Technology, Engineering & Mathematics |
| Special topic course: | N | Not a Special Topic Course |
| Program Status: | 1 | Both Certificate and Major Applicable |
| Repeatability: | 00 | Two Repeats if Grade was D, F, NC, or NP |
| Repeat group id: | | |
| | | |
| SCHEDULING |
| Audit allowed: | N | Not Auditable |
| Open entry/exit: | N | Not Open Entry/Open Exit |
| Credit by Exam: | N | Credit by examination not allowed |
| Budget code: Program: | 0000 | Unrestricted |
| Budget code: Activity: | 1701 | Mathematics-General |
| | | |
| OTHER CODES |
| Disciplines: | Mathematics |
| Basic Skills: | N | Not a Basic Skills Course |
| Level below transfer: | Y | Not Applicable |
| CVU/CVC status: | Y | Distance Ed, Not CVU/CVC Developed |
| Distance Ed Approved: | Y | Hybrid (i.e., a mix of face-to-face and technology-based instruction) |
| Emergency Distance Ed Approved: | Y | Fully Online
Partially Online
Online with flexible in-person activities
|
| Credit for Prior Learning: | N | Agency Exam |
| N | CBE |
| N | Industry Credentials |
| N | Portfolio |
| Non-credit category: | Y | Not Applicable, Credit Course |
| Classification: | Y | Liberal Arts and Sciences Courses |
| SAM classification: | E | Non-Occupational |
| TOP code: | 1701.00 | Mathematics, General |
| Work-based learning: | N | Does Not Include Work-Based Learning |
| DSPS course: | N | NO |
| In-service: | N | Not an in-Service Course |
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