# SRJC Course Outlines

 7/3/2022 7:58:55 PM MATH 15 Course Outline as of Summer 2019 Changed Course CATALOG INFORMATION Discipline and Nbr:  MATH 15 Title:  ELEMENTARY STATISTICS Full Title:  Elementary Statistics Last Reviewed:10/22/2018

 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
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: Untitled document
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: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: BMC Communication and Analytical ThinkingMath 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: UC Transfer: Transferable Effective: Fall 1989 Inactive: C-ID: CID Descriptor: MATH 110 Introduction to Statistics SRJC Equivalent Course(s): MATH15 OR PSYCH9

Certificate/Major Applicable: Both Certificate and Major Applicable

COURSE CONTENT

Student Learning Outcomes:
Upon completion of the course, students will 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: Untitled document
During this course, students will:
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:
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)