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|Discipline and Nbr:
|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
Title 5 Category:
AA Degree Applicable
Grade or P/NP
00 - Two Repeats if Grade was D, F, NC, or NP
Also Listed As:
| ||Total Out of Class Hours: 140.00||Total Student Learning Hours: 210.00||
Exploration of concepts in statistics, descriptive statistics, probability theory (including but not limited to the uniform, binomial, Poisson, normal, chi-square and t distributions), Central Limit Theorem, estimation of population parameters from a sample, hypothesis testing (including parametric and nonparametric methods), correlation and linear regression, introduction to analysis of variance, computer simulations.
Completion of MATH 154 or higher (VF)
Limits on Enrollment:
Schedule of Classes Information
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, computer simulations.
(Grade or P/NP)
Prerequisites:Completion of MATH 154 or higher (VF)
Limits on Enrollment:
Repeatability:00 - Two Repeats if Grade was D, F, NC, or NP
ARTICULATION, MAJOR, and CERTIFICATION INFORMATION
Major Applicable Course
Outcomes and Objectives:
At the conclusion of this course, the student should be able to:
|Associate Degree:||Effective:||Fall 1981||Inactive:||
|Communication and Analytical Thinking
|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:||
| CID Descriptor: MATH 110|| Introduction to Statistics|| SRJC Equivalent Course(s): MATH15 OR PSYCH9
Upon successful completion of the course, students will be able to:
1. Create and use graphic displays of data and frequency distributions.
2. Define mean, median, mode, percentiles, variability and standard
deviation, and compute each for sets of data.
3. Use laws of probability and Bayes' formula.
4. Define and apply combinations, permutations, sample space, and
5. Apply the Central Limit Theorem.
6. Calculate sampling distributions of means, proportions and standard
7. Compute confidence intervals and required sample size.
8. Perform hypothesis testing for mean, proportion and variance.
9. Implement goodness of fit test, the test for independence, and
analysis of variance.
10. Discuss linear regression and correlation, and compute regression equations.
11. Use statistics software package for evaluation of data and inference.
12. Process data sets from disciplines including business, social sciences, psychology,
life science, health science and education.
Topics and Scope
I. Statistical Description
A. Graphic display of data
B. Frequency distributions
H. Standard deviation
I. Chebyshev's Theorem
II. Counting and Probability Distributions
A. Laws of probability and counting
D. Probability distributions (including, but not limited to, the
6. Student t
III. Statistical Inference
A. Sampling distributions
3. Differences of means
B. Standard error
C. Central Limit Theorem
D. Confidence intervals
E. Hypothesis testing (parametric and extended nonparametric)
3. Differences of means
5. Goodness of fit and independence
F. Required sample size
G. Correlation and linear regression
H. Introduction to analysis of variance
IV. Use of computer and electronic calculator
A. Evaluation of data
B. Methods of simulations
V. Use data sets from the social, physical and the biological sciences.
1. Daily reading outside of class (0-50 pages per week)
2. Problem set assignments from required text(s) or supplementary
materials chosen by the instructor
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.
Representative Textbooks and Materials:
|Writing: Assessment tools that demonstrate writing skill and/or require students to select, organize and explain ideas in writing.||Writing
0 - 0%
|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%
|Skill Demonstrations: All skill-based and physical demonstrations used for assessment purposes including skill performance exams.||Skill Demonstrations
0 - 0%
|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%
Elementary Statistics: Picturing the World (5th ed.). Larson, Ron and Farber, Betsy. Pearson:
Elementary Statistics, A Step by Step Approach (8th ed.). Bluman, Allan. McGraw-Hill: 2010.
Modern Elementary Statistics (12th ed.). Freund, John. Pearson: 2007.
Elementary Statistics (12th ed.). Triola, Mario F. Pearson: 2010.