SRJC Course Outlines

11/16/2019 4:00:53 PMMATH 15 Course Outline as of Summer 2019

Changed Course
CATALOG INFORMATION

Discipline and Nbr:  MATH 15Title:  ELEMENTARY STATISTICS  
Full Title:  Elementary Statistics
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:  00 - Two Repeats if Grade was D, F, NC, or NP
Also Listed As: 
Formerly: 

Catalog 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/Corequisites:
Completion of MATH 161 OR MATH 156 OR MATH 154 OR MATH 155 or appropriate placement based on AB 705 mandates


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.
(Grade or P/NP)

Prerequisites:Completion of MATH 161 OR MATH 156 OR MATH 154 OR MATH 155 or appropriate placement based on AB 705 mandates
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:
 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

Certificate/Major Applicable: Major Applicable Course



COURSE CONTENT

Student Learning Outcomes:
Upon completion of the course, students will be able to:
Untitled document
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
Untitled document
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:
Untitled document
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:
Untitled document
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)

Print PDF