SRJC Course Outlines

9/22/2019 3:36:23 AMMATH 161 Course Outline as of Summer 2019

New Course (First Version)
CATALOG INFORMATION

Discipline and Nbr:  MATH 161Title:  MATH PREP STATS/LIB ARTS  
Full Title:  Mathematics Preparation for Statistics and Liberal Arts
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
Survey of fundamental algebra topics, probability and exploratory data analysis needed to prepare students for transfer-level statistics and liberal arts mathematics courses.
 
Advisory: This course is NOT intended for math, science, computer science, business, or engineering majors.

Prerequisites/Corequisites:
Completion of MATH 150 or MATH 151 or MATH 150B or appropriate placement based on AB 705 mandates


Recommended Preparation:

Limits on Enrollment:

Schedule of Classes Information
Description: Untitled document
Survey of fundamental algebra topics, probability and exploratory data analysis needed to prepare students for transfer-level statistics and liberal arts mathematics courses.
 
Advisory: This course is NOT intended for math, science, computer science, business, or engineering majors.
(Grade or P/NP)

Prerequisites:Completion of MATH 150 or MATH 151 or MATH 150B or appropriate placement based on AB 705 mandates
Recommended:
Limits on Enrollment:
Transfer Credit:
Repeatability:00 - Two Repeats if Grade was D, F, NC, or NP

ARTICULATION, MAJOR, and CERTIFICATION INFORMATION

Associate Degree:Effective:Summer 2019
Inactive: 
 Area:B
MC
Communication and Analytical Thinking
Math Competency
 
CSU GE:Transfer Area Effective:Inactive:
 
IGETC:Transfer Area Effective:Inactive:
 
CSU Transfer:Effective:Inactive:
 
UC Transfer:Effective:Inactive:
 
C-ID:

Certificate/Major Applicable: Both Certificate and Major Applicable



COURSE CONTENT

Student Learning Outcomes:
Upon completion of the course, students will be able to:
Untitled document
1.  Create linear and exponential models using real world data in the context of application
    problems.
2.  Find and analyze summary statistics for categorical and quantitative data.
3.  Create and analyze graphical representations for categorical and quantitative data.
4.  Create and interpret functions graphically, verbally, and algebraically.
 

Objectives: Untitled document
During this course, students will:
1. Evaluate, apply, and simplify algebraic expressions.
2. Use linear expressions, equations, and inequalities in application problems.
3. Produce data through random sampling and analyze the data collected.
4. Analyze real data sets by finding measures of central tendency, position, and spread, and by
    constructing various charts and graphs.
5. Use data to calculate and analyze the slope, y-intercept, and equation of a line in two variables
    and construct a graph of the linear equation and regression line.
6. Apply linear and exponential functions for regression analysis to solve application problems.
7. Solve and analyze basic probability problems using ratios, proportions, two-way tables and
    percentages.
8. Consistently apply effective learning strategies for success in college.

Topics and Scope
Untitled document
I. Arithmetic Operations, Formulas and Algebraic Expressions
    A. Arithmetic of signed numbers and interpretation of inequalities
    B. Operations with fractions, proportions, ratios and percent
    C. Measurement and unit conversion
    D. Exponents, square roots, scientific notation
    E. Order of operations and simplifying algebraic expressions
     F. Evaluating formulas
 
II. Exploratory Data Analysis
    A. Quantitative versus categorical data
    B. Collecting data
    C. Frequency and relative frequency tables
    D. Constructing and reading bar charts, dot plots, and histograms
    E. Measures of center: mean and median
    F. Measures of spread: range and standard deviation
    G. Quartiles and box plots
 
III. Linear Equations and Inequalities
     A. Solving general linear equations with application problems
    B. Solving formulas with application problems
    C. The rectangular coordinate system and plotting ordered pairs
    D. Graphs of linear equations
    E. Find and interpret slope, rate of change and y-intercept
    F. Writing, solving and graphing one-variable linear inequalities
 
IV. Functions
    A. Function notation, models and applications
    B. Graphing various functions, models and applications
    C. Constructing and analyzing scatterplots
    D. Regression line, prediction and interpretation
 
V. Exponential Functions
    A. Integer and rational exponents
    B. Exponential functions and their graphs
     C. Exponential growth and decay
    D. Exponential regression, prediction and interpretation
    E. Introduction to logarithms
 
VI. Probability
    A. Introduction to probability, notation and rules
    B. Conditional probability
     C. Probability and proportions calculated from two-way tables
 
VII. Technology - Use of Technology (Calculator or Computer Software) to Evaluate Formulas,
      Calculate Probabilities, Analyze Data, and Find Statistics
 
VIII. Topics Related To Developing Effective Learning Skills
     A. Study skills: organization and time management, test preparation and test-taking skills
    B. Self-assessment: using performance criteria to judge and improve one's own work,
         analyzing and correcting errors on one's test
    C. Use of resources: strategies identifying, utilizing, and evaluating the effectiveness of
         resources in improving one's own learning, e.g., peer study groups, computer
         resources, lab resources, tutoring resources

Assignments:
Untitled document
1. Reading outside of class (0-60 pages per week)
2. Problem sets (1-8 per week)
3. Quizzes (0-4 per week)
4. Projects (0-10)
5. Exams (2-6)
6. Final exam

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
5 - 20%
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 - 95%
Exams and quizzes
Other: Includes any assessment tools that do not logically fit into the above categories.Other Category
0 - 10%
Projects and participation


Representative Textbooks and Materials:
Untitled document
Pre-Statistics ALEKS (software)
 
Pre-Statistics. Davis, Donald and Armstrong, William and McCraith, Mike. Cengage. 2019
 
A Pathway to Introductory Statistics. Lehmann, Jay. Pearson. 2016

Print PDF