# SRJC Course Outlines

11/27/2021 3:09:11 PM | MATH 161 Course Outline as of Fall 2020
| Changed Course |

CATALOG INFORMATION |
||

Discipline and Nbr: MATH 161 | Title: MATH PREP STATS/LIB ARTS | |

Full Title: Mathematics Preparation for Statistics and Liberal Arts | ||

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 |

Grading: Grade or P/NP

Repeatability: 00 - Two Repeats if Grade was D, F, NC, or NP

Also Listed As:

Formerly:

**Catalog Description:**

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 AB705 placement into Math Tier 1 or higher

**Recommended Preparation:**

**Limits on Enrollment:**

**Schedule of Classes Information**

Description:

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 AB705 placement into Math Tier 1 or higher

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:

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:**

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**

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

G.Introduction to Sigma Notation

H. Introduction to Factorials

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:**

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:**

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