College of the Redwoods
CURRICULUM PROPOSAL
C-ID Descriptor (if applicable): Math 110
1. Course ID and Number: Math 15
2. Course Title: Introduction to Statistics
3. Check one of the following:
New Course (If the course constitutes a new learning experience for CR students, the course is new).
Required - Justification for Need (Provide a brief description of the background and rationale for the course. This might
include a description of a degree or certificate for which the course is required or the relationship of this course to
other courses in the same or other disciplines. To see examples of such descriptions, consult pages 10-11 of The
Course Outline of Record: A Curriculum Reference Guide.
Updated/Revised Course
If curriculum has been offered under a different discipline and/or name, identify the former course:
Should another course be inactivated? No
Yes
Inactivation date:
Title of course to be inactivated:
(If yes, complete a Course Inactivation Form found on the Curriculum Website.)
4. If this is an update/revision of an existing course, provide explanation of and justification for changes to this course. Be
sure to explain the reasons for any changes to class size, unit value, and prerequisites/corequisites.
Course outline needs updated wording in order to match C-ID standards.
5. List the faculty with which you consulted in the development and/or revision of this course outline.
Faculty Member Name(s) and Discipline(s): David Arnold, Tami Matsumoto, Bruce Wagner, Todd Olsen, Michael Butler,
Mike Haley, Steve Jackson, Levi Gill, Discipline: Mathematics
6. If any of the features listed below have been modified in the new proposal, indicate the “old” (current) information and
“new” (proposed) changes. If a feature is not changing, leave both the “old” and “new” fields blank.
FEATURES
OLD
NEW
Elementary Statistics
Introduction to Statistics
Catalog Description
(Please include complete text of
old and new catalog descriptions.)
The study of statistical methods as applied
to descriptive statistics and inferential
statistics. An emphasis on the meaning
and use of statistical significance will be
central to the course. Students will use
frequency distributions, graphs, measures
of relative standing, measures of central
tendency, measures of variability,
correlation, and linear regression to
explore descriptive statistics. Students will
use the laws of probability and statistical
tests (t-tests, chi-square, ANOVA, and
regression analysis) to make decisions via
hypothesis testing and estimate
parameters using confidence intervals.
The study of statistical methods as applied to
descriptive statistics and inferential statistics.
An emphasis on the meaning and use of
statistical significance will be central to the
course. Students will use probability techniques
to make decisions via hypothesis testing and will
estimate parameters using confidence intervals.
Topics include descriptive statistics; probability
and sampling distributions; statistical inference;
correlation and linear regression; analysis of
variance, chi-square and t-tests; and application
of technology for statistical analysis including
the interpretation of the relevance of the
statistical findings. The course includes
applications using data from disciplines
including business, social sciences, psychology,
life science, health science, and education.
Grading Standard
Select
Select
Course Title
TOPS/CIPS Code
Total Units
Lecture Units
Curriculum Proposal: Revised 05.08.15
Academic Senate: (pending)
Page 1 of 9
Lab Units
Prerequisites
Math 120 or Math 194
Math 120, or Math 194, or Math 102
English 150
English 150 or English 102
Select
Select
Corequisites
Recommended Preparation
Maximum Class Size
Repeatability—
Maximum Enrollments
Other
1. DATE: 11/2/2015
2. DIVISION: Math, Science, Behavioral and Social Sciences
3. [CB04] COURSE CREDIT STATUS: D Credit - Degree Applicable
4. [CB01] COURSE ID AND NUMBER: Math 15
5. [CB02] COURSE TITLE: Introduction to Statistics
(Course title appears in Catalog and schedule of classes.)
6. SHORT TITLE: Introduction to Statistics
(Short title appears on student transcripts and is limited to 30 characters, including spaces.)
7. [CB03] LOCAL ID (TOPs code): 1701.00 Taxonomy of Program Codes
8. NATIONAL ID (CIP code): 27.0101 Classification of Instructional Program Codes
9. DISCIPLINE(S): Mathematics Select from Minimum Qualifications for Faculty
Course may fit more than one discipline; identify all that apply:
10. FIRST TERM NEW OR REVISED COURSE MAY BE OFFERED: Spring 2016
11. COURSE UNITS (Note: 1 lecture unit requires 18 hours in-class/36 hours out-of-class; 1 lab unit requires 54 in-class hours)
TOTAL UNITS:
TOTAL HOURS:
[CB07]
[CB06]
4
min. units
4
max. units
Lecture Units:
4
Lab Units:
0
72
min. hours
72
max. hours
Lecture Hours:
72
Lab Hours:
0
12. MAXIMUM CLASS SIZE: 35
13. WILL THIS COURSE HAVE AN INSTRUCTIONAL MATERIALS FEE? No
Yes
Fee: $
If yes, attach a completed Instructional Materials Fee Request Form found on the Curriculum Website.
GRADING STANDARD
Letter Grade Only
Pass/No Pass Only
[CB12] Is this course a repeatable lab course? No
Grade-Pass/No Pass Option
Yes
If yes, how many total enrollments? Select
Is this course to be offered as part of the Honors Program? No
Yes
If yes, explain how honors sections of the course are different from standard sections.
Additional material will be covered emphasizing the role of statistics in the world today and the history of how statistics
Curriculum Proposal: Revised 05.08.15
Academic Senate: (pending)
Page 2 of 9
changed the way we do science.
CATALOG DESCRIPTION - The catalog description should clearly describe for students the scope of the course, its level, and
what kinds of student goals the course is designed to fulfill. The catalog description should begin with a sentence fragment.
The study of statistical methods as applied to descriptive statistics and inferential statistics. An emphasis on the meaning
and use of statistical significance will be central to the course. Students will use probability techniques to make decisions
via hypothesis testing and will estimate parameters using confidence intervals. Topics include descriptive statistics;
probability and sampling distributions; statistical inference; correlation and linear regression; analysis of variance, chisquare and t-tests; and application of technology for statistical analysis including the interpretation of the relevance of the
statistical findings. The course includes applications using data from disciplines including business, social sciences,
psychology, life science, health science, and education.
Special Notes or Advisories (e.g. Field Trips Required, Prior Admission to Special Program Required, etc.):
A TI-83 or TI-84 graphing calculator is required.
PREREQUISITE COURSE(S)
No
Yes
Rationale for Prerequisite:
Course(s): Math 120, or Math 194, or Math 102
Describe representative skills without which the student would be highly unlikely to succeed.
Intermediate Algebra or Pathway to Statistics provides the mathematical content level needed to succeed in this course, as
well as the ability to persist when the critical thinking involved becomes more advanced. Particular skills include the use of
set-notation and logic, critical thinking skills relevant for success in statistics, data analysis, inequalities, square roots,
function notation, linear functions, and percents. Ability to solve algebraic equations analytically, graphically, numerically
and verbally in real-world settings. Ability to use technology in the study of mathematics. First term the change will be
effective will be Summer 2016.
COREQUISITE COURSE(S)
No
Yes
Rationale for Corequisite:
Course(s):
RECOMMENDED PREPARATION
No
Yes
Course(s): English 150 or English 102
Rationale for Recommended Preparation:
Students will benefit from a higher level of reading competency at this level of mathematics. In addition, the written
assignments are better suited for students that have at least this level of writing skills. First term the change will be
effective will be Summer 2016.
COURSE LEARNING OUTCOMES –This section answers the question “what will students be able to do as a result of taking this
course?” State some of the outcomes in terms of specific, measurable student actions (e.g. discuss, identify, describe, analyze,
construct, compare, compose, display, report, select, etc.). For a more complete list of outcome verbs please see Public
Folders>Curriculum>Help Folder>SLO Language Chart. Each outcome should be numbered.
1. Accurately communicate statistical ideas using correct statistical notation, graphs, and vocabulary.
2. Use descriptive and inferential statistics to solve real-world problems.
3. Demonstrate appropriate use of technology in making decisions based upon real-world data.
4. Read and interpret information that contains statistical analysis and be able to communicate these results.
5. Judge the validity of research reported in the mass media and peer reviewed journals.
COURSE OBJECTIVES - This section describes the objectives the course addresses through the course content. Objectives can
include specific disciplinary questions or goals that are central to the course subject matter and are meant to address what
the various intents of the course are. Each objective should be numbered.
1. Distinguish among different scales of measurement and their implications;
2. Interpret data displayed in tables and graphically;
3. Apply concepts of sample space and probability;
4. Calculate measures of central tendency and variation for a given data set;
5. Identify the standard methods of obtaining data and identify advantages and disadvantages of each;
Curriculum Proposal: Revised 05.08.15
Academic Senate: (pending)
Page 3 of 9
6. Calculate the mean and variance of a discrete distribution;
7. Calculate probabilities using normal and t-distributions;
8. Distinguish the difference between sample and population distributions and analyze the role played by the Central
Limit Theorem;
9. Construct and interpret confidence intervals;
10. Determine and interpret levels of statistical significance including p-values;
11. Interpret the output of a technology-based statistical analysis;
12. Identify the basic concept of hypothesis testing including Type I and II errors;
13. Formulate hypothesis tests involving samples from one and two populations;
14. Select the appropriate technique for testing a hypothesis and interpret the result;
15. Use linear regression and ANOVA analysis for estimation and inference, and interpret the associated statistics; and
16. Use appropriate statistical techniques to analyze and interpret applications based on data from disciplines including
business, social sciences, psychology, life science, health science, and education.
METHODS OF INSTRUCTION – Clear methods by which instructor will facilitate acquisition of objectives. Include here
descriptions, NOT lists. Course outline must clearly articulate how these methods of instruction are related to, and help
student work towards, achieving the objectives and student learning outcomes. Instructional methodologies will be
consistent with, but will not be limited to, the following types or examples.
Students will attend and participate in classroom discussion which may include lecture and interactive group work.
Students will be introduced to technology that will enliven the core concepts of statistics. Regular assignments (problem
sets from the selected textbook) will be given that include the use of technology. Assignments of reading of mass media
and/or journal articles that illustrate the concepts of the course will be given.
COURSE CONTENT–This section describes what the course is “about”-i.e. what it covers and what knowledge students will acquire.
Concepts: What terms and ideas will students need to understand and be conversant with as they demonstrate course
outcomes? Each concept should be numbered.
1. Summarizing data graphically and numerically;
2. Descriptive statistics: measures of central tendency, variation, relative position, and levels/scales of measurement;
3. Sample spaces and probability;
4. Random variables and expected value;
5. Sampling and sampling distributions;
6. Discrete distributions – Binomial;
7. Continuous distributions – Normal;
8. The Central Limit Theorem;
9. Estimation and confidence intervals;
10. Hypothesis Testing and inference, including t-tests for one and two populations, and Chi-square test;
11. Correlation and linear regression and analysis of variance (ANOVA);
12. Applications using data from disciplines including business, social sciences, psychology, life science, health science, and
education; and
13. Statistical analysis using technology such as SPSS, EXCEL, Minitab, or graphing calculators.
Themes and Issues: What motifs, if any, are threaded throughout the course? What primary tensions or problems inherent in
the subject matter of the course will students engage? Each item should be numbered.
1. The appropriate use of technology in the problem-solving process.
2. A connection between statistics, science, and the real world.
3. The role of the student in becoming a successful learner.
4. The recognition that the problem-solving skills learned in this class are applicable in future mathematics classes, classes
in related fields, as well as in the real world.
5. The importance of communication by writing statistics using correct notation and grammar.
6. Reading unfamiliar mathematics using their text and other resources.
7. Using statistics as part of a decision-making process.
8. Critical thinking.
Skills: What abilities must students have in order to demonstrate course outcomes? (E.g. write clearly, use a scientific
calculator, read college-level texts, create a field notebook, safely use power tools, etc). Each skill should be numbered.
1. Fundamentals of Statistical Analysis: State the appropriate null and alternative hypotheses, and determine the
direction of extreme. Interpret Type I and Type II errors for given hypotheses. Validate assumptions of the hypothesis test.
Form a decision rule based on the level of significance. Calculate the appropriate test statistic. Compute the p-value and
Curriculum Proposal: Revised 05.08.15
Academic Senate: (pending)
Page 4 of 9
use it to decide which hypothesis is supported. Create an interval estimate of a parameter. Use appropriate statistical
techniques and technology to analyze and interpret applications based on data from disciplines including business, social
sciences, psychology, life science, health science, and education.
2. Data Studies and Sampling: Gather data using probability sampling methods. Recognize different types of sampling
bias. State the difference between observational versus experimental studies. Recognize bias in articles from the mass
media and professional journals.
3. Summarizing Data: Distinguish between different types of data and types of variables and the corresponding levels and
scales of measurement. Create appropriate displays of distributions (bar graphs, pie charts, frequency tables, stem-andleaf plots, frequency plots, boxplots, histograms, scatterplots). Identify shapes of distributions. Calculate descriptive
statistics, including the appropriate measure of center (mean, median, mode) and spread (range, interquartile range,
standard deviation) for a given set of data. Calculate measures of relative standing. Calculate a linear transformation and
standardize data.
4. Modeling Distributions: Model a population with the appropriate distribution of a random variable, including
continuous (normal) and discrete (binomial) distributions. Calculuate expected values of random variables. Calculate the
proportion associated with a given range of values from a random variable. Calculate the range of values of a random
variable associated with a given proportion.
5. Probability: Calculate probabilities using normal and t-distributions and simulate probabilities using technology. List a
sample space and identify events of interest in the sample space. Calculate probabilities using the rules of probability.
6. Sampling Distributions: Calculate the sampling distribution of the sample proportion. Calculate the sampling
distribution of a sample mean. Distinguish the difference between sample and population distributions and analyze the
role played by the Central Limit Theorem.
7. Testing Hypotheses and Confidence Intervals for Proportions and Means: Demonstrate the connection between
confidence intervals and hypothesis testing. Identify the appropriate conditions for using hypothesis tests for population
proportions or population means. Create a confidence interval estimate for a population proportion or a population mean.
Conduct a hypothesis test and create a confidence interval estimate for two population proportions. Conduct hypotheses
tests and create confidence interval estimates for means of paired and independent samples using z- and t-tests.
8. One-Way Analysis of Variance: Validate the assumptions in one-way ANOVA. Determine the corresponding Fdistribution. Perform a one-way ANOVA test.
9. Relationships between Two Quantitative Variables: Display the relationship and determine if a linear model is
appropriate. Calculate the least squares regression model. Perform residual analysis and identify influential points and
outliers. Determine if the linear relationship is statistically significant. Calculate r, the correlation coefficient. Recognize the
relationship between r and the slope. Interpret the coefficient of determination r^2.
10. The Chi-Square Statistic: Perform a test of the goodness of fit. Perform tests of homogeneity and of independence.
REPRESENTATIVE LEARNING ACTIVITIES –This section provides examples of things students may do to engage the course
content both inside and outside of class (e.g., critically reading outside-of-class, researching outside-of-class, writing outsideof-class, writing papers outside-of-class, completing homework outside-of-class, attending a field trip). These activities should
relate directly to the Course Learning Outcomes. Each activity should be numbered.
1. Listening to lectures.
2. Participating in group activities and/or assignments.
3. Participating in class assignments and/or discussions.
4. Completing homework assignments.
5. Reading mass media and/or journal articles that contain statistical analyses.
6. Completing online activities on the computer.
7. Using the graphing technology to complete activities designed to foster a deeper level of understanding of the concepts
and skills developed in this class.
ASSESSMENT TASKS –This section describes assessments instructors may use to allow students opportunities to provide
evidence of achieving the Course Learning Outcomes. Each assessment should be numbered.
Representative Assessment Tasks (These are examples of assessments instructors could use.):
1. Examinations and/or quizzes.
2. Homework assignments.
3. Take-home examinations and/or quizzes.
4. Writing assignments to develop communication of statistical concepts.
5. Group projects and other in-class activities.
6. Portfolios and/or reference books.
Curriculum Proposal: Revised 05.08.15
Academic Senate: (pending)
Page 5 of 9
7. Group and/or individual projects and presentations.
Required Assessments for All Sections (These are assessments that are required of all instructors of all sections at all
campuses/sites. Not all courses will have required assessments. Do not list here assessments that are listed as representative
assessments above.):
1. Collaborative and/or individual homework assignments.
2. Proctored exams, quizzes, or reports.
EXAMPLES OF APPROPRIATE TEXTS OR OTHER READINGS –This section lists example texts, not required texts.
Author, Title, and Date Fields are required
Author David M Diez, Christopher D Barr, Mine C e
̧ tinkaya-Rundel Title OpenIntro Statistics 3rd Edition Date 2015
Author John Verzani Title Using R for Elementary Statistics, 2nd Edition Date 2014
Author Martha Aliaga/Brenda Johnson Title Interactive Statistics 3rd Edition Date 2006
Author
Title
Date
Other Appropriate Readings:
COURSE TYPES
1. Is the course part of a Chancellor’s Office approved CR Associate Degree?
No
Yes
If yes, specify all program codes that apply. (Codes can be found in Outlook/Public Folders/All Public Folders/
Curriculum/Degree and Certificate Programs/choose appropriate catalog year):
Required course for degree(s)
Restricted elective for degree (s) MATH.LA.A.AA, SCIEX.LA.A.AA, LA.AA-T Mathematics, SCI.LA.A.AA, MS.AS,
FNR.AS.FOR.TECH, BUS.LA.A.AA
Restricted electives are courses specifically listed (i.e. by name and number) as optional courses from which students
may choose to complete a specific number of units required for an approved degree.
2. Is the course part of a Chancellor’s Office approved CR Certificate of Achievement?
No
Yes
If yes, specify all program codes that apply. (Codes can be found in Outlook/Public Folders/All Public Folders/
Curriculum/Degree and Certificate Programs/choose appropriate catalog year):
Required course for certificate(s)
Restricted elective for certificate(s)
Restricted electives are courses specifically listed (i.e. by name and number) as optional courses from which students
may choose to complete a specific number of units required for an approved certificate.
3. [CB24] Is this course a part of an CCCCO approved education program? 1 - Program applicable
If this is a new course and will be a part of program under development, code this course as “1 – Program applicable”.
4. [CB08] Basic Skills: NBS Not Basic Skills
5. [CB10] Work Experience: NWE Not Coop Work Experience
6. [CB22] Noncredit Category: Credit course, not applicable
7. Course eligible Career Technical Education funding (applies to vocational and tech-prep courses only): No
8. [CB23] Course developed using a Chancellor’s Office Economic Development Grant: No
Yes
Yes
9. [CB11] Purpose: Y Credit Course Course Classification Status (All credit courses should be categorized as “Y – Credit
Course”).
10. Accounting Method: W Weekly Census
11. [CB13] Disability Status: N Not a Special Class
12. [CB09] Course SAM Priority Code: E Not Occupational Definitions of SAM Priority Codes
Curriculum Proposal: Revised 05.08.15
Academic Senate: (pending)
Page 6 of 9
COURSE TRANSFERABILITY
1. [CB05] Current Transferability Status: A Transferable to both UC and CSU
2.
[CB21] Course Prior to Transfer Level: Y Not Applicable Definitions of Course Prior to Transfer Levels
CURRENT TRANSFERABILITY STATUS (Check at least one box below):
This course is currently transferable to:
Neither CSU nor UC
CSU as general elective credit
CSU as a specific course equivalent (see below)
If the course transfers as a specific course equivalent give course number(s)/ title(s) of one or more currently-active,
equivalent lower division courses from CSU.
1. Course Math 140 Elementary Statistics, Campus CSU Bakersfield
2. Course STAT 108 – Elementary Statistics,
Campus Humboldt State University
UC as general elective credit
UC as specific course equivalent
If the course transfers as a specific course equivalent give course number(s)/ title(s) of one or more currently-active,
equivalent lower division courses from UC.
1. Course 3. Elementary Statistics, Campus UC Davis
2. Course Stats 7: Basic Statistics, Campus UC Irvine
PROPOSED CSU TRANSFERABILITY (Check at least one of the boxes below):
No proposal
Remove as General Education
Propose as General Elective Credit
Propose as a Specific Course Equivalent (see below)
If specific course equivalent credit is proposed, give course number(s)/ title(s) of one or more currently-active, equivalent
lower division courses from CSU.
1. Course
, Campus
2. Course
, Campus
PROPOSED UC TRANSFERABILITY (Check one of the boxes below):
No proposal
Remove as General Education
Propose as General Elective Credit OR Specific Course Equivalent (fill in information below)
If “General Elective Credit OR Specific Course Equivalent” box above is checked, give course number(s)/ title(s) of one or
more currently-active, equivalent lower division courses from UC.
1. Course
, Campus
2. Course
, Campus
CURRENTLY APPROVED GENERAL EDUCATION (Check at least one box below):
Not currently approved
CR
CR GE Category(-ies): Area D3: Analytical Thinking, Secondary GE Category (if applicable)
CSU
CSU GE Category: B4
IGETC
IGETC Category: 2
PROPOSED CR GENERAL EDUCATION (Check at least one box below):
No proposal
Remove as General Education
Review to maintain CR GE Status
New GE Proposal
Approved as CR GE by Curriculum Committee: 12.11.15
Not approved
Approved to remove CR GE status
CR GE Area Designation(s) - To be proposed and/or maintained.
Area A: Natural Science
Area B: Social Science
Curriculum Proposal: Revised 05.08.15
Academic Senate: (pending)
Page 7 of 9
Area C: Humanities
Area D: Language and Rationality
D1: Writing
D2: Oral Communications
D3: Analytical Thinking
Area E: Multicultural Understanding*
*To be considered part of CR GE Area E, all courses must meet the following condition: The course must also be (or
be proposed) in one other CR GE area.
General Education Outcomes
For each GE area this course satisfies (See BP4025 for Area descriptions), list the course outcome(s) that map to each of the
specific GE area outcome(s). Explain how this course’s outcomes map to each of the two outcomes listed under the
appropriate area. (Note: one course outcome can satisfy both Area outcomes.)
Area A – Natural Sciences
• communicate scientific ideas;
• apply scientific concepts to analyze natural relationships.
Area B – Social Sciences
• communicate intellectual ideas related to the social sciences;
• apply social science concepts to analyze social, historical, political, anthropological or psychological relationships.
Area C – Humanities
• communicate aesthetic and/or cultural ideas;
• analyze ideas or practices specific to the influence of culture on human expression.
Area D – Language, Communication and Rationality
Area D1- Writing
• generate, compose, revise and communicate ideas clearly in writing;
• analyze ideas presented in writing, media, speech or artistic representations.
Area D2 – Oral Communication
• generate, compose, revise and communicate ideas clearly;
• analyze ideas presented in writing, media, speech or artistic representations.
Area D3 – Analytical Thinking
• communicate analytical and/or computational ideas;
• apply analytical and/or computational concepts to analyze relationships.
Statistics requires a wide breadth of critical reasoning. Perhaps more than any other lower division
mathematics course. In many ways statistics is the marriage of math and science. This course covers the
following GE Outcomes: Evaluate ideas presented in writing, media, speech, Evaluate sources of information,
Analyze/interpret data, Use problem solving skills effectively, Apply the scientific method and scientific
reasoning, Apply mathematical and scientific concepts to analyze relationships, Make judgements and ethical
decisions. These outcomes will be assessed through SLO #1, 2, 3, 4, 5.
Area E – Multicultural Understanding
• communicate an awareness of cultures in a diverse global community;
• analyze issues from multiple perspectives, specifically as they relate to gender, self identity, ethnicity, race,
socioeconomic status, sexuality, worldview, collective behavior, and/or values.
GE Criteria for Breadth and Generality
GE courses should be broad and general in scope. Typically such courses are introductory-- not advanced or specialized—and
the content encompasses a broad spectrum of knowledge within a given field of study. Explain how the proposed GE course
fulfills GE criteria for breadth and generality.
While the core of this course is to introduce students to the mathematical methods of data analysis, the context in which
Curriculum Committee Approved: 05.08.15
Academic Senate Approved: 05.02.14
Page 8 of 9
those tools are taught encompasses a wide varity of topics. Data from a varity of disciplines is included in development of the
tools of statistics. Since this course serves a varity of disciplines as a required course, "the content encompasses a broad
spectrum" of real world topics.
PROPOSED CSU GENERAL EDUCATION BREADTH (CSU GE) (Check at least one box below):
NO PROPOSAL
A. Communications and Critical Thinking
A1 – Oral Communication
A2 – Written Communication
A3 – Critical Thinking
B. Science and Math
B1 – Physical Science
B2 – Life Science
B3 – Laboratory Activity
B4 – Mathematics/Quantitative Reasoning
C. Arts, Literature, Philosophy, and Foreign Language
D. Social, Political, and Economic Institutions
C1 – Arts (Art, Dance, Music, Theater)
E. Lifelong Understanding and Self-Development
C2 – Humanities (Literature, Philosophy,
E1 – Lifelong Understanding
Foreign Language)
E2 – Self-Development
Rationale for inclusion in this General Education category: Same as above
Proposed Intersegmental General Education Transfer Curriculum (IGETC) (Check at least one box below):
NO PROPOSAL
1A – English Composition
1B – Critical Thinking-English Composition
1C – Oral Communication (CSU requirement only)
2A – Math
3A – Arts
3B – Humanities
4A – Anthropology and Archaeology
4B – Economics
4E – Geography
4F – History
4G – Interdisciplinary, Social & Behavioral Sciences
4H – Political Science, Government & Legal Institutions
4I – Psychology
4J – Sociology & Criminology
5A – Physical Science
5B – Biological Science
6A – Languages Other Than English
Rationale for inclusion in this General Education category: Same as Above
Submitted By: David Arnold and Michael Butler
Dean/Director: Dave Bazard
Tel. Ext.: 4222, 4234
Date: 11/2/15
Review Date: 11/12/15
For Dean/Director only: Does this course change require a substantial or nonsubstantial change to a degree? Yes
CURRICULUM COMMITTEE USE ONLY
Approved by Curriculum Committee: No
Yes
Date: 12.11.15
Academic Senate Approval Date: 12.14.15
Board of Trustees Approval Date:
Curriculum Committee Approved: 05.08.15
Academic Senate Approved: 05.02.14
Page 9 of 9
No