University of Wisconsin-Whitewater
Curriculum Proposal Form #4A
Change in an Existing Course
Type of Action (check all that apply)
Course Revision (include course description & former and new syllabus) Grade Basis
Contact Hour Change and or Credit Change Repeatability Change
Diversity Option Other: Change of course name. New course name should be: Introduction to Statistical Reasoning and Analysis
General Education Option
area: *
* Note: For the Gen Ed option, the proposal should address how this course relates to specific core courses, meets the goals of General Education in providing breadth, and incorporates scholarship in the appropriate field relating to women and gender.
Effective Term:
Current Course Number (subject area and 3-digit course number): MATH 230
Current Course Title: Introductory Statistics
Sponsor(s): William Mickelson
Department(s): Mathematical and Computer Sciences
College(s):
List all programs that are affected by this change:
DEPARTMENT OF INFORMATION TECHNOLOGY AND BUSINESS EDUCATION
DEPARTMENT OF MANAGEMENT
DEPARTMENT OF OCCUPATIONAL & ENVIRONMENTAL SAFETY & HEALTH
DEPARTMENT OF BIOLOGICAL SCIENCES
DEPARTMENT OF GEOGRAPHY AND GEOLOGY
DEPARTMENT OF PHILOSOPHY AND RELIGIOUS STUDIES
DEPARTMENT OF POLITICAL SCIENCE
DEPARTMENT OF SOCIOLOGY, ANTHROPOLOGY AND CRIMINAL JUSTICE
DEPARTMENT OF COMMUNICATION SCIENCES DISORDERS
DEPARTMENT OF HISTORY
DEPARTMENT OF SOCIAL WORK
SAFETY DEGREE PROGRAM (M.S.)
GENERAL EDUCATION (GM)
If programs are listed above, will this change affect the Catalog and Advising Reports for those programs? If so, have Form 2's been submitted for each of those programs?
(Form 2 is necessary to provide updates to the Catalog and Advising Reports)
NA Yes They will be submitted in the future
11
Proposal Information: (Procedures for form #4A)
I. Detailed explanation of changes (use FROM/TO format)
FROM: MATH 230 – Introductory Statistics
A pre-calculus course in statistics. Descriptive statistics, probability distributions, prediction, hypothesis testing, correlation, and regression. This course does not count towards a mathematics major or minor in either liberal arts or secondary education or towards a mathematics minor in elementary education. This course may not be taken for credit if credit has been or is being earned in any other statistics course. Prereq: Waiver or a grade of C or better in MATH 141. Unreq: Any other statistics course.
TO: MATH 230 – Introduction to Statistical Reasoning and Analysis
A course on the principles, procedures and concepts surrounding the production, summarization and analysis of data. Emphasis on critical reasoning and interpretation of statistical results. Content includes: probability, sampling, and research design; statistical inference, modeling and computing; practical application culminating in a research project. Unrequisite: ECON 245, PSYCH 215, SOCIOLOGY 295. Prereq: Grade of C or better in Math 141 or permission of instructor.
II. Justification for action
The Department of Mathematical and Computer Sciences has essentially three courses that are an Introduction to Statistics. Two of these classes, Math 230 and Math 231, are service courses. We are updating our curriculum based on advances in statistics education and recommendations from the LEAP initiative. We are moving the MATH 230 course focus away from formulas and computations, toward statistical concepts and reasoning, critical thinking about data and data analysis. The class will have hands on data analysis components and projects. At the same time, we wish to consolidate MATH 230 and 231 into one course, Math 230-Revised, for efficiency and cost savings. Programs affected by this change will be advised to have their students enroll in the revised MATH 230 course to be renamed, Introduction to Statistical Reasoning and Analysis.
III. Syllabus/outline (if course revision, include former syllabus and new syllabus)
The revised course syllabus and an example course project description can be found below. Please see accompanying former syllabi.
Introduction to Statistics – MATH 230 – Spring 2013
MWF 12:05-12:55pm – McGraw Hall Room 125
Instructor: William T. Mickelson
Office: 2225 Laurentide Hall
Office Hours: MWF from 11:00–12:00; M 2:15-4:15; or by appointment
Text: Essential Statistics by David Moore
Prerequisite: A grade of C or better in Math 141, or waiver. A student may not register for
any course which is a pre-requisite for another course in which credit has been earned unless prior departmental approval is obtained.
Phone: (office): 262-472-5169 (home): 608-233-1884
I do have young children, so please be considerate and do not call my home phone after 9:00pm or before 7:00am.
E-mail: (please put MATH 230 in the subject line)
I check email daily during the semester and email is the preferred form of communication. Please note: email is NOT an instantaneous form of communication. You need to allow/plan at least 24 hours for a return email.
TEACHING PHILOSOPHY
I feel it is important for you to have an understanding of my teaching philosophy and the objectives I have for this introductory statistics course. My philosophy of teaching is based on two fundamental beliefs I hold about the purpose of education and the role of the teacher and student in the learning process. First, the primary aim of education is to help students develop their intellect and use their minds well. This means that you will be asked to develop ways of thinking that you may not have been exposed to in the past. Second, I recognize that each student brings to the classroom unique prior experiences, knowledge, and learning styles. It is my responsibility as an educator to help bridge the gap between you and the subject-matter of this course in a way that is meaningful for all students. It is your responsibility as a student to actively participate in the learning process and allow yourself the opportunity to learn. This means: being in class, being prepared for class by reading ahead of time, participating in class discussions, doing the experiments and data collection activities, attempting to interpret the results of our activities and assignments, and draw conclusions from data there by creating knowledge for yourself and others. By doing this you will construct for yourself an understanding of statistics that is deep enough to apply statistical reasoning on problems you are interested in, and to critique other people’s statistical arguments.
RATIONALE FOR STATISTICS AS A TOPIC TO STUDY AND THE METHOD OF INSTRUCTION IN THIS CLASS
Our society is rapidly gaining easy access to, and becoming dependent upon, ever increasing amounts of data and information. The knowledge and skills necessary to process, analyze and interpret this information/data are more important today than ever before. With this reliance on data comes a serious responsibility for all people to be educated in the basic principles and procedures of statistical reasoning. In addition, it is important for all members of our society to fully understand the extent to which statistical reasoning influences policy decisions, frames debates, informs business decisions, helps to evaluate quality of services and products, guides research, and sheds light on controversial topics. From an educational perspective, attaining statistical reasoning abilities implies that the student develop critical thinking skills about how data is obtained, summarized, and used. The teaching methods used in this class are designed to help you develop critical thinking skills about reasoning with data. Any teaching method, however, is not sufficient to ensure learning. You as the student must be actively involved in the process as well.
After about 25 years of study, debate, and argument, The American Statistical Association (ASA) and the Mathematics Association of American (MAA) Joint Curriculum Committee have developed a set of general guidelines for how the introductory statistics course should be taught. The ASA and MAA advocate:
· an increased emphasis on the elements of statistical thinking (i.e. the need for data, the importance of data production, the omnipresence of variability, the measuring and modeling of variability).
· the incorporation of more data and concepts, fewer recipes and derivations. Wherever possible, automate computations and graphics. An introductory course should: a) rely heavily on real (not merely realistic) data; b) emphasize statistical concepts; c) rely on computers rather than computational recipes; d) treat formal derivations as secondary in importance.
· active learning through the following alternatives to lecturing: a) group problem solving and discussion; b) laboratory exercises; c) demonstrations based on class-generated data; d) written and oral presentations; and e) projects.
In other words, these recommendations call for activity-based learning using real data focused on promoting the learning of statistical concepts and the development of statistical reasoning abilities. This class will be taught consistent with these general guidelines.
COURSE FRAMEWORK AND LEARNING OBJECTIVES
Applying these general principles to the teaching of statistics gives rise to my objectives for this course. I would like you to understand statistics as: a process of gathering evidence to increase our understanding of the world (there are right ways and wrong ways to do this and we must delineate the differences), a method of problem-solving, and a way to help make decisions in the face of variability and uncertainty. There are five general steps to statistical reasoning. These are: a) posing interesting and meaningful inquiry questions that can be addressed quantitatively, b) designing a study to address the inquiry question, c) collecting data, d) summarizing and analyzing the data, and e) drawing conclusions from the data. It is my opinion that a firm understanding of these topics and how they should be carried out is utterly essential for any educated person. Ultimately, the goal is for you to become a critical and informed consumer as well as producer of numerical information and argument. With this in mind, my main learning objectives are that you:
1. develop an in-depth conceptual understanding of basic statistical and probabilistic concepts, ideas and principles, as well as how they are related and interconnected.
2. can demonstrate the ability to apply the tenets of correct statistical reasoning in applied situations and correctly interpret results.
3. develop basic statistical computing and data analysis skills.
4. develop the ability to correctly interpret statistical computer printout.
5. demonstrate a correct understanding of statistical formulas and notation.
6. develop an awareness of the prevalence of the use of statistics in our society and a positive outlook toward statistics and their uses.
OUTLINE OF COURSE
Reasoning with data, the application of statistical principles and procedures, is a non-linear process. Even though there are five general steps to statistical reasoning, one must always be looking ahead and re-visiting past decisions to fully understand the context of the study and draw valid conclusions. The class will start with basic probability; move to the intricacies of research design, data collection, and exploratory data analysis; then end with a focus on statistical inference including such topics as: sampling distributions, confidence intervals and hypothesis tests. Statistical principles, procedures, and concepts will be stressed through the course materials, activities and discussions. How to reason, from a statistical perspective, will be modeled through out the course.
Chapters covered during the three primary course units, they are:
I) Probability: Chapters 9, 3, 11 and 12
II) Producing, Organizing and Describing Data: Chapters 7, 8, 1 and 2
III) Analyzing Data
a. Statistical Inference and Confidence Intervals: Chapters 10, 13, 14, 16 and 18
b. Correlation and Regression: Chapters: 4, 5 and 22
c. Contingency Tables and Chi-Square Tests: Chapters 21
COURSE REQUIREMENTS
· Attendance
· Participation
· Completion of assigned reading
· Completion of course assignments
· Mid-term examinations
· Completion of a project with written report and oral presentation
Attendance and Participation
This class will look and feel like an evolving on-going discussion with each class period building on previous experiences. Unlike most math classes, this class has a large number of difficult concepts/ideas that you will need to fully understand and be able to work with. It will not be possible for you to understand and internalize the statistical vocabulary, concepts, ideas, and mode of reasoning, or successfully apply them without being in class and actively participating in all of the class activities and discussions. Furthermore, if you do miss class, it will not be easy to catch up. Don’t miss class!
As a formal class policy, attendance and participation is required. Students with excused absences, which include university sponsored events/activities, or medical or family emergencies (documentation required), will be considered in attendance. Evidence of repeated unexcused absences will be addressed consistent with the University of Wisconsin-Whitewater polices and applied on an individual basis. Excessive (more than 5) unexcused absences will result in failure for the course, regardless of exam performance.
Assigned Reading
The sections and chapters of the textbook will be used as a supplement to what occurs during class. This class will NOT necessarily follow the textbook chapter by chapter. The specific reading assignments will be given during class. You are required to read what is assigned. Examinations will cover content from chapters and sections assigned as reading, whether or not the specific topics are covered during class time, plus class time presented additional materials. In other words, you are responsible for all assigned reading materials and course content.
Course Assignments
You will be responsible for completing various course assignments. These assignments range from helping you to understand a statistical concept or idea, developing technical skills, advancing the completion of your course project (see below), or applying what you’ve learned to become a critical consumer of research. You can expect to complete approximately 6 assignments for a total of 60 points toward the final course grade. The instructor reserves the right to change the number of assignments and point totals, depending on course events.