Proposal for General Education Program
1. Course/Department/Representative: PHIL 210 Inductive Reasoning /
Philosophy / Kevin Possin kpossin@winona.edu Please see attached forms.
2. Proposed WSU GEP Goal Area: Goal 4—Math/Logical Reasoning
This course currently meets Goal 4 at Minnesota State University-Mankato—
the only other state university to offer it.
3-4. WSU GEP Goal Area 4: Goal and Student Competencies and
Documentation:
GEP Goal: To increase students’ knowledge about mathematical and logical modes
of thinking. This will enable students to appreciate the breadth of applications of
mathematics, evaluate arguments, and detect fallacious reasoning. Students will
learn to apply mathematic, logic, and/or statistics to help them make decisions in
their lives and careers
Inductive Reasoning PHIL 210 Goal Documentation: This is an applied
introductory logic course, dedicated to the analysis of scientific and statistical
arguments and the detection of fallacious inductive reasoning, e.g., appeal to
false authority, confirmation bias, sharp-shooter fallacy, placebo effect, and
experimenter-expectancy effect. The ultimate goal is to enable students to form
more evidence-based, rational scientific and statistical beliefs, so as to make
better decisions about their own personal and professional desires and
intentions and their decisions regarding broader social policies.
The course outline will help to illustrate further how the GEP Goal is met:
I.
II.
III.
IV.
Deductive vs. Inductive Reasoning.
Appeal to Authority.
Epistemology and the Scientific Method.
Arguing For or Against Theoretical Hypotheses.
A. Theories and Models.
B. The 6-Step Program for Understanding and
Evaluating Theoretical Hypotheses.
C. Historical Cases.
D. Marginal Science.
V. Arguing For or Against Statistical Hypotheses.
A. Statistical Models and Distributions.
B. Simple Correlations.
C. Rules of Probability.
D. Sampling.
E. The 4-Step Program for Understanding and Evaluating
Statistical Hypotheses.
F. Historical Cases.
G. Opinion Polls and Surveys.
VI. Arguing For or Against Causal Hypotheses.
A. Causation vs. Correlation.
B. Causal Models: Deterministic v. Stochastic.
C. The 5-Step Program for Evaluating Causal Hypotheses.
D. Historical Cases and Experimental Designs:
Random Sample, Prospective, and Retrospective.
VII. Risk Assessment and Social Policy.
Programs and methods for understanding and evaluating arguments for and against
scientific hypotheses are studied and then applied to numerous cases, both
contemporary and historical. The elements and complexities of rational theory
choice are discussed and illustrated by examining many famous and contemporary
cases.
The fundamentals and notation of probability theory are studied, including the
concepts of: values of variables, proportions, probability distributions, correlation,
strength of correlation, random sample, sampling methods, selection probabilities,
relative frequencies, estimated proportions, confidence intervals, confidence levels,
standard deviations, margins of error, statistical significance, and various ways in
which random samples can increase or decrease their representational capacities.
Statistical analyses are applied to numerous polls and surveys to generate and
assess statistical hypotheses.
The distinctions among the relations of mere correlation, causation, and commoncause are studied, and various experimental designs are discussed in terms of their
differing abilities to distinguish among these possible relations. Statistical analyses
are applied to numerous cases and studies to test and assess causal hypotheses.
These analytical skills and methods are then synthesized and put to use to assess
risk with respect to personal practices and social policies, e.g., on questions such as
whether folic acid is effective in preventing birth defects or whether seatbelts
should be required in school buses instead of using the necessary funds in other
ways so as to enhance the safety of school children. Statistical analyses such as
these help students discover and correct how poor we actually are at assessing risk,
i.e. how “predictably irrational” we are, as Dan Ariely has said.
Goal Area 4 Student Competencies:
Students will be able to:
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


Illustrate historical and contemporary applications of mathematics/logical
systems.
Clearly express mathematical/logical ideas in writing.
Explain what constitutes a valid mathematical/logical argument (proof).
Apply higher-order problem-solving and/or modeling strategies.
Inductive Reasoning PHIL 210 Student Competencies Documentation:
Students will acquire, practice and demonstrate the ability to:




Illustrate historical and contemporary applications of logical systems by
illustrating and applying scientific and statistical methods of inductive
analysis to contemporary and historical experiments, studies, polls, and
surveys.
Clearly express mathematical/logical ideas in writing by clearly explaining
these methodological and statistical concepts and methods of scientific
hypothesis analysis in their written critiques of scientific articles, polls, and
surveys.
Explain what constitutes a valid mathematical/logical argument, by
explaining what constitutes a cogent scientific argument, in terms of the
reliability of the evidence used to support the theoretical hypothesis and the
implausibility of alternative explanations of the data; explaining what
constitutes a cogent statistical argument, in terms of the statistical
significance of the data used to estimate and support the statistical
hypothesis; and explaining what constitutes a cogent argument for a causal
hypothesis, in terms of the statistical significance of the data used to support
the hypothesis and how the design of the experimental study generating that
data makes alternative explanations of the data implausible.
Apply higher-order problem-solving and statistical modeling strategies by
applying the inductive reasoning skills they have acquired to assess the
reliability and statistical significance of evidence and data, so as to better
assess the risks involved in one’s own personal habits and broader social
policies, so as to make more rational decisions in one’s life and career and in
the voting booth.
5. Course Outline:
I.
II.
III.
IV.
Deductive vs. Inductive Reasoning.
Appeal to Authority.
Epistemology and the Scientific Method.
Arguing For or Against Theoretical Hypotheses.
A. Theories and Models.
B. The 6-Step Program for Understanding and
Evaluating Theoretical Hypotheses.
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C. Historical Cases.
D. Marginal Science.
V. Arguing For or Against Statistical Hypotheses.
A. Statistical Models and Distributions.
B. Simple Correlations.
C. Rules of Probability.
D. Sampling.
E. The 4-Step Program for Understanding and Evaluating
Statistical Hypotheses.
F. Historical Cases.
G. Opinion Polls and Surveys.
VI. Arguing For or Against Causal Hypotheses.
A. Causation vs. Correlation.
B. Causal Models: Deterministic v. Stochastic.
C. The 5-Step Program for Evaluating Causal Hypotheses.
D. Historical Cases and Experimental Designs:
Random Sample, Prospective, and Retrospective.
VII. Risk Assessment and Social Policy.
All course contents and requirements satisfy Goal Area 4 competencies.
Current Catalog Description: Introduction to inductive reasoning and how to
avoid being tricked by faulty or pseudo scientific claims and arguments, and how to
critically assess public policy in light of good scientific reasoning. Students study
how to use experimentation and the scientific method to test theoretical, statistical,
and causal hypotheses. Famous discoveries in the history of science are used as
illustrations. Other topics include fundamental concepts of probability, sampling,
causation, and correlation.
6. Assessment Plan:
Various means are employed to verify that students have acquired and can
demonstrate all of the Goal Area 4 Student Competencies, such as homework
exercises and exams, involving critical analyses and reviews of numerous scientific
articles, statistical surveys, polls, and clinical studies, whereby students
demonstrate their understanding and application of all the individual critical
thinking skills listed in the course outline.
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