Professional Component: Mathematics and Physical Sciences
Prepared by: Michael Frankel
Revised: November 10, 2003
Required Course PHYS 152 Mechanics
Catalog Description: Credit 4. Class 3. Lab 2.
Statics, uniform and accelerated motion; Newton's Laws; circular motion; energy, momentum, and conservation principles; dynamics of rotation; gravitation and planetary motion; properties of matter; simple harmonic and wave motion.
Prerequisite: MATH 164
Textbook: H.D. Young and R.A. Freedman, University Physics, AddisonWesley (10th Edition), 2000. ISBN 0201603225.
Coordinator: Frederick W. Kleinhans, Associate Professor of Physics.
Prerequisites by Topic: Algebra, trigonometry, one variable differential and integral calculus.
Goals: To teach students of science and engineering the uses and applications of Newton’s laws of mechanics.
Course Outcomes:
Upon successful completion of the course, students should be able to:

Recognize the difference between scalar and vectorial quantities. Be able to solve problems with both.

Solve problems involving the motion of a body in one dimension, under different conditions (uniform velocity, uniform acceleration, varying acceleration).

Solve problems associated with the motion of a body under the effect of gravity (projectile motion).

Determine the motion of a body in different frames of reference.

Graphically analyze a problem by drawing its free body diagrams.

Solve problems using Newton’s three laws of motion.

Solve problems using the equivalence between work and energy.

Distinguish between conservative and nonconservative forces. Be able to associate a potential energy with a conservative force.

Solve collision problems in one and two dimensions by using conservation of momentum.

Solve problems involving the rotation of bodies.

Use conservation of angular momentum to explain the rotational motion of different bodies.

Describe the motion of a mass attached to a spring and other examples involving simple harmonic motion.

Determine all the forces acting on a rigid body in equilibrium.

Solve problems where a body is elastically deformed under the action of external forces.

Solve problems using Newton’s law of gravitation.

Determine periods, radii, and orbits of celestial bodies and satellites.

Use Pascal’s principle, Arquimides’s principle and Bernoulli’s equation to solve problems involving static and moving fluids.

Determine the speed of a wave in a mechanical medium.

Determine the interference patterns arising when two or more waves are present on a medium.

Determine the normal modes of oscillation in a medium of simple geometry.

Solve problems involving sound waves in air.
Topics:

Vectors (1 period)

Motion in one dimension and free falling bodies (2 periods)

Motion in two dimensions (2 periods)

Newton’s laws and applications (2 periods)

Work, mechanical energy and power (2 periods)

Potential energy (1 period)

Momentum, conservation of momentum and collisions (2 periods)

Rotation of rigid bodies (1 period)

Dynamics of rotational motion (1 period)

Angular momentum, conservation of angular momentum and precession (1 period)

Oscillatory motion and simple harmonic motion (2 periods)

Equilibrium and elasticity (2 periods)

Gravitation and orbits (2 periods)

Fluids: static and dynamics (2 periods)

Mechanical waves. Speed of waves, interference and normal modes (2 periods)

Sound (1 period)
Computer Usage: Most of the assignments are submitted electronically. The students also learn to use computers to acquire data, to analyze errors occurring during the measurement process, and to make simulations of physical problems.
Laboratory Projects:

Introduction to motion

Kinematics

Projectile motion

Error analysis

Newton’s laws

Mechanical energy

Collisions in two dimensions

Rotations

Simulations using Microsoft Excel®

Simple harmonic motion

Equilibrium and statics

Space mission (web based laboratory)

Waves
Professional Component: Mathematics and Physical Sciences
Prepared by: Ricardo S. Decca and Frederick W Kleinhans
Revised: March 29, 2003
Required Course: Physics 251 Heat, Electricity and Optics
Catalog Description Credit 5. Class 4. Lab 2.
Heat, kinetic theory, elementary thermodynamics, heat transfer. Electrostatics, Electrical Currents and devices. Magnetism and electromagnetic radiation. Optics.
Prerequisite: PHYS 152 Mechanics
Corequisite: MATH 261 Multivariate Calculus
Prerequisites by topic: Calculusbased mechanics
Textbook: H.D. Young and R.A. Freedman, University Physics, AddisonWesley, 2000. ISBN 0201603225
Coordinator: Andrew D.Gavrin, Associate Professor of Physics.
Goals: To teach science and engineering majors the fundamentals of classical physics beginning with electrostatics and ending with geometrical optics. Thermodynamics is also included beginning with the definitions of heat and temperature and ending with the second law of thermodynamics.
Course Outcomes:
After completion of this course, the students should be able to:

Learn basic terminology of heat, electricity, and optics

Learn fundamental physical laws and the skills needed for heat, electricity, and optics

Solve kinetic theory, elementary thermodynamics, and heat transfer problems

Solve electrostatics and electrical current problems and devices

Solve magnetism and electromagnetic radiation problems

Solve optics problems.
Topics:

Electric Charge

Electric Field and Force

Properties of Electric Conductors and Insulators

Gauss’s Law

Electric Potential and Potential Energy

Capacitance

Dielectrics

Electric Current

Resistance and Resistivity

Electromotive Force

Direct Current Circuits

RC Circuits

Magnetic Forces and Fields

BiotSavart Law and Ampere’s Law

Faraday’s Law and Lenz’s Law

Electromagnetics Induction Phenomena

Inductance and RL circuits

Alternating Current Circuits

Electromagnetic Radiation

Reflection, Refraction, Dispersion and Polarization of Light

Geometric Optics

Temperature and Heat

KineticMolecular Theory of Gases

The First Law of Thermodynamics

The Second Law of Thermodynamics
Computer Usage: Students use computers in lab to acquire, analyze and display data, and to perform simulations of physical systems. Students use a webbased system to download and submit homework. Students interact with faculty and other students through a course web site.
Laboratory Projects:

Mathematical Exploration and Review (3 weeks)

Introduction to Electronics (1 week)

Use of Excel to Simulate Physical (1 week)

DC Circuits (simulation) (1 week)

DC Circuits (implementation) (1 week)

Magnetic Fields (1 week)

Introduction to Oscilloscope (1 week)

AC Circuits (2 weeks)

Optics (1 week)

Thermodynamics (2 weeks)
Evaluation Methods: Tests, HW and lab reports.
Professional Component: Mathematics and Physical Sciences
Prepared by: Andrew D. Gavrin
Revised: April 30, 2002
Required Course: TCM 360 Communication in Engineering Practice
Catalog Description: Credit 2. Class 1. Recitation 2.
The application of rhetorical principles to written and oral communication in the engineering professions. Planning, drafting and revising professional engineering reports; planning and delivering oral presentations; organizing information; developing persuasive arguments.
Prerequisites: ENG W131, COMM R110, Junior Standing or Consent of Instructor.
Textbook: T.E. Pearshall, The Elements of Technical Writing, 2^{nd} Edition, Allyn and Bacon, 2002. ISBN 0205318738
Coordinator: Dr. Wanda L. Worley, Assistant Professor of Technical Communications
Goals: To improve junior and senior engineering students’ ability to select, organize and present technical information to audiences in organizational settings – both in writing and orally.
Course Outcomes:
Upon successful completion of the course, students should be able to:

Describe the circumstances for a written or oral communication activity in an organizational setting.

Identify the audience(s) for a communication activity and describe them, noting, in particular, their informational needs, their levels of technical and organizational knowledge and other factors about them which might affect their participation in and response to the communication activity.

Narrate the events which preceded the communication activity and which are likely to follow it, nothing previous necessary or important and which may affect the outcome of the communication activity.

Prepare and present effective oral and written reports for the audiences and organizational circumstances students have identified. Such reports will be characterized by:

Information appropriate for the audience members’ needs and the writer/speaker’s purposes,

Organizational patterns that support the content and purposes of the report.

Language and visual elements that are appropriate in register and technical detail for the audience and the situation.

Layout in written documents and delivery in oral presentations that facilitate audience understanding of the writer/speaker’s purposes and content.

Provide helpful feedback to classmates on drafts of documents, rehearsals of speeches and final speech performances.

Describe own processes and strategies for analyzing situations and developing written reports and oral presentations and identify own need for assistance or further development.

Manage communication projects in an effective and efficient manner.

Use current technology to prepare written reports and visual aids to support oral presentations.

Hone general communication skills, including standard English communication conventions.
Topics:

Principles of technical writing (2 periods)

Communication context (2 periods)

Report purposes, audiences, formats (4 periods)

Peer response to written documents (4 periods)

Oral presentations

Grammar, punctuation, usage, style, sentence structure, tone (4 periods)

Visual elements in reports (1 period)

PowerPoint to supplement oral reports (1 period)

Group project (7 periods)

Criteria in comparison reports (.5 periods)

Specific report formats:

ProblemSolution (7 periods)

Comparison Using Criteria (7 periods)

Application resume and cover letter (5 periods)

Content

Design & Layout

Digital

IUPUI career placement resources

Interviewing skills

Letter format, style, tone, etc.

Email etiquette (5 periods)
Evaluation Methods: Written reports, oral presentations.
Professional Component: Communications and Ethics
Prepared By: Wanda L. Worley
Revised: November 21, 2003
Elective STAT 350 Introduction to Statistics (3 cr.)
(one of the three Statistics and Probability electives)
Catalog Description: Credit 3. Class 3.
A dataoriented introduction to the fundamental concepts and methods of applied statistics. Intended primarily for majors in the mathematical sciences (Mathematics, Actuarial Sciences, Mathematics Education). The objective is to acquaint the students with the essential ideas and methods of statistical analysis for data in simple settings. It covers material similar to that of STAT 511 but with emphasis on more dataanalytic material. Includes a weekly computing laboratory using Minitab.
Prerequisite: Completion of MATH 163 within the past two academic years with a minimal grade of C.
Prerequisite by Topic: Transcendental functions, methods of differentiation and integration, partial differentiation and integration.
Textbook: A.C. Tamhane and D.D. Dunlop, Statistics and Data Analysis from Elementary to Intermediate, 2000, Prentice Hall Publishing, (ISBN 0137444265).
Coordinator: Dr. Benzion Boukai, Professor, Stat Group, Mathematical Sciences
Goals: Application of basic probability models and appropriate statistical methodologies for data analysis in scientific research. This is introductory statistics course (calculus based) for students majoring in Mathematics, Sciences, and Engineering.
Course Outcomes:
Upon successful completion of this course, students should:

Become familiar with the axioms and rules of probability including the longrun interpretation.

Become familiar with description and properties of frequently used discrete and continuous random variables and distributions used to model various applied phenomenon.

Know the notions of population, sample, types of variables and appropriate method of presenting quantitative information in tables and diagrams

Learn the notion of sampling distribution of a statistic as a thought experiment of obtaining values of the statistic by repeated independent sampling.

Learn who to estimate basic population characteristics based on random samples, and develop an appreciation for the random error inherent in such estimation by constructing confidence intervals.

Learn the proper approaches for constructing significant test of (scientific) statistical hypothesis.

Apply statistical tests of significance in comparing two or more subpopulations, and in relation between two or more variables (continuous or discrete).
Topics:
The following outline is a week by breakdown of topics. There are 2 periods per week (1 period = 75 class minutes), for a 15week semester.

Probability axioms, properties and interpretation. Counting techniques, Conditional Probability and Bayes Formula, independence.

Random variables; discrete and continuous. Expected values

Joint DistributionsIndependence, Chebyshev’s Inequality and the WLLN. More on random variables, transformations, sums and independence

Useful random variables and their distributions. The Binomial and Normal distributions.

Collecting Data and Sampling Design. Describing data: measures of centrality and variability.

Displaying data: basic graphical methods. Summarizing Bivariate Data, exploring relationship.

Sampling distributions of statistics. The Central Limit Theorem.

Review and Examination.

Introduction to Statistical Inference. Point Estimation. Estimation of the mean of a normal population and proportion in a dichotomous population

Estimation with Confidence. Tests of Hypotheses.

Inference about the population mean.

Comparing two population means, paired and independent.
Computer Usage: Students use computers to perform laboratory projects with the Statistical software MINITAB.
Laboratory Projects: A set of 67 computer projects with Minitab will be covered. These projects are primarily designed to give the student a taste of how statistical work is done in practice; for display, computation and analysis of data as well as for simulations and demonstrations of probability laws. They will combine concepts learned in class, computation/simulations, data exploration and analysis as well as a clear communication of the results obtained.
Evaluation Methods: Homework, projects, a midterm and a final exam.
Professional Component: Mathematics and Physical Sciences
Prepared by: Benzion Boukai
Revised: November 07, 2003
Elective: STAT 511 Statistical Methods I (3 cr.)
(one of the three Statistics and Probability electives)
Catalog Description: Credit 3. Class 3.
Descriptive statistics, Probability axioms and rules, Counting techniques, Discrete random variables, Continuous random variables, Random samples and sampling distributions, Point estimation, Confidence interval estimation, Tests of hypotheses, Analysis of variance, Simple linear regression and correlation, Goodnessoffit tests and Twoway contingency tables.
Prerequisite: Completion of MATH 164 within the past two academic years with a minimal grade of C.
Prerequisite by Topic: Transcendental functions, methods of differentiation and integration, partial differentiation and integration, implicit functions, power series, improper integrals.
Textbook: J.L. Devore, Probability and Statistics: For Engineering and the Science, 5^{th} ed., 1999, Duxbury, ISBN 0534372813.
Coordinator: Stat Group, Mathematical Sciences
Goals: Proper application of (1) probability models and (2) statistical methodologies in scientific research.
Course Outcomes:
Upon successful completion of this course, students should:

Know the notions of population, sample, types of variables and appropriate method of presenting quantitative information in tables and diagrams.

Learn the axioms and rules of probability both as proportion of items having particular characteristics and as the longrun proportion of times events occur,. Students will be able to apply various counting techniques in order to evaluate probability.

Become familiar with description and properties of frequently used discrete and continuous random variables to model various applied phenomenon.

Learn the notion of sampling distribution of a statistic as a thought experiment of obtaining values of the statistic by repeated independent sampling.

By a logical inversion of ideas from sampling distribution estimate population characteristics based on random samples, and develop an appreciation for the random error inherent in such estimation by constructing confidence intervals.

Depending on the nature of the variable, learn the proper approach to establishing or refuting proposed scientific hypotheses through statistical tests.

Recognize the central role of statistical significance in comparing two or more subpopulations, in relation between two or more variables (continuous or discrete).
Topics:
The following outline is a week by breakdown of topics. There are 2 periods per week (1 period = 75 class minutes), for a 15week semester. Some periods are saved for challenging problem solving through group activities. However, the instructor may use these period to cover additional lecture or discussion topic depending on his/her own interest and the need of the students.

Types of variables, descriptive statistics, presenting summary data in tabular and graphical forms. Includes computer demonstration.

Probability axioms, properties and interpretation. Counting techniques.

Conditional probabilities, independence. Challenging problem solving through group engagement.

Discrete random variables, their interpretations and applications.

Continuous random variables, their interpretations and applications.

Joint probability distributions. More problem solving through group engagement.

Random samples, sampling distributions, functions of random variables and their properties.

Review and Examination.

Point estimation concepts and illustrations for single samples. Estimation of the mean of a normal population and proportion in a dichotomous population.

Hypotheses test concepts and illustrations for single samples. Tests about the mean of a normal population and proportion in a dichotomous population.

Point estimation, confidence intervals and hypotheses tests concerning two samples – paired and independent.

Comparison of more than two samples classified by one or two factors.

The simple linear regression model. Estimation of model parameters and prediction. Correlation.

Goodnessoffit tests for oneway and twoway layouts of discrete (or discretized) variables.

Review and examination.
Computer Usage: The instructor may use a computer in the class to illustrate some statistical applications and simulation results to justify theorems whose proofs are beyond the scope of the course.
Laboratory Projects: No projects are assigned. However, the students are encouraged to use the MINITAB, Excel and other packages available at the Department of Mathematical Sciences computer laboratory.
Evaluation Methods: Homework, quizzes, midterm and final exams.
Professional Component: Mathematics and Physical Sciences
Prepared By: Jyotirmoy Sarkar
Revised: November 07, 2003
Elective: ECE 302 Probabilistic Methods in Electrical Engineering
(one of the three Statistics and Probability electives)
Catalog Description: Credit 3. Class 3.
An introductory treatment of probability theory including distribution and density function, moments and random variables. Applications of normal and exponential distributions. Estimation of means, variances. Hypothesis testing and linear regression. Introduction to random processes, correlation functions, spectral density functions, and response of linear systems to random inputs.
