Data Analytics

Skip Sub Menu

Courses

Courses for the Major Core and Minor:

Computer Science Courses

Information Systems Courses

Mathematics Courses

Statistics Courses


Computer Science Courses

CS 065: INTRODUCTION TO COMPUTER SCIENCE I, 3 credit hrs.
Algorithms, programming, program structures and computing systems. Debugging and verification of programs, data presentation. Computer solution of problems using a high- level language. Prereq.: Four years of high school mathematics or MATH 020.

CS 066: INTRODUCTION TO COMPUTER SCIENCE II, 3 credit hrs.
Continuance of CS 65 using a block-structured language and emphasizing data abstraction. More general data structures and alternative implementations of them are used in programs, Sorting, searching and tree traversal algorithms are used and analyzed. Provides preparation for further study in computer science. Prereq: CS 065 or equivalent

CS 083: COMPUTER ETHICS, 3 credit hrs.
This course increases understanding of issues related to ethics, professional conduct and social responsibility as they arise in Computer Science and applications of Information Technology. Additionally, the course serves to develop 1) the ability to think clearly; 2) habits of professional responsibility and behavior; and 3) effective writing and presentation skills. Students are exposed to the history of the discipline from a social point of view, and to various frameworks from which ethical and professional decisions must be made within the discipline. Sophomore, junior, or senior standing required.

CS/BIO 116: BIOINFORMATICS, 3 credit hrs.
The analysis of biological systems through the use of computational methods. Analyzing these systems often involves creating electronic databases of biological structures (protein sequences, genomes, DNA, etc.) and developing algorithms to analyze the data. Prereq.: CS 065 or consent of instructor.

CS 137: DATA STRUCTURES AND ALGORITHM ANALYSIS, 3 credit hrs.
Formal and informal methods for analyzing the correctness and efficiency of algorithms. Implementation and analysis of advanced algorithms and data structures such as AVL trees, B-trees, hash-tables, heaps, and graph algorithms. Introduction to complexity theory and NP-Completeness. Prereq.: CS 66 and (MATH 054 or MATH 101).

CS 143: ARTIFICIAL INTELLIGENCE, 3 credit hrs.
Introduction to the theory, tools and methods of artificial intelligence. Topics include knowledge representation, predicate calculus, basic data structures, and problem solving strategies. A symbol manipulation language is used. Computer science aspects of artificial intelligence are emphasized. Applications from areas such as natural language understanding, vision or expert systems are examined. Prereq.: CS 066.

CS/MATH 165: INTRODUCTION TO NUMERICAL ANALYSIS, 3 credit hrs.
A practical introduction to numerical computing. The primary focus is the concepts and tools involved in modeling real continuous mathematical or engineering problems on the digital computer. The effects of using floating point arithmetic, error analysis, iterative methods for solving equations, and numerical integration and differentiation will be studied. Prereq.: CS 065, MATH 080 and 100.

CS 167: MACHINE LEARNING, 3 credit hrs.
This course introduces approaches to developing computer programs that learn from data. Both foundational and contemporary machine learning algorithms will be covered in the context of a variety of data and problem types. Specific topics will vary but may include artificial neural networks, decision trees, instance-based learning, Bayesian learning, support vector machines, hidden Markov models, reinforcement learning, and natural language processing. Students will develop their own implementations of the algorithms as well as utilize modern machine learning software and programming libraries. Pre-requisite: CS 066.

CS 178: CLOUD COMPUTING AND DATABASE SYSTEMS 
Data sets have become so large and complex that a new set of software tools must be developed in order to facilitate questions that can lead to impactful insights. This course will provide an in-depth study of tools and techniques used to process 'big data' stored on multiple computers. Topics include virtualization, python programming, the Hadoop ecosystem, MapReduce programming, Amazon Web Services, database querying including SQL and NoSQL programming.

CS 190: CASE STUDIES IN DATA ANALYTICS, 3 credit hrs.
In this course, students will apply descriptive, predictive, and prescriptive data analysis methods learned in previous courses to new cases. Students will learn to effectively manage long-term data analysis projects within diverse teams through a complete data analytics project lifecycle and compellingly communicate outcomes through writing and oral presentations which include appropriate use of data visualizations. Credits: 3. Pre-requisites: (1) CS 066, (2) STAT/MATH 130 or ACTS/MATH 131, and (3) two of STAT 170, STAT 172, CS 167, CS 178. 


Information Systems Courses

IS 044: Microsoft Office Tools for Business Analysis, 3 credit hrs.
Microsoft Office Tools for Business Analysis. Students will become proficient in the use of software for communication and presentation of text and data using Microsoft Office Suite Tools. This course explores the use of technology and application software for solving business problems, both analytic and organizational in nature. The course uses the most current Microsoft Office application suite, including Word, Excel and PowerPoint. Topics include the use of financial, logical, and time functions in creating worksheets and the use of Pivot tables and charts in analyzing and presenting data. Topics also include how to use technology reliably and safely to avoid data loss and to avoid potential security compromises with an emphasis on ethical practices with regard to data and privacy issues. With all topics, there will be an emphasis on problem solving where the tools are used to create desired solutions. Prereq.: MATH 020 or equivalent college algebra course, knowledge of basic software tools including word processing, email, Internet browsers, and presentation software.

IS 160: DATABASE MANAGEMENT, 3 credit hrs.
A study of database concepts and technologies used in managing and using data within modern organizations: defining data needs; using modern database tools; understanding database design; and creating applications. Prereq.: IS 044 or CS 065.


Mathematics Courses

MATH 028: BUSINESS CALCULUS, 3 credit hrs.
Brief algebra review, data analysis, limits, derivatives, integration, applications to business. Prereq.: MATH 020 or equivalent.

MATH 050: CALCULUS I, 4 credit hrs.
Functions; continuity; limits; differentiation; applications of derivatives; definite integrals; Prereq: Math 20 or equivalent.

MATH 070: CALCULUS II, 4 credit hrs.
Definite integrals; techniques of integration; applications of definite integrals, infinite series and sequences; power series; Taylor series. Prereq: Math 50.

MATH 080: LINEAR ALGEBRA, 3 credit hrs.
Systems of linear equations; vectors, linear independence, linear transformations; matrix operations, inverse of a matrix, determinants; null and column space of a matrix, rank; general vector spaces, basis of a vector space, dimension; eigenvalues and eigenvectors, diagonalization, orthogonality; applications. Prereq.: MATH 050.

MATH 100: CALCULUS III, 4 credit hrs.
Plane curves; vectors; limits, continuity and differentiation for functions of several variables; multiple integrals. Prereq.: Math 70

MATH 120: APPLIED DIFFERENTIAL EQUATIONS I, 3 credit hrs.
Ordinary differential equations; systems of differential equations. Fourier series, integrals and harmonic analysis, partial differential equations, orthogonal functions. Bessel functions. Legendre functions. Prereq.: MATH 080, 100.

MATH 121: APPLIED DIFFERENTIAL EQUATIONS II, 3 credit hrs.
Continuance of MATH 120. Prereq.: MATH 120.

MATH 125: MATHEMATICAL MODELING, 3 credit hrs.
The construction, analysis and interpretation of mathematical models. Examples are drawn from a variety of areas. Student projects are required. Prereq.: MATH 070, 080.

MATH 127: INTRODUCTION TO GAME THEORY, 3 credit hrs.
Game Theory is the logical analysis of situations of conflict and cooperation. Topics will include zero-sum games and non-zero-sum two-person games, n person games, applications to economics, politics and nature. Prereq.: MATH 028 or MATH 050 or consent of instructor.

STAT/MATH 130: PROBABILITY FOR ANALYTICS, 3 credit hrs.
An introduction to the concepts of probability that form the foundation for analytics practice. Descriptive statistics, data visualization, univariate discrete and continuous probability distributions, confidence intervals and one-sample hypotheses testing. Applies R and/or SAS skills. Prereq.: MATH 070 and STAT 040.

MATH/CS 165: INTRODUCTION TO NUMERICAL ANALYSIS , 3 credit hrs.
Error analysis, iterative methods for solving nonlinear equations, direct and iterative methods for solving linear systems, approximation of functions, derivatives, integrals. Prereq.: CS 065, MATH 080 and 100.

MATH 176: ADVANCED LINEAR ALGEBRA, 3 credit hrs.
Hermitian, unitary, normal, positive definite and nonnegative matrices; LU, QR and Choleski factorizations; equivalence, similarity, congruence and their respective canonical forms; norms; Schur triangular form, Jordan canonical form; applications. Prereq.: MATH 101.


Statistics Courses

STAT 040: R and SAS, 3 credit hrs.
This course will cover how to access, structure, format, manipulate and archive data using R and SAS. It will include topics in data inputting, merging files, cleaning data, data summary, descriptive statistics, running procedure statements, graphical presentation of data, loops, if/then statments, and creating your own scripts and functions that extend the language. Prereq.: MATH 020 or equivalent college algebra course, knowledge of basic software tools including word processing, email, Internet browsers, and presentation software. Course is for the Data Analytics major or minor, or the Actuarial Science major.

STAT 060: STATISTICS FOR THE LIFE SCIENCES, 3 credit hrs.
An introduction to statistical methods used in the life sciences. In this course the student will develop the ability (1) to decide which techniques to use to solve particular problems, (2) to use basic statistical tools to address questions, and (3) to explain statistical results to others. At the end of the course the student should understand how to: (1) display and describe distributions, (2) display and examine relationships between variables, (3) design samples and experiments, (4) determine probabilities and use probability distributions, (5) conduct significance tests associated with means and proportions, and (6) significance tests associated with two-way tables, and one-way ANOVA. Prereq.: MATH 020 or equivalent. For life science, health science, and pharmacy majors only. 

STAT 071: STATISTICS I, 3 credit hrs.
An introduction to descriptive and inferential statistics; frequency distributions; measures of central tendency and spread; confidence intervals; large and small sample tests of significance; probability; and binomial and normal distributions. Prereq.: MATH 020 or MATH 028 or equivalent.

STAT 072: STATISTICS II, 3 credit hrs.
Continuance of STAT 071 with further tests of significance; analysis of variance; correlation and regression; and contingency table analysis. Prereq.: STAT 071, STAT 130, or ACTS 131, and also IS 044. 

STAT/MATH 130: PROBABILITY FOR ANALYTICS, 3 credit hrs.
An introduction to the concepts of probability that form the foundation for analytics practice. Descriptive statistics, data visualization, univariate discrete and continuous probability distributions, confidence intervals and one-sample hypotheses testing. Applies R and/or SAS skills. Prereq.: MATH 070 and STAT 040.

STAT 135: MATHEMATICAL STATISTICS, 3 credit hrs. (new course)

STAT 170: STATISTICAL MODELING AND DATA ANALYSIS II, 3 credit hrs.
Regression and time analysis. Specific topics include simple and multiple regressionl multicollinearity; heteroscedasticity; diagnostics; forecasting with the regression model; binary and multiple-choice models; autocorrelation; random walks; ARIMA models; minimum mean-square-error forecasts and confidence intervals. Prereq.: STAT 040 and one of (STAT 072, STAT 130, ACTS 135 or ACTS 141).

STAT 172: GENERALIZED LINEAR MODELS AND DATA MINING, 3 credit hrs.
Data Mining and Generalized Linear Modeling - The emphasis will be on data analysis, statistical assumptions, and diagnostics. Topics include: Linear Regression, Logistic and Probit Regression, CART, Neural Networks, Association Rules, Clustering, Generalized Linear Models, Models for Continuous Data, Models for Binary Data, Models for Polytomous data, Log-Linear Models, Conditional Likelihoods, and Gamma Regression. Prereq.: STAT/MATH 130 or ACTS/MATH 131; STAT 040; and MATH 070.

STAT/CS 190: 3 credit hrs.
In this course, students will apply description, predictive, and prescriptive data analysis methods learned in previous cases to new cases. Students will learn to effectively manage long-term data analysis projects within diverse teams through a complete data analytics project lifecycle and compellingly communicate outcomes through writing and oral presentations which include appropriate use of data visualizations. Prereq.: CS 066, STAT/MATH 130 or ACTS/MATH 131, and two of STAT 170, STAT 172, CS 167 or CS 178.


Actuarial Science Courses for Specialty in Casualty or Life

ACTS 120: THEORY OF INTEREST, 3 credit hrs.
Measurement of interest; solution of interest problems; basic and general annuities; yield rates; amortization schedules and sinking funds; bonds; yield curves; duration + immunization; stochasic approaches. Prereq.: MATH 070

ACTS 121: INTRODUCTION TO DERIVATIVES, 3 credit hrs.
Derivatives and their use in managing risk; forwards, futures, options, swaps; hedging and speculative strategies based on options; Black-Scholes formula + Option Greeks. Prereq.: STAT 071 or (ACTS 131 concurrent allowed), MATH 028 or higher, FIN 101 or ACTS 120

ACTS 132/MATH 132: INTRODUCTION TO PROBABILITY II, 3 credit hrs.
Continuation of ACTS 131. The POISSON process and its relation to the exponential distributions; frequency and severity with coverage modifications; aggregate loss models and ruin theory. Prereq.: ACTS 131

ACTS 145: DERIVATIVES MATHEMATICS, 3 credit hrs.
Delta hedgingl exotic options; the lognormal model for stock prices; Monte Carlo simulation; Brownian motion and Ito's Lemma; Black-Scholes Equation; implied and historical volatility; interest rate models. Prereqs.: ACTS 121 or FIN 121, and ACTS 131


Bioinformatics Specialty Courses

BIO 012: GENERAL BIOLOGY, 3 credit hrs.
This course covers topics cell biology, biochemistry, and genetics. The labs, which focus on content covered in the lectures, will incorporate the process of inquiry through active learning and the scientific method. Students will have repeated opportunities in the inquiry-based laboratories to develop and test hypotheses, analytically explore the natural world, collect, analyze, and formally present data. Offered fall semesters. No prerequisites. Co-requisite lab BIO 012L. Students who take BIO 012 online in the summer term must still complete the lab section, but may take BIO 012L in the fall term.

BIO 012L: GENERAL BIOLOGY LAB, 1 credit hr.
Co-requisite lab for BIO 012.

BIO 105: INTRODUCTION TO GENETICS, 3 credit hrs.
The principles of heredity and their theoretical and practical applications. Prereq: BIO 001, 012, 013, or 018. Organic Chemistry recommended.

BIO 116: BIOINFORMATICS, 3 credit hrs.
An introduction to the principles, practice, and application of bioinformatics. The focus of the course will be the analysis of biological systems through the use of computational methods. Topics include: sequence alignment, algorithm analysis, genome assembly, and databases. Cross- listed with CS 116.

BIO 165: CELL BIOLOGY, 4 credit hrs.
A comprehensive introduction to molecular cell biology with an emphasis on applications to biology and medicine. Basic structure and chemistry of cells, protein-targeting, cellular signaling, the cytoskeleton, and the cell cycle. Prereq: BIO 001, 012, 013, or 018, or equivalent.

BIO 186: MOLECULAR BIOLOGY, 3 credit hrs.
Introduction to principles, practice, and applications of modern molecular biology. Chemistry of informational macromolecules, mechanism regulation and integration of informational processes in the cell; application to basic biology and medicine. Implications for society. Prereq.: BIO 165 or consent of instructor. Crosslisted with CHEM 134.

BIO 198: INTERNSHIP, 1 to 3 credit hrs.
A forum for a student-initiated and directed study of a biological topic of interest. Must be mentored by a Biology faculty member. Requires completion of an independent study form and approval by the chair.

BIO 199: CAPSTONE, 3 credit hrs.
Topics will vary in different semesters and will focus on the unifying theme of evolution. Students will complete an instructor-approved project requiring analysis and synthesis of a problem involving biological principles pertaining to the course topic. This project will culminate with a written document and an oral presentation of the chosen project. This course is required for completion of the biology major. Prereq.: Enrollment restricted to biology majors with senior standing. Offered fall semester only.


Computational Specialty Courses

CS 137: DATA STRUCTURES AND ALGORITHMS, 3 credit hrs.
Formal and informal methods for analyzing the correctness and efficiency of algorithms. Implementation and analysis of advanced algorithms and data structures such as AVL trees, B-trees, hash-tables, heaps, and graph algorithms. Introduction to complexity theory and NP-Completeness. Prereq.: CS 065 and either MATH 054 or MATH/CS 150.

CS 140: INTERNSHIP, 1 to 3 credit hrs.
Students who are in a work environment related to the major field of study may receive credit for applications of classroom knowledge to their job. The student meets regularly with the adviser to determine appropriate assignments. May be repeated up to a maximum of eight hours of credit.(Graded on a credit/no credit basis.) Prereq: At least junior standing or consent of instructor.

CS 143: ARTIFICIAL INTELLIGENCE, 3 credit hrs.
Introduction to the theory, tools and methods of artificial intelligence. Topics include knowledge representation, predicate calculus, basic data structures, and problem solving strategies. A symbol manipulation language is used. Computer science aspects of artificial intelligence are emphasized. Applications from areas such as natural language understanding, vision or expert systems are examined. Prereq.: CS 066, 130.

CS 147: GRAPHICS, 3 credit hrs.
Introduction to computer graphics terminology and hardware. Elementary graphics mathematics and algorithims. Prereq.: CS 066.

CS 160: OPERATING SYSTEMS, 3 credit hrs.
Introduction to the design, development and implementation of operating systems. Problems of resource allocation, concurrency file systems design, networking and the interface between hardware and software. Prereq.: CS 130.

CS/MATH 165: INTRODUCTION TO NUMERICAL ANALYSIS, 3 credit hrs.
Error analysis, iterative methods for solving nonlinear equations, direct and iterative methods for solving linear systems, approximation of functions, derivatives, integrals. Prereq.: CS 065 MATH 080 and 100. Crosslisted with MATH 165.

CS 188: SOFTWARE ENGINEERING, 3 credit hrs.
Developing sofrware is fundamentally different from writing programs. While programming expertise is a critical skill, the ability to produce software that is useful, usable and accepted by a broad audience requires much more to be successful. This course will expose you to some intracacies of developing Software. We will survey the field of software engineering, convering the life cycle of software, various developmental strategies, requirement analysis, design tools, and testing methodologies. These concepts will be explored in theory as well as in practice: you will gain experience in conceiving, specifying, designing, developing and implementing a reasonably sized software solution.

CS 191: CAPSTONE, 1 credit hr.
The purpose of a capstone is for students to undertake an independent project that applies and synthesizes what they have learned in their major. This course is typically taken in one of the student's final two semesters at Drake. One outcome will be a written project that can take several forms, for example a research paper, a software package, or lesson plans. A second outcome is a presentation of their work to the students and faculty of the department, usually during the last two weeks of the semester.


Electronic Commerce Specialty Courses

IS 074: ADVANCED IT APPLICATIONS FOR BUSINESS, 3 credit hrs.
This course focuses on advanced applications of Microsoft Excel, Microsoft Access, and Visual Basic Applications (VBA) . Emphasis is on integration of advanced data analysis tools and techniques with reporting and presentation tools for solving business problems and presenting results. Prereq.: IS 044 or equivalent.

IS 145: WEBSITE TECHNOLOGY, 3 credit hrs.
An introduction to website technology and programming using the Hypertext Markup Language (HTML) and other website development languages. Emphasis is on using the Web for business content presentation. Topics include content markup, website design and hyperlinks, content organization, style sheets, and multimedia. Prereq.: IS 044 or CS 065

IS 160: DATABASE MANAGEMENT, 3 credit hrs.
A study of database concepts and technologies used in managing and using data within modern organizations: defining data needs; using modern database tools; understanding database design; and creating applications. Prereq.: IS 044 or CS 065.

IS 194: ELECTRONIC COMMERCE, 3 credit hrs.
A study of internet-based electronic commerce. Topics include the information technologies underlying the electronic marketplace, and the impact of e-commerce on content, retail, and service industries, organizational strategy, and society. Prereq.: MGMT 110 and MKTG 101.


Economics Specialty Courses

ECON 001: PRINCIPLES OF MACROECONOMICS, 3 credit hrs.
Principles and institutions of the American economy and their application to contemporary economic problems. Topics include the economic role of government and the banking system, the determination and measurement of national income, and monetary and fiscal policies. The student is expected to have a basic understanding of the use of graphs, fractions and simple algebra.

ECON 002: PRINCIPLES OF MICROECONOMICS, 3 credit hrs.
Topics include the theory of consumer behavior; the economics of the business firm; the theory of production, resource pricing and income distribution; international trade and finance; and comparative economic systems. The student is expected to have a basic understanding of the use of graphs, fractions and simple algebra.

ECON 107: ECONOMETRICS, 3 credit hrs.
Statistical analysis of economic relationships using least- squares regression and related methods. Estimation, confidence intervals, hypothesis tests, and forecasting with cross-section and time-series data. Applications using computers. Prereq.: ECON 001; ECON 002; STAT 072 or STAT 141 or ACTS 141; and MATH 028 or MATH 050.

ECON 173: INTERMEDIATE MICROECONOMIC ANALYSIS, 3 credit hrs.
Principles of price determination applied to the analysis of consumer demand and business supply; production and costs; comparison of various market structures; income distribution; general equilibrium analysis. Elementary knowledge of calculus assumed. Prereq.: ECON 002 and MATH 028.

ECON 174: INTERMEDIATE MACROECONOMIC ANALYSIS, 3 credit hrs.
Consideration of various theoretical approaches to the analysis of aggregate economic behavior, including models of income determination and growth. Elementary knowledge of calculus assumed. Prereq.: ECON 001 and ECON 002 and MATH 028.


Finance Specialty Courses

FIN 101: CORPORATE FINANCE, 3 credit hrs.
A study of the finance function in corporate decision making .Topics include analysis of the time value of money, capital budgeting, risk and return, the acquisition and allocation of capital, and the special problems associated with international financial decision making. Prereq.: ACCT 42, IS 044, STAT 071 or MATH 070, ECON 002, and either MATH 020 or MATH 028.

FIN 102: ADVANCED CORPORATE FINANCE, 3 credit hrs.
This course provides a rigorous re-examination, extension and application of topics covered in FIN 101. Special emphasis is given to capital budgeting complications, real options in a capital budgeting context, capital structure, and dividend policy. Prereq.: FIN 101, MATH 028, STAT 072, and IS 044 or equivalent and FIN 121 (concurrent ok).

FIN 121: INTRODUCTION TO DERIVATIVES, 3 credit hrs.
Derivatives and their use in managing risk; forwards, futures, options, swaps; hedging and speculative strategies based on options; option pricing; Black-Scholes formula + Option Greeks. Prereq.: STAT 071 or (ACTS 131 concurrent allowed), MATH 028 or higher, FIN 101 or ACTS 120.

FIN 193: PORTFOLIO ANALYSIS, 3 credit hrs.
Topics in portfolio selection and management, including the Markowitz E-V efficient model, Sharp Index model, capital market equilibrium, arbitrage pricing, and performance evaluation. Prereq.: FIN 101, FIN 102, and FIN 121.


Insurance Specialty Courses

INS 051: PERSONAL RISK MANAGEMENT, 3 credit hrs.
Risk; various techniques for handling risk include the effective use of insurance; how insurance works; overview of insurance company functions and regulation; basic legal concepts of insurance; insurance products for meeting personal risks, life insurance, health insurance, homeowners insurance, auto insurance and umbrella liability insurance.

INS 141: BUSINESS RISK MANAGEMENT, 3 credit hrs.
Risk management process, identifying risks, alternative techniques for handling business risks; evaluating alternatives; choosing and implementing the best alternative(s); handling business risks with life insurance, employee benefits, and business property-liability insurance.

INS 161: INSURANCE COMPANY OPERATIONS, 3 credit hrs.
Financial aspects; key functions - product design and pricing, marketing, underwriting, reinsurance, claims handling, and investment; external factors affecting insurers in a rapidly changing world.


Marketing Specialty Courses

MKTG 101: MARKETING PRINCIPLES, 3 credit hrs.
Provides a theoretical and practical understanding of the role of marketing in society. The course is focused on managerial decision making regarding markets, products and services, promotion, distribution, logistics, and pricing to satisfy customer needs and institutional goals. Prereq.: ECON 002 and sophomore standing.

MKTG 109: MARKETING AND THE INTERNET, 3 credit hrs.
This class provides a detailed examination of the use of the Internet in marketing by established businesses. Through lectures, case studies, class exercises and projects, the course examines how to use the Web to drive measurable business outcomes such as building brand awareness, delivering product and service information, sales and service support, and quoting and product fulfillment. Prereq.: MKTG 101

MKTG 111: DIRECT AND INTERACTIVE MARKETING, 3 credit hrs.
An introduction to the theory and practice of direct and interactive marketing including mail order, direct response advertising, search engine marketing, lists and database marketing, measurability and accountability, and the cultivation of customers. Emphasis placed on the integration of marketing strategies across multi-channels including those emerging from new technologies. Prereq.: MKTG 101

MKTG 113: MARKETING RESEARCH, 3 credit hrs.
The role of research in providing information for marketing management decision making; problem definition; research designs; sampling procedures; questionnaire design; data acquisition; analysis, interpretation, and presentation of research findings. Prereq.: MKTG 101 and STAT 071 or equivalent, or consent of the Assistant Dean, Graduate Programs, College of Business and Public Administration.

MTKG 130: FIELD APPLICATIONS IN MARKETING, 3 credit hrs.
Students consult an area organization on a marketing research project addressing the organization's goals and objectives. Emphasis on developing an understanding of qualitative marketing research methods and the practical use of both qualitative methods and the quantitative methods presented in MKTG 113. Prereq.: MKTG 101, MKTG 113 and STAT 072.


Mathematics Specialty Courses

MATH 100: CALCULUS III, 4 credit hrs.
Functions; continuity; limits; differentiation; applications of derivatives; definite integrals; techniques of integration; applications of definite integrals; infinite series; plane curves; limits, continuity and differentiation for functions of several variables; multiple integrals. Prereq.: MATH 070.

MATH 120: DIFFERENTIAL EQUATIONS I, 3 credit hrs.
Ordinary differential equations; systems of differential equations. Fourier series, integrals and harmonic analysis, partial differential equations, orthogonal functions. Bessel functions. Legendre functions. Prereq.: MATH 080, 100.

MATH 125: MATHEMATICAL MODELING, 3 credit hrs.
The construction, analysis and interpretation of mathematical models. Examples are drawn from a variety of areas. Student projects are required. Prereq.: MATH 070, 080.

MATH 127: GAME THEORY, 3 credit hrs.
Game theory is the logical analysis of situations of conflict and cooperation. Topics will include zero-sum games and non-zero-sum two-person games, n person games, applications to economics, politics and nature. Pre-requisite: MATH 028 or MATH 050 or consent of instructor.

STAT/MATH 130: PROBABILITY FOR ANALYTICS (new course)
An introduction to probability concepts, including definition of probability; independence; conditional probability; random variables; specific discrete and continuous probability distributions; multivariate random variables; moments and moment generating functions; functions of random variables; sampling distributions; and central limit theorem. Prereq.: MATH 070.

MATH 140: INTERNSHIP, 1 to 3 credit hrs.
Students who are in a work environment related to the major field of study may receive credit for applications of classroom knowledge to their job. The student meets regularly with the adviser to determine appropriate assignments. May be repeated up to a maximum of eight hours of credit. (Graded on a credit/no credit basis). Prereq.: At least junior standing or consent of instructor.

CS/MATH 165: INTRODUCTION TO NUMERICAL ANALYSIS, 3 credit hrs.
Error analysis, iterative methods for solving nonlinear equations, direct and iterative methods for solving linear systems, approximation of functions, derivatives, integrals. Prereq.: CS 065, MATH 080 and 100. Crosslisted with CS 165.

MATH 176: ADVANCED LINEAR ALGEBRA, 3 credit hrs.
Hermitian, unitary, normal, positive definite and nonnegative matrices; LU, QR and Choleski factorizations; equivalence, similarity, congruence and their respective canonical forms; norms; Schur triangular form, Jordan canonical form; applications. Prereq.: MATH 101.

MATH 191: CAPSTONE, 1 credit hr.
The purpose of a capstone is for students to undertake an independent project that applies and synthesizes what they have learned in their major. This course is typically taken in one of the student's final two semesters at Drake. One outcome will be a written project that can take several forms, for example a research paper or a software package. A second outcome is a presentation of their work to the students and faculty of the department, usually during the last two weeks of the semester.


A&S News