Through discussion of approximately 50 news articles, learn basic principles of statistics. This course focuses on the relevance, interpretation and usage of statistics in the news media. It has no quantitative prerequisites and involves more reading than math aptitude. Statistics deals with the study of variability, uncertainty, and decision-making, and has applicability to most other disciplines and everyday life. NOTE: This course fulfills the Quantitative Literacy (GQ) requirement for students under GenEd and a Quantitative Reasoning (QA or QB) requirement for students under Core.

Course Attributes: GQ Repeatability: This course may not be repeated for additional credits. This is a beginning course in probability and statistics with special emphasis on the critical analysis of games of chance. The objectives of the course are to introduce several quantitative concepts with real-life applications. These applications are related to situations that involve fallacies in reasoning, equity markets and games of chance.

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NOTE: This course fulfills the Quantitative Literacy (GQ) requirement for students under GenEd and a Quantitative Reasoning (QA or QB) requirement for students under Core. Course Attributes: GQ Repeatability: This course may not be repeated for additional credits. Fundamentals of mathematics and Excel are necessary for a student to pursue their degree at the Fox School of Business and Management. Topics and illustrations are specifically directed to applications in business and economics throughout this course.

The overarching theme of this class is to solidify foundational quantitative and Excel skills and use those skills to solve relevant business applications. Field of Study Restrictions: Must be enrolled in one of the following Fields of study: Accounting, Actuarial Science, Business Management, Business Basics, Economics, Entrprnrship & Innovation Mgt, Entrepreneurship, Finance, Financial Planning, Horticulture, Human Resource Management, International Business, Law & Business, Legal Studies, Management Information Systems, Marketing, Pre Business, Real Estate, Risk Management and Insurance, Supply Chain Management, Statistical Sci + Data Analyt, Undeclared-Business & Mngt, Undeclared-University Studies. Course Attributes: QA Repeatability: This course may not be repeated for additional credits. Pre-requisites: to 0702 Required Courses:1 Minimum Grade of C- May not be taken concurrently OR STA1 Y May not be taken concurrently OR STA2 Y May not be taken concurrently OR MATH 1011 Minimum Grade of C- May not be taken concurrently OR Minimum Grade of C- May not be taken concurrently OR ST1A Y May not be taken concurrently OR ST2A Y May not be taken concurrently. Fundamentals of mathematics and Excel are necessary for a student to pursue their degree at the Fox School of Business and Management. Topics and illustrations are specifically directed to applications in business and economics throughout this course.

The overarching theme of this class is to prepare students to be proficient in areas of quantitative analysis, and to use those skills to solve relevant business applications. The course will also include broader and deeper applications of the topics from.

Excel will be used to reinforce topics and present solutions. Field of Study Restrictions: Must be enrolled in one of the following Fields of study: Accounting, Actuarial Science, Business Management, Economics, Entrprnrship & Innovation Mgt, Entrepreneurship, Finance, Financial Planning, Human Resource Management, International Business, Law & Business, Legal Studies, Management Information Systems, Marketing, Pre Business, Real Estate, Risk Management and Insurance, Supply Chain Management, Statistical Sci + Data Analyt, Undeclared-Business & Mngt, Undeclared-University Studies. Course Attributes: QB Repeatability: This course may not be repeated for additional credits. Pre-requisites: Minimum Grade of C- May not be taken concurrently OR Minimum Grade of C- May not be taken concurrently OR STA2 Y May not be taken concurrently OR STT2 Y May not be taken concurrently OR ST2A Y May not be taken concurrently. Continuation of Statistics 1001 (C011).

Introduction to Differential and Integral Calculus. Topics include functions and graphs, differentiation of polynomial, logarithmic, exponential, and rational functions. Higher order derivatives with applications, maximum and minimum, break-even analysis and market equilibrium. Integration: antiderivative and the definite integral with applications to marginal analysis and other problems in business and economics. Use of a graphic calculator. NOTE: (1) Math C075 (taken prior to Summer 2007 session) and some other higher level Math courses can substitute for Statistics 1902.

Please check with your academic advisor when making your course selection. (2) This course can be used to satisfy the university Core Quantitative Reasoning B (QB) requirement. Although it may be usable towards graduation as a major requirement or university elective, it cannot be used to satisfy any of the university GenEd requirements. See your advisor for further information.

(3) Prior to fall 2014, the title of was 'Honors Calculus for Business.' Field of Study Restrictions: Must be enrolled in one of the following Fields of study: Accounting, Actuarial Science, Business Management, Economics, Entrprnrship & Innovation Mgt, Entrepreneurship, Finance, Financial Planning, Human Resource Management, International Business, Law & Business, Legal Studies, Management Information Systems, Marketing, Real Estate, Risk Management and Insurance, Supply Chain Management, Statistical Sci + Data Analyt, Undeclared-Business & Mngt, Undeclared-University Studies. Cohort Restrictions: Must be enrolled in one of the following Cohorts: SCHONORS, UHONORS, UHONORSTR. Course Attributes: HO, QB Repeatability: This course may not be repeated for additional credits.

Pre-requisites: Minimum Grade of C- May not be taken concurrently OR Minimum Grade of C- May not be taken concurrently OR STA2 Y May not be taken concurrently OR STT2 Y May not be taken concurrently OR ST2A Y May not be taken concurrently. This course will cover the fundamentals of data description, data analysis, and graphical methods with applications to business problems.

Topics include random variables, discrete and continuous distributions, estimation of parameters, and hypothesis testing. Students will gain proficiency in simple and multiple regression models and forecasting.

Excel will be used for data analysis and to reinforce topics taught in class. Statistics 2104 is a one credit hour course that covers probability rules, joint and conditional probability, inference, confidence intervals, hypothesis tests, two sample design, simple linear regression, inference for regression, and multiple regression. NOTE: This course is designed for transfer students who have successfully completed a 3 credit hour introductory statistics course. This one credit hour course will bridge the gap between a 3 credit hour introductory statistics course taken at another institution, and the 4 credit hour Statistics 2103 (Business Statistics) course at Fox.

Prior to fall 2014, the title of was 'Selected Topics in Business Statistics.' Repeatability: This course may not be repeated for additional credits. This course will cover topics in linear algebra, matrix theory, advanced calculus, optimization and numerical techniques. This course will allow students to acquire knowledge necessary in understanding concepts in statistical theory and methods. Students will apply quantitative analysis, critical thinking and interpretation to real-life problems in diverse areas, like business, engineering, healthcare, etc. Repeatability: This course may not be repeated for additional credits. Pre-requisites: ( Minimum Grade of C May not be taken concurrently) AND ( Minimum Grade of C May not be taken concurrently). Copy Of Remove Wat Win7 on this page.

This course covers the basics of statistical estimation theory, in preparation for further study in regression, time series analysis, and forecasting (as tested on the SOA/CAS Course 4 professional examination). Topics include: classical point estimation methods; construction of confidence intervals; tests of statistical hypotheses; and basic analysis of categorical data. NOTE: This course replaces the Statistics 2102 (0022) Business Core requirement for Actuarial Science majors. Field of Study Restrictions: Must be enrolled in one of the following Fields of study: Accounting, Actuarial Science, Business Management, Economics, Entrprnrship & Innovation Mgt, Entrepreneurship, Finance, Financial Planning, Human Resource Management, International Business, Law & Business, Legal Studies, Management Information Systems, Marketing, Real Estate, Risk Management and Insurance, Supply Chain Management, Statistical Sci + Data Analyt, Statistics, Undeclared-Business & Mngt. Repeatability: This course may not be repeated for additional credits. Pre-requisites: Minimum Grade of C- May not be taken concurrently OR Minimum Grade of C- May not be taken concurrently OR Minimum Grade of C- May not be taken concurrently OR Minimum Grade of C- May not be taken concurrently OR Minimum Grade of C- May not be taken concurrently. This course presents practical applications of statistical methods using software.

The emphasis is on giving students experience in solving real life problems using appropriate statistical methods. Statistical techniques studied include organization and presentation of data, statistical testing, multiple regression, Chi-Square tests and logistic regression.

Case studies and projects, with applications, are used to show the application of statistical methods to business problems. Through this course students should be able to select, utilize and apply quantitative statistical methods to real life problems, and get familiar with data analysis using statistical software. The main statistical software we use is SPSS. Students will also be exposed to other packages, such as Excel and R. Field of Study Restrictions: Must be enrolled in one of the following Fields of study: Accounting, Actuarial Science, Business Management, Economics, Entrprnrship & Innovation Mgt, Entrepreneurship, Finance, Financial Planning, General Business Studies, Human Resource Management, International Business, Law & Business, Legal Studies, Management Information Systems, Marketing, Real Estate, Risk Management and Insurance, Supply Chain Management, Statistical Sci + Data Analyt, Statistics, Undeclared-Business & Mngt. Repeatability: This course may not be repeated for additional credits.

This course presents the principal applications of sample surveys, survey design, criteria of a good sample design, and characteristics of simple random sampling, stratified random sampling, and cluster sampling. Case studies are used where appropriate to illustrate applications of survey sampling. Emphasis will be placed on both the theory and methodology of surveying and include sampling principles, sample design, questionnaire construction, and response problems. Field of Study Restrictions: Must be enrolled in one of the following Fields of study: Accounting, Actuarial Science, Business Management, Economics, Entrprnrship & Innovation Mgt, Entrepreneurship, Finance, Financial Planning, General Business Studies, Human Resource Management, International Business, Law & Business, Legal Studies, Management Information Systems, Marketing, Real Estate, Risk Management and Insurance, Supply Chain Management, Statistical Sci + Data Analyt, Statistics, Undeclared-Business & Mngt. Repeatability: This course may not be repeated for additional credits. The first part of this course provides students with insight into statistically designed experiments and related topics. The course covers the fundamental statistical concepts required for designing efficient experiments to answer real questions.

The fundamental concepts of replication, blocking, and randomization are examined. Topics covered include block designs, balanced incomplete block designs, and Latin Square designs. Additional topics include factorial experiments, fractional factorial designs, and orthogonal arrays. The course also introduces students to response surface methodology, mixture designs, and conjoint analysis. Quality improvement can be accomplished using experimental design principles. Download Fox Float Rp23 Manual Treadmill here.

The second part of the course covers the core principles of the management of quality in the production of goods and services. Statistical quality control techniques are used in the implementation of these principles. Topics covered include control charts, cusum procedures, and Taguchi methods. Field of Study Restrictions: Must be enrolled in one of the following Fields of study: Accounting, Actuarial Science, Business Management, Economics, Entrprnrship & Innovation Mgt, Entrepreneurship, Finance, Financial Planning, General Business Studies, Human Resource Management, International Business, Law & Business, Legal Studies, Management Information Systems, Marketing, Real Estate, Risk Management and Insurance, Supply Chain Management, Statistical Sci + Data Analyt, Statistics, Undeclared-Business & Mngt. Repeatability: This course may not be repeated for additional credits. This course provides students with the fundamental concepts and tools needed to understand the role of statistics and business analytics in organizations.

It covers basic descriptive statistics, probability, and statistical inference. Topics include probability distributions, random sampling and sampling distributions, point and interval estimation, and hypothesis testing.

The course also covers hypothesis testing for several populations, correlation, simple linear regression, multiple regression, and an introduction to data mining. Use of Excel for data analysis and inference.

NOTE: This course is a four credit hour course which will substitute for Statistics 2101 (C021) and 2102 (0022) for Fox School students. Prior to fall 2014, the title of was 'Honors Business Statistics.'

Not to be taken by School of Business and Management students; open only to Engineering students. Descriptive statistics, inference, regression and correlation, and experimental design. Engineering applications. College Restrictions: Must be enrolled in one of the following Colleges: Business & Mngmnt, Fox School.

Repeatability: This course may not be repeated for additional credits. Pre-requisites: Minimum Grade of C- May not be taken concurrently OR Minimum Grade of C- May not be taken concurrently OR MATH 1038 Minimum Grade of C- May not be taken concurrently. The course covers a variety of statistical methods useful in interdisciplinary research, such as simple and multiple regression analysis, ANOVA, analysis of covariance, logistic regression, and predictive models.

Emphases are placed on rationales, assumptions, techniques, and interpretation of results from computer packages. Repeatability: This course may not be repeated for additional credits. Topics will be chosen from multiple regression, forecasting, and time series. Standard statistical packages will be introduced and used extensively. The course will emphasize applications in business such as financial forecasting, production management, and actuarial science. This course has been approved by the Society of Actuaries/Casualty Actuarial Society for VEE - Applied Statistical Methods.

Completion of this course with a minimum grade of B- is required for VEE - Applied Statistical Methods credit. Field of Study Restrictions: Must be enrolled in one of the following Fields of study: Accounting, Actuarial Science, Business Management, Economics, Entrprnrship & Innovation Mgt, Entrepreneurship, Finance, Financial Planning, Human Resource Management, International Business, Law & Business, Legal Studies, Management Information Systems, Marketing, Real Estate, Risk Management and Insurance, Supply Chain Management, Statistical Sci + Data Analyt, Statistics, Undeclared-Business & Mngt. Repeatability: This course may not be repeated for additional credits. This time series analysis and forecasting models course with interdisciplinary applications covers important univariate and multivariate time series methods, including ARIMA models, further forecasting methods (logistic regression, ARIMA), centered and training Moving Average (MA). Students will apply the body of theoretical knowledge to analyzing real-life data sets.

Repeatability: This course may not be repeated for additional credits. This course is an introduction to programming for statistical analysis using the SAS Software System. Students will learn data set creation by data transformation to/from SAS using Import and Export functions. Concatenation, merging and subsetting data, as well as data restructuring and new variable construction using arrays and SAS functions will be taught.

Simple procedures to clean and perform quality control of data, as well as procedures for calculating descriptive statistics, plots, and print outs will be covered. Laboratory exercises and homework assignments include brief exercises as well as manipulation and analysis of real data sets. Repeatability: This course may not be repeated for additional credits. This course covers estimation and testing of hypotheses when the functional form of the population distribution is not completely specified. The topics also include sampling models and analyses for discrete data: Fisher's exact test, logistic regression, ROC analysis, log-linear models and Poisson regression, conditional logistic regression, Cochran-Mantel-Haenszel test, measures of agreement between observers, quasi-independence, multinomial logit models, proportional odds model, association models, generalized estimating equations (GEE). Students work with R and SAS throughout the semester.

Repeatability: This course may not be repeated for additional credits.