麻豆社区app

Basic concepts of analytical geometry, limits and derivatives, differentials and rates, integration, definite and indefinite integrals, differentiation of logarithmic and exponential functions. Prerequisite: MATH1350 (0 Units)

A course emphasizing the empirical and scientific approaches to disciplines involved in statistical and data analytics sciences. Students learn the historical foundation of each departmental program area. Students will also familiarize themselves with the perspectives and specialties of our department faculty while systematically and critically reviewing the expanding roles of data-centric sciences. The course focuses on teaching, writing, developing a future internship, exploring potential graduate work, and engaging in professional associations from a Christian worldview. Note: This course is designed to introduce students in statistics-related majors (Applied Statistical Analysis, Statistics and Data Analytics, Actuarial Science, Sports Analytics, etc.) to the discipline. It is not designed as a major or general education course in statistics and does not fulfill the 'introduction to statistics' requirement for any major. (1 Units)

Mathematical theory and applications, development of formulae, principles of statistical decision theory, descriptive measurements, probability concepts, random variables, normal distribution, inferential statistics, sampling distributions, confidence intervals, hypothesis testing, chi-squared procedures, linear regression, and the use of computers in statistics. (3 Units)

This course represents a basic concepts and methodology course in regression analysis using application of general linear regression models to real-life situations. Case studies are used to give practice in diagnosing practical problems, deciding on appropriate models, and knowing which inferential technique will answer the researcher's questions for the purposes of description and prediction. Regression models and model building typical of problems used in the social and behavioral sciences, the natural and health sciences, and many other disciplines are covered. Prerequisite: MATH2450 or STAT1440 (3 Units)

A continuation of Statistical Computing I using comprehensive and widely available tools like SAGE, SPSS, SAS and R. Advanced techniques will be covered including (but not limited to) numerical linear algebra, optimization and nonlinear equations, the EM algorithm, Laplace approximations, quadrature methods, simulation methodology, sampling, Monte Carlo and bootstrap methods. Prerequisite: STAT2100 (3 Units)

An introduction to data mining, management and statistical programming techniques using comprehensive and widely available tools like SAGE, SPSS, SAS and R. Students learn exploratory data analysis, coding and manipulation of variables, database management applying statistical concepts. Modeling and simulation experiments on a variety of applied data sets. Prerequisite: STAT1440 (3 Units)

This course studies experimental designs with corresponding models and analyses critical for students in the empirical sciences. Course topics include estimation, test of hypothesis, analysis of variance and a variety of topics in experimental design. Decisions and practical considerations which minimize experimental error and avoid confounding results are dealt with in real life contexts. Prerequisite: STAT1440 (3 Units)

This course provides the tools to create and critically evaluate data visualizations. Focus will be on statistical graphics, graphics that display statistical data. Additionally, recent advances in the field of information visualization will be covered. Prerequisite: MATH2450 or STAT1440 (3 Units)

A course to introduce statistical models of advanced least squares regression and standard ANOVA techniques and extensions to categorical data. Students will conceptually understand linear mixed effects models, log linear and generalized linear models for count data; and survival models for the analysis of lifetime data. In addition, students will apply these models to real data, to discern patterns and conclusions, and present their results. Prerequisite: STAT2100 (3 Units)

A course in application of parametric and nonparametric single and multivariable data analytic techniques to sports. Topics will include: linear regression, correlation, confounding and interactions, variable selection, categorical predictors and outcomes, logistic regression, factor analysis, discriminant analysis, and regression techniques with longitudinal data. Prerequisite: STAT2100 (3 Units)

This course enables students to examine theory and applications of data science and analytics to the field of sports performance, administration, and player rehabilitation. Students will evaluate evidence based literature related to statistical analysis to determine whether a published study has reliable results which can be used in translating evidence to practice. Topics may include aspects of sports strategy, team and player performance, teach and franchise management, officiating and refereeing, coaching and training issues, fan support and marketing, fantasy competitions, and contemporary topics of metrics and technology use (limitations and extensions). (1 Units)

This course is aimed at developing "hands on" experience in data and visualization analytic skills in the context of involvement with a sport team, league, or corporation. Students will assist in the development of the analytical and data collection capabilities of the organization. (1 Units)

The course is designed to be a culminating experience for senior students. The course gives students through writing, seminar and conference participation, an opportunity to demonstrate their skill and proficiency in the field of statistics. In some cases, this may be coupled with internships. (1 Units)

This course is designed for professional nursing and general college students. Included are a general survey of human histology and the study of structure and function of organ systems of the human body, including the integumentary, skeletal, muscular, endocrine, and nervous systems. Structure and function of sensory organs are also included in the course. Should be taken with Anatomy and Physiology I Lab . (3 Units)

A laboratory experience designed to illustrate and reinforce topics covered in BIO 153 Anatomy and Physiology I. Included is the detailed study of cells, tissues, the structure and function of the skeleton, the muscles, and the nervous and endocrine systems of the human body using laboratory experience and demonstration. Prerequisite: BIOL1530 (1 Units)

A study of the muscle and bone structure of the human body and how they work together to create movement. Emphasis is on the function of specific muscles and bones in creating defined movement. Prerequisite: BIOL1530, BIO153 (3 Units)

A course providing instruction and experience in the prevention and care of injuries incurred in 麻豆社区apps. Methods of taping, therapy, health habits, and protective equipment are considered. Prerequisite: KINE2530, KIN264 (3 Units)

A study of the sociological and psychological impact of physical activity on humans. The psychological factors of self-perception, motivation, cooperation, and competition will be examined and used as descriptors to illustrate the idea of sport as an institution of society. (0 Units)

This course is designed to develop an understanding of measurement and evaluation concepts. Measurement and evaluation topics relevant to construction and use of assessment in the psychomotor, cognitive and affective domains will be covered. Class activities include collection, analysis of data, and evaluation of instruments for personal and program evaluation. (3 Units)

A study of basic management principles and their application to the field of sport. (0 Units)

This course is an examination of sport organizations focused on both professional and amateur governance structures and processes. The study of policy in educational, non-profit, professional and international sport venues will also be addressed. (0 Units)

A study of the sociological and psychological impact of physical activity on humans. The psychological factors of self-perception, motivation, cooperation, and competition will be examined and used as descriptors to illustrate the idea of sport as an institution of society. (0 Units)

Sampling theory and practice are presented in this course through a study of simple random samples, stratified random samples, cluster sampling, estimating sample size, ratio estimates, subsampling, two-state sampling and analysis of sampling error. This is a critical course for students in education and the social, medical, biological and management sciences where sampling is a fundamental step in virtually every statistical procedure and critical to meaningful survey research. Prerequisite: STAT1440 (3 Units)

This course is designed to develop an understanding of measurement and evaluation concepts. Measurement and evaluation topics relevant to construction and use of assessment in the psychomotor, cognitive and affective domains will be covered. Class activities include collection, analysis of data, and evaluation of instruments for personal and program evaluation. (3 Units)