| Course Code | CSP4200 |
| Course Title | Data Analysis I: Statistical Concepts and Procedures Using R |
| Description | The purpose of this course is to provide the fundamental background which is necessary for the modeling of biological and environmental data. In an age of limited resources,it is becoming increasingly important to monitor and model wildlife populations and the environment in which they live. Biologists are now asked to utilize efficient sampling design and modeling strategies. Research has shown that effective statistical training involves a high level of interaction among participants and the instructor. The NCTC is well known for its state of the art training facilities and interactive courses. Participants in this course have generally had some basic training in statistics (a course or two in undergraduate or graduate education). Although many participants have such experience, such experience is not necessary for taking this course. We begin the course discussing fundamental principles including random variable types and probability distributions, sampling and population distributions, bias, precision, the Central Limit Theorem, making estimations from samples, and hypothesis testing. Other topics include exploratory data analysis techniques, descriptive statistics (e.g., measurements of central tendency and dispersion), data transformations, power analysis, and univariate parametric and nonparametric inferential statistics: Z-tests, one sample, two sample, and paired T-tests, sign test, Wilcoxon rank sum test, and an introduction to categorical data analysis. Participants will use computers to describe data sets, simulate random variable and sampling distributions, Type I & II error rates, and confidence intervals, perform power analysis of experimental designs, and analyze data using inferential statistical procedures. The general approach is a topic presentation by an instructor, followed by a instructor-led computer exercise, then an “independent” class computer exercise applying the concepts learned on biological data. Participants are encouraged to discuss data in which they are currently engaged with. Although this interaction is encouraged, the purpose of the course is not of a ‘consulting’ nature. |
| Objectives | Statistical methods form the backbone of most approaches to understand data. Consequently, the purpose of this course is to enhance the scientific capacity of participants.Skills gained include thinking from a statistical perspective, increased performance in balancing risks, and improved scientific decision-making.Additional instructional goals are enhanced statistical problem-solving capabilities, more efficient communication with statisticians, more in-depth assessment of reports and studies in the literature, and strengthened aptitude to continue developing statistical skills after this class is over.Additional Objectives include:Defend rationale of data interpretations, including the setting of Type I and II error rates; Calculate statistical power; Use data description techniques; Identify assumptions of inferential statistical methods and use proper alternatives if required; Interpret results of statistical procedures; and Provide participants the necessary background to be successful in Data Analysis II. |
| Target Audience | Those interested in more fully utilizing statistical tools in research, management, and decision-making. |
| Prerequisite | |
| Delivery Method | Instructor-Led Classroom Delivery (ILT) |
| Instructional Hours | 38 |
| Credits/CEUs | 2 |
| Primary Contact | JOSEPH WITT; Phone: (304) 876-7447; Email: joe_witt@fws.gov; |
| Secondary Contact | SO LAN CHING; Phone: (304) 876-7771; Email: so_lan_ching@fws.gov; |
| Other Contact | |
| Extracted from DOI LEARN on | 1/31/2010 8:20:33 AM |
