DISC 1011 - Introduction to Probability and Statistics 

Level I, Undergraduate, Small Cohort (less than 20 students)

Modality: Online

School of Science, Computing and Artificial Intelligence 

Campus: The UWI, FIC 

Course overview

• This introductory course introduces students to Probability and Statistics. It covers the theory in two integrated modules. 

• Probability Theory is primarily concerned with modelling phenomena with uncertain outcomes while Statistical theory provides a basis for various techniques in data collection, analysis, and interpretation.

• The focus of this course is to build the fundamental assumptions in Probability and Statistics. 

• It will be assessed using both theoretical and practical applications using statistical software, where students are able to apply these ideas to solve problems and make critical real- world decisions.

• Course assessments are divided as follows: 65% comprising computational assignments, guided discussions, and a guided mini-project, as well as a final examination worth 35%.

• For a Sample Lesson Plan see here: 

BIOL 6206 - Management and Analysis of Environmental Data 

Postgraduate, Small Cohort (less than 5 students)

Modality: Online

Department of Life Sciences, Faculty of Science and Technology

Campus: The UWI, STA

Course overview

• Statistics is an indispensable tool in various fields, such as Natural and Physical Sciences, Biological and Social Sciences. 

• This course specialises in Ecological Data Analysis using R: The Statistical Programming Language, which is used globally for ecology and environmental data. 

• It provides a numerical treatment of statistical concepts and methods applied to ecology, from basic exploratory analysis to more advanced multivariate analysis. 

• It is designed to equip students with a portfolio of skills and hands-on experiences for postgraduate studies and beyond. 

• The use of statistical software for various modules is key, to provide students with a clear understanding of the real-world applications in STEM fields. 

• Course assessments are 100% comprising computational assignments using R software, guided discussions, and a guided mini-project and mini-presentation. There is no final examination.

PSYC 6013 - Advanced Statistics and Research Methods in Psychology 

Postgraduate, Small Cohort (less than 5 students)

Modality: Online

Department of Life Sciences, Faculty of Science and Technology

Campus: The UWI, STA

Course overview

• This course integrates research design and statistics for psychology. 

• Topics covered will include methods and software skills increasingly required by researchers in psychology and other social sciences.

• It consolidates knowledge of the statistical and research methods including data screening, descriptive statistics, comparison of means, correlations, validity and reliability, principles guiding research design, interpretation and reporting of statistical results and general linear modelling.

• In addition, it explores evaluation of constructs and measures using exploratory and confirmatory factor analysis and structural equation modelling.

• Students will acquire proficiency in the use of SPSS for most of the statistical analyses performed in this course.

• Emphasis will be on conceptual understanding of when to apply techniques and how to interpret statistical output.

• Course assessments are 100% comprising computational assignments using SPSS software, guided discussions, and a guided mini-project and mini-presentation. There is no final examination.

ECNG 6710 - Research Methods

Postgraduate, Small Cohort  (less than 10 students)

Modality: Blended

Department of Electrical and Computer Engineering, Faculty of Engineering

Campus: The UWI, STA

Course overview

• This course is designed to provide necessary theoretical and practical knowledge in overall research process. 

• Elaborate treatment of theory and practice related to various research processes will be undertaken, so that students will be able to start working on a specific technical topic (which will be specified during the first week of the course), undertake a comprehensive literature survey, summarize various findings and developments made by earlier researchers, form a basis for new challenge to take on the work further, prepare a detailed technical project proposal, convince peers with an oral presentation.

• This course has 3 main components: Research, Statistics and MATLAB, taught by various lecturers.

• I lecture the Statistics Component, which has 6 modules and a Coursework Examination.

• Course assessments are worth 100% comprising a Research Paper, MATLAB Programming assignments and a Statistics Examination. There is no final examination.

MATH 1115 - Fundamental Mathematics for the General Sciences I

Level I, Undergraduate, Large Cohort (over 100 students)

Modality: Face-to-face

Department of Mathematics and Statistics, Faculty of Science and Technology

Campus: The UWI, STA

Course overview

• The main objective of this course is to provide entering undergraduate students with a set of mathematical tools and methods that can be applied to their scientific field of choice.

• The major topics will be prefixed by typical mathematical problems that arise frequently in practical applications of the varying fields of science. As a service course in Mathematics, it should be considered as a broad introduction of the typical methods utilized in the applied sciences for solving problems. 

• Little attention will be given to the underlying concepts of mathematical theory during lecture hours. 

• Emphasis will be placed on the use of Microsoft Excel as a tool for the presentation of data in Laboratory Reports.

• Course assessments are equally  split: 50% comprising problem sheets, lab sheets and coursework tests and a final examination worth 50%.

MATH 1192 - Introduction to Mathematical Software I - A Primer on Excel

Level I, Undergraduate, Large Cohort (over 100 students)

Modality: Face-to-face

Department of Mathematics and Statistics, Faculty of Science and Technology

Campus: The UWI, STA

Course overview

• This course will enhance the student’s knowledge of Microsoft Excel, which will be used to solve frequently encountered mathematics and statistics problems.

• Microsoft Excel will be introduced as data management software, and popular features of Excel such as formatting, editing, chart types and ‘autofill’ will be covered at the beginning of the course. 

• Students are also introduced to mathematical tools in Excel which will assist in problem solving. 

• An introduction to the Visual Basic Editor and programming in Visual Basic is then offered to students for Real-world Applications.

• Course assessments are worth 100% comprising 5 structured assignments, using MS Excel. There is no final examination.

MATH 2274 - Probability Theory I  

Level II, Undergraduate, Medium/Large Cohort  (70 - 130 students)

Modality: Face-to-face

Department of Mathematics and Statistics, Faculty of Science and Technology

Campus: The UWI, STA

Course overview

• This course will enhance the student's knowledge of Probability Theory, as it relates to the likelihood of events occurring, and  its applications

• The course begins with a discussion of the basic ideas of probability, including the axioms of probability, combinatorial probability, conditional probability and independence. 

• The rest of the course focuses on distribution theory, related to well-known discrete and continuous distributions.

• The idea of a statistic is also introduced with ideas of distributions of the mean and the sample variance, to provide context for follow-up courses in Statistics

• Real-world applications are provided using simple examples in statistical software to give students a gentle introduction to put theory to practice.

• Course assessments are equally split: 50% comprising structured assignments and coursework tests, and a final examination worth 50%. 

MATH 2274 - Statistics I  

Level II, Undergraduate, Medium/Large Cohort  (60 - 90 students)

Modality: Face-to-face

Department of Mathematics and Statistics, Faculty of Science and Technology

Campus: The UWI, STA

Course overview

• The course is a survey of the major ideas of inference, experimental design and statistical methods. 

• Students are introduced to the basics of the statistical packages such as R and its use in descriptive statistics.

• Emphasis is placed on the use of real data, and both summary statistical measures for continuous and discrete data are discussed. 

• Students also learn about inference, including point estimation, confidence intervals and hypothesis testing. 

•  Regression models, ANOVA in designed experiments and non-parametric procedures are also discussed.

• Assessment will be based on the weekly assignments and in-course tests followed by a final examination based on the whole course 

• Course assessments are equally split: 50% comprising structured assignments and coursework tests, and a final examination worth 50%.