Mathematical and Statistical Sciences Course Catalogue

Presented by the Faculty of Natural and Agricultural Sciences

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Courses 1

Introduction to Statistics for Industry

2

Introduction to Probability for Industry

3

Introduction to Machine Learning for Industry

4

Design and Analysis of Experiments for Industry

5

Introductory Short Course on the statistical software package R

6

Short Course in Data Handling Using Excel

7

Short Course on Statistics and Data Analysis for research purposes

8

Short Course on Regression and ANOVA methods

Introduction to Statistics for Industry The purpose of the Introduction to Statistics for Industry is to empower participants with knowledge and understanding of basic descriptive statistics required to summarise variables of interest, to be able to quantify correlations between variables, to perform simple regression analysis, and to conduct basic inference related to the comparison of means.

Target Group Engineers and applied scientist in industry.

Duration 3 Days. Day 1 = 3 sessions of 2.5 hours each (7.5 hours total). Day 2 = 3 sessions of 2.5 hours each (7.5 hours total). Day 3 = 2 sessions of 2.5 hours each (5 hours total)

Module Outcomes Demonstrate informed knowledge and understanding of descriptive statistics, some basic inferential methods, as well as the execution of programming statements in a statistical software package. Demonstrate an ability to select and apply basic descriptive and inferential statistical analyses, and interpret results from these analyses. Demonstrate an ability to report results and conclusions in an accurate and ethical manner.

Introduction to Probability for Industry

The purpose of the Introduction to Probability for Industry course is to provide participants with knowledge of basic probability concepts, including conditional probability, discrete and continuous distributions, estimation techniques, and goodness-of-fit tests for these statistical distribution. These concepts will also be utilised to show how simple and complex Monte Carlo simulations can be performed using computer software.



Target Group

Engineers and applied scientist in industry.

Duration 3 Days. Day 1 = 3 sessions of 2.5 hours each (7.5 hours total). Day 2 = 3 sessions of 2.5 hours each (7.5 hours total). Day 3 = 2 sessions of 2.5 hours each (5 hours total)

Module Outcomes Demonstrate applied knowledge and critical understanding of basic probability theory concepts and simulation techniques. Demonstrate the ability to identify, select, and apply the most appropriate distributions to be fit to realworld data and then interpret and critically judge the effectiveness of these fits. Demonstrate the ability to report results and conclusions in an accurate and ethical manner.



Introduction to Machine Learning for Industry The purpose of the Introduction to Machine Learning for Industry Short Course is to empower participants with knowledge and competence on how to build supervised and unsupervised machine learning and statistical models for prediction and classification using appropriate software. The techniques that will be taught include multiple regression analysis, logistic regression, regression trees, linear discriminant analysis, principal component analysis, and clustering.

Target Group Engineers and applied scientist in industry.

Duration 3 Days. Day 1 = 3 sessions of 2.5 hours each (7.5 hours total). Day 2 = 3 sessions of 2.5 hours each (7.5 hours total). Day 3 = 2 sessions of 2.5 hours each (5 hours total)

Module Outcomes Demonstrate applied knowledge and critical understanding of basic probability theory concepts and simulation techniques. Demonstrate the ability to identify, select, and apply the most appropriate distributions to be fit to realworld data and then interpret and critically judge the effectiveness of these fits. Demonstrate the ability to report results and conclusions in an accurate and ethical manner.

Design and Analysis of Experiments for Industry The purpose of the short course in Design and Analysis of Experiments for Industry is to empower participants with knowledge and competence of industrial experimental methodology, basic statistics required for industrial experimental design, and in the analysis of data for designed experiments. Various experimental designs and their applications will be discussed, including factorial and fractional factorial designs, blocking of experiments, response surface designs and optimal experimental designs.

Target Group Engineers and applied scientist in industry.

Duration 3 Days. Day 1 = 3 sessions of 2.5 hours each (7.5 hours total). Day 2 = 3 sessions of 2.5 hours each (7.5 hours total). Day 3 = 2 sessions of 2.5 hours each (5 hours total)

Module Outcomes Demonstrate applied knowledge and critical understanding of industrial experimental design methodology. Demonstrate the ability to identify, select, and analyse the appropriate experimental design for specific real-world scenarios. Demonstrate the ability to report results and conclusions in an accurate and ethical manner.

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Introductory Short Course on the statistical software package R This short course aims to equip participants with the skills necessary to utilise the R-software programme to address various data problems using programming techniques. The participant will develop programming skills necessary for advanced data analysis.

Target Group Postgraduate students busy with research, researchers or any person who would like to develop his or her R-programming skills with a NQF 6 qualification with intermediate computer literacy.

Duration 2 Days

Module Outcomes Detailed knowledge and understanding of data structures and the execution of programming statements in the statistical software package R. Demonstrate an ability to create, manipulate and format data structures in R.

Short Course in Data Handling Using Excel This short course aims to equip participants with the skills necessary to utilise the functionality of Microsoft Excel to manipulate, edit, summarise and work with data.

Target Group Individuals who would like to develop their Excel skills with the aim towards using these skills to improve their productivity in the workplace.

Duration 3 Days

Module Outcomes Basic knowledge and informed understanding of basic spreadsheet data handling in Excel. Knowledge of, and the ability to select and apply standard Excel functions and tools for manipulating, summarising, and editing Excel spreadsheet data.

Short Course on Statistics and Data Analysis for research purposes This short course aims to equip participants with the skills necessary to understand, analyse and interpret the statistical output obtained from computer software in order to answer specific research questions. In addition the participant will gain knowledge on how to approach the process of designing a questionnaire as a data collection tool and evaluate the validity and reliability of these questionnaires.

Target Group Postgraduate students busy with research, researchers or any person who would like to enhance his or her statistical knowledge.

Duration

Module Outcomes Demonstrate informed knowledge and understanding of descriptive and inferential statistics applied in quantitative research. Demonstrate an ability to select, apply and interpret standard statistical methods and techniques within different research studies. Demonstrate an ability to report results in a reliable, accurate, and ethical manner.

Short Course on Regression and ANOVA methods This short course aims to equip participants with the skills necessary to understand, analyse and interpret the statistical output obtained from regression and ANOVA analyses produced by computer software in order to answer specific research questions. The participant will gain deeper insight into the application of regression and ANOVA methods.

Target Group Postgraduate students busy with research, researchers or any person who would like to enhance his or her statistical knowledge relating to regression and ANOVA methods.

Duration 2.5 days

Module Outcomes Informed knowledge and clear understanding of regression, ANOVA and ANCOVA methods applied in quantitative research. An ability to select and apply appropriate regression, ANOVA and ANCOVA methods within different research studies and interpret the statistical software output from these methods. An ability to report results in a reliable, accurate and an ethical manner.

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Course Academic Prof Roelof Coetzer [email protected] Apply Here