Solving Problems with Data and Probability | Online Short Course
The Solving Problems with Data and Probability course is designed to help professionals apply analytical thinking and statistical methods to real-world project challenges. Whether you’re working in operations, management, or project teams, this course builds your ability to interpret data, assess risks, and make informed decisions that drive project success.
In modern work environments, the ability to solve problems using data is a competitive advantage. This course introduces core concepts of data analysis and probability in a practical, accessible way—making it ideal for those involved in project management courses or seeking to enhance their decision-making skills.
What You’ll Learn
Through this course, you’ll gain valuable knowledge and problem-solving skills in:
- Understanding basic statistical concepts and how they apply to project environments.
- Collecting, organising, and interpreting project-related data.
- Applying probability tools to assess risk and predict potential outcomes.
- Using data to support problem identification, root cause analysis, and solution development.
- Communicating findings and data insights clearly to support team decisions.
These skills help improve planning accuracy, risk management, and team confidence in project execution.
Who Should Enrol
This course is ideal for professionals looking to enhance their analytical thinking within project settings. It is especially useful for those working with data, involved in planning, or participating in project management courses where data literacy adds value.
Ideal for:
- Project team members seeking to support data-driven decision-making.
- Professionals in roles requiring analysis, forecasting, or reporting.
- Students and learners in project management or business courses.
- Team leaders and coordinators responsible for evaluating project performance.
- Anyone interested in applying statistics and probability to improve project outcomes.
By enrolling, you’ll gain the tools to approach problems logically, interpret data meaningfully, and support your team with actionable insights. This course strengthens both your problem-solving capacity and your value as a project contributor.
Take the next step—enrol today and start solving problems with confidence, clarity, and data-backed decisions.
Description
This unit standard is designed to provide credits towards the mathematical literacy requirement of the NQF at Level 3. The essential purpose of the mathematical literacy requirement is that, as the learner progresses with confidence through the levels, the learner will grow in a confident, insightful use of mathematics in managing everyday living needs to become a self-managing person. An understanding of mathematical applications that provides insight into the learner`s present and future occupational experiences and so develop into a contributing worker. The ability to voice a critical sensitivity to the role of mathematics in a democratic society and become a participating citizen. People credited with this unit standard can pose questions and collect and organise data. Represent and interpret data using various techniques to investigate real-life and work problems. Use random events to explore and apply probability concepts in simple life and work-related situations.
Course Content
- Situations or issues that can be dealt with through statistical methods are identified correctly.
- Variables contributing to a problem situation are identified and addressed in data gathering, e.g. crime is related to the time of day and location.
- Appropriate and efficient methods are used to collect, record, and organise data.
- Data samples are of adequate size and are representative of the population.
- Graphical representations and numerical summaries are consistent with the data, are clear and appropriate to the situation and target audience.
- Different representations of aspects of the data are compared to take a position on the issue.
- Calculations and the use of statistics are correct and appropriate to the problem.
- Interpretations of statistics are justified and applied to answer questions about the problem.
- New questions that arise from the modeling of the data are discussed.
- Data are gathered, organised, sorted and classified in a suitable manner for further processing and analysis.
- Experiments and simulations are chosen appropriately in terms of the situation to be investigated.
- Probabilities are determined correctly.
- Distinctions are correctly made between theoretical and experimental probabilities.
- Predictions are based on validated experimental or theoretical probabilities.
- The outcomes of experiments and simulations are communicated clearly.
Accreditation
- Non-accredited: Short course only
- Duration: 1h 30m
- Delivery: Classroom/Online/Blended
- Access Period: 12 Months
