FI1BBST05 Statistical Tools

FI1BBST05 Statistical Tools

  • Course description
    • Course Code
      FI1BBST05
    • Level of Study
      5.1
    • Program of Study
      Data Analyst 2
    • Credits
      5
    • Study Plan Coordinator
      Bertram Haskins, Alec Du Plessis
Teaching Term(s)
2025 Autumn
About the Course

This course provides candidates with the knowledge of using integrated spreadsheet tools and introductory statistical modelling software. Candidates will be challenged to apply their organized datasets using the decision-making metrics learned. Technical skills will be developed, and the use of existing statistical tools will give candidates a firm starting point to developing their own bespoke solutions to contextualized real world problems. This course builds on the competence from Spreadsheet Fundamentals.

This course builds directly on the skills gained from Spreadsheet Fundamentals. Candidates at this point are able to manage a workbook and are now ready to be introduced to the knowledge and skills needed to use statistical tools to further analyse and extract heuristics from data sets. Several mathematical techniques are taught which assist in improving data quality, and to reduce erroneous data points from impacting the rest of the model. The tools selected for this course are from built-in spreadsheet suites and any industry standard practices.

Course Learning Outcomes
Knowledge

The candidate:

  • has knowledge of spreadsheet data tools to perform statistical analysis on data sets using built-in functions
  • has knowledge of statistical methodologies using to extract key performance indicators from numerical values
  • has knowledge of concepts and processes required to execute advanced data analytics tool packs exclusive to spreadsheet software
  • has knowledge of processes and tools required to perform industry required analysis, specifically: correlation, regression, Anova, histogram and covariance analysis
  • has knowledge of Power Query and how to automate time consuming tasks in spreadsheet software
  • understands z-scores and z-testing and the significance on z-values in the reduction of outliers
Skills

The candidate:

  • can apply knowledge to perform statistical analysis on data sets using built in spreadsheet tools
  • masters relevant techniques and tools to install and use the advanced data analysis suite
  • masters advanced spreadsheet techniques such as Power Query to automate tasks
  • can apply knowledge of statistical tools and z-values to reduce errors and eliminate outliers
General Competence

The candidate:

  • can carry out work using advanced spreadsheet tools to needs of selected target groups
  • can develop effective work methods in the production of an analysis within the spreadsheet framework
Learning Activities

Digital Learning Resources
The learning management system (LMS) is the primary learning platform where students access most of their course materials. The content is presented in various formats, such as text, images, models, videos or podcasts. Each course follows a progression plan, designed to lead students through weekly modules at their own pace. Exercises and assignments (individual or in groups) are embedded throughout the courses to support continuous practice and assessment of the learning outcomes.

Campus Resources
In addition to the digital learning resources, campus students participate in physical learning activities led by teachers as part of the overall delivery.

Guidance
Guidance and feedback from teachers support students' learning journeys, and may be provided synchronously or asynchronously, individually or in groups, via text, video or in-person feedback.

Assessments
Form of assessmentGrading scaleGroupingDuration of assessment
Course Assignment
Pass / Fail
Individual
1 Week(s)
Reading List

Teaching materials, reading lists, and essential resources will be shared in the learning platform and software user manuals where applicable.