FI1BBST05 Statistical Tools

FI1BBST05 Statistical Tools

  • Course description
    • Course code
      FI1BBST05
    • Level of study
      5.1
    • Program of study
      Data Analyst 2
    • Credits
      5
    • Course coordinator
      Bertram Haskins, Alec Du Plessis
Teaching term(s)
2024 Autumn
Authors
Alec Du Plessis
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
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
Learning outcomes - 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
Teaching and Learning

In this course, the following teaching and learning methods can be applied, but are not limited to:

  • Lecture: Educator-led presentations or activities providing knowledge, skills, or general competencies in the subject area.
  • Group work: Collaborative activities where students work together to solve problems or complete tasks.
  • Tutoring: One-on-one or small group sessions with an instructor for personalized guidance and support.
  • Student presentations: Opportunities for students to demonstrate their understanding of course material by presenting to peers.
  • Online lessons: Digital content delivered via an online learning platform.
  • Guidance: Individualized advice and direction from instructors to support students in their learning journey.
  • Workshops: Practical sessions focused on hands-on application of theoretical concepts or skills.
  • Self-study: Independent study where students engage with course material on their own without any teacher support.
Reading list

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

Assessments
Form of assessmentGrading scaleGroupingDuration of assessment
Course Assignment
Pass / Fail
Group/Individual
1 Week(s)
Approved by
x.x
Accreditation
x.x