Overview

This module introduces students to the fundamental concepts and techniques of business analytics, with a focus on practical application using Microsoft Excel. Students will learn how to organise, summarise, and visualise data, and develop an understanding of descriptive and relational statistics for exploring patterns and relationships. The module also covers key statistical methods, including sampling, confidence intervals, hypothesis testing, and regression, as well as time series and probabilistic analysis. By the end of the module, students will be able to analyse data, interpret statistical results, and discuss their meaning with confidence.

This module introduces students to the principles of business analytics and the use of Microsoft Excel for data analysis. Topics include data types, presentation methods, descriptive statistics, probability, and the normal distribution. The module also covers sampling, confidence intervals, hypothesis testing, regression, and time series analysis, with an emphasis on interpreting and communicating statistical results.

Assessment Strategy

-threshold -D- to D+ (40-49%): No major omissions or inaccuracies in the deployment of information/skills. Some grasp of theoretical/conceptual/practical elements. Integration of theory/practice/information present intermittently in pursuit of the assessed work's objectives. -good -B- to B+ (60-69%): Very good performance Most of the relevant information accurately deployed. Good grasp of theoretical/conceptual/practical elements. Good integration of theory/practice/information in pursuit of the assessed work's objectives. Evidence of the use of creative and reflective skills. -excellent -A- to A+ (70%+): Outstanding performance. The relevant information accurately deployed. Excellent grasp of theoretical/conceptual/practice elements. Good integration of theory/practice/information in pursuit of the assessed work's objectives. Strong evidence of the use of creative and reflective skills. -another level-C- to C+ (50-59%): Much of the relevant information and skills mostly accurately deployed. Adequate grasp of theoretical/conceptual/practical elements. Fair integration of theory/practice/information in the pursuit of the assessed work's objectives. Some evidence of the use of creative and reflective skills.

Learning Outcomes

• Analyse data and interpret the results

• Apply the methods of statistical inference to formulate and test hypotheses

• Conduct data analysis

• Describe and summarise data using tables, graphs, and measures of central tendency and dispersion.

• Estimate and specify confidence intervals for a mean and variance

• Investigate patterns of association between variables