# Introduction to Data Analysis and Statistics for Business - BUSN3670

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## Module delivery information

Location Term Level1 Credits (ECTS)2 Current Convenor3 2024 to 2025
Medway
Autumn Term 4 15 (7.5) Epameinondas Katsikas

## Overview

The aim of this module is to give students a solid grounding in key statistical techniques required to analyse effectively business data and data relevant for business. Indicative content:
• Maths and statistical skills for business; revision of algebra and basic mathematical functions.
• Summarising data with histograms, bar charts, frequency distributions, measures of central tendency and dispersion.
• Spreadsheets: features and functions of commonly-used spreadsheet software including: workbook, worksheet, rows, columns, cells, data, text, formulae, formatting, printing, , charts and graphs, data management facilities,
• Probability: The relationship between probability, proportion and percent, addition and multiplication rules in probability theory and Venn diagrams.
• Common Probability Density Functions.
• Sampling and its use in inference, and applications of sampling in business management.
• Regression and correlation: scatter plots; simple regression; interpreting computer output.
• Forecasting using spreadsheets.
• Hypothesis testing using z-scores and t-scores
• Simulations- random number generation

## Details

### Contact hours

Total contact hours: 27
Private study hours: 123
Total study hours: 150

## Method of assessment

Main assessment methods:
On-Line Moodle Test (20%)
Individual Stats Report (1000 words) (20%)
Examination, 2 Hour (60%)

Reassessment method:
100% examination

Freeman J. et al. (2014) Statistics for Business and Economics. London: Cengage Learning

Swift L. and Piff S. (2014) Quantitative Methods for Business, Management & Finance. Basingstoke: Palgrave Macmillan

See the library reading list for this module (Medway)

## Learning outcomes

The intended subject specific learning outcomes.
On successfully completing the module students will be able to:
- Summarise and analyse data and present it effectively to others.
- Use statistical techniques to draw well-founded inferences from quantitative data.
- Identify sources of published statistics, understand their context and report on their wider relevance.
- Apply key mathematical formulae to calculate financial variables for decision-making.

The intended generic learning outcomes.
On successfully completing the module students will be able to:
- Demonstrate numeracy and quantitative skills.
- Scan and organise data and abstract meaning from information.
- Work and study independently, and utilise resources effectively.

## Notes

1. Credit level 4. Certificate level module usually taken in the first stage of an undergraduate degree.
2. ECTS credits are recognised throughout the EU and allow you to transfer credit easily from one university to another.
3. The named convenor is the convenor for the current academic session.