Introduction to Data Analysis and Statistics for Business - CB367

Location Term Level Credits (ECTS) Current Convenor 2019-20
Medway Autumn
View Timetable
4 15 (7.5) DR D Tunaru

Pre-requisites

None

Restrictions

None

2019-20

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

This module appears in:


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

Indicative reading

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.

University of Kent makes every effort to ensure that module information is accurate for the relevant academic session and to provide educational services as described. However, courses, services and other matters may be subject to change. Please read our full disclaimer.