Module ASB-2411:
Quantitative Methods for Bus

Module Facts

Run by Bangor Business School

10 Credits or 5 ECTS Credits

Semester 1

Organiser: Mrs Nia Weatherley

Overall aims and purpose

NOTE: This module is NOT available to students on BSc degrees.

This module provides a foundation course in statistical methods, including data collection and interpretation, probability distributions, hypothesis formulation and testing, correlation and regression analysis.

Course content

  1. Collection, management and presentation of data: samples and surveys;
  2. Descriptive statistics: averages and measures of dispersion;
  3. Uncertainty, randomness and probability;
  4. Probability distributions: the Binomial, Poisson and Normal distributions;
  5. Analysis of sample data; estimation and confidence intervals;
  6. Statistical inference: hypothesis testing;
  7. Investigating association and causality: correlation and regression analysis.

Assessment Criteria

threshold

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

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.

excellent

Excellent standard: 70+ Class 1 An outstanding performance, exceptionally able. 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.

High Standard: 60-69 Class 2.1 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.

Learning outcomes

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

  2. Evaluate probabilities involving the Binomial, Poisson and Normal distributions.

  3. Apply the methods of statistical inference to formulate and test hypotheses.

  4. Investigate patterns of association and casuality using correlation and regression analysis.

  5. Analyse data, and interpret the results.

  6. Estimate and specify confidence intervals for a mean and variance.

Assessment Methods

Type Name Description Weight
In-class Test 20
Assignment 20
Examination S1 2hrs 60

Teaching and Learning Strategy

Hours
Lecture

One 2-hour lecture per week;

20
Tutorial

One 1-hour tutorial per fornight.

4
Private study 76

Transferable skills

  • Numeracy - Proficiency in using numbers at appropriate levels of accuracy
  • Computer Literacy - Proficiency in using a varied range of computer software
  • Self-Management - Able to work unsupervised in an efficient, punctual and structured manner. To examine the outcomes of tasks and events, and judge levels of quality and importance
  • Exploring - Able to investigate, research and consider alternatives
  • Inter-personal - Able to question, actively listen, examine given answers and interact sensitevely with others
  • Critical analysis & Problem Solving - Able to deconstruct and analyse problems or complex situations. To find solutions to problems through analyses and exploration of all possibilities using appropriate methods, rescources and creativity.
  • Self-awareness & Reflectivity - Having an awareness of your own strengths, weaknesses, aims and objectives. Able to regularly review, evaluate and reflect upon the performance of yourself and others

Subject specific skills

  • Quantification and design. Data, and their effective organisation, presentation and analysis, are important in economics. The typical student will have some familiarity with the principal sources of economic information and data relevant to industry, commerce, society and government, and have had practice in organising it and presenting it informatively. This skill is important at all stages in the decision-making process.
  • Numeracy: the use of quantitative skills to manipulate data, evaluate, estimate and model business problems, functions and phenomena.

Pre- and Co-requisite Modules

Courses including this module

Compulsory in courses:

Optional in courses: