SYLLABI PART A QUANTITATIVE TECHNIQUES

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  1. AIM
  2. LEARNING OUTCOMES
    1.     At the conclusion of this module the candidate should be able to.

The aim of the module is:-

1)   To expose the student and to assess competency in the Quantitative Techniques which are applied in solving business related problems.

  • Understand the mathematical and statistical techniques which are useful for business applications.
  • Apply the Quantitative Techniques to solve business problems.
  • Interpret statistical data for business applications.
  1. PRE-REQUISITE LEARNING
  2. LEARNING CONTENTASSESSMENT SCHEME
    1. Defining statistics, and its use in business.
    2. Collection and presentation of numerical information:
    3. Data Description
    4. Business Calculations:
    5. Correlation and regression analysis:
    6. Probability:
    7. Sampling:
    8. Index Numbers:
    9. Time Series Analysis:
  3. RECOMMENDED READING

Evidence of assessed pre-requisite knowledge and understanding at ‘A’ Level, or those of equivalent qualifications which have been approved as meeting the Institute’s requirements must be demonstrated.

Questionnaires, interviews, tabulation analysis and interpretations.

Graphical displays, bar graphs (multiple, component), pie charts, pictograms, line graphs, lorenze curves, stem and leaf diagrams, pictorial presentations, moving totals and averages.

Measures of Centrality – mean, medium, weighted mean, mode

Measures of Spread – for grouped and ungrouped data – variance, standard deviation, range quartiles, percentiles, interquartile range, box and wisker plot.

Frequency Distributions – histograms, polygon, ogives, skewness

The elimination of common errors.  Approximations and their limitations.

Use of annuity tables, sinking fund schedules, simple and compound interest, elementary insurance calculations.

Correlation coefficient, scattergraphs, cross tabulation tables, simple linear regression, multiple correlation coefficient.  Regression analysis.  Interpretation of parameters.

A basic introduction to probability from a practical viewpoint.  Equally likely outcomes, combinations of events, union of events, conditional probability, mutually exclusive events, venn diagrams, probability trees, conditional probability, normal distribution.

Binomial distribution, Poison distribution and proportions, Testing a hypothesis for small and large samples and confidence intervals, types of errors, power of test.

Methods of sampling, samples, populations.  Parameters and statistics.

Sampling distributions.  Estimating population means and proportions.  Testing a hypothesis.

Problems involved in their use, price relative methods, aggregative methods.  Laspeyre and Paasche indices ratail price index, index construction and interpretation.

Trends, moving averages, seasonal variations, random variations, exponential smoothing and simple forecasting.  De-seasonalising a time series.

Official sources of economic and business data.

The National Income and Expenditure Accounts.

Censuses of population, production, distribution.

Manpower earnings, cost of living, capital formation, trade returns and balance of payments.

NOTE:

Candidates will be provided with the necessary tables.

Candidates may make use of hand-held, self-powered, silent, non-programmable calculators, but intermediate working steps must be shown.

Three hour examination paper

HARPER WM (1993) STATISTICS (6TH Edition) MACDONALD  EVANS PLYMOUTH
REES DG (1995) ESSENTIAL STATISTICS (3rd Edition) CHAPMAN & HALL LONDON

                                                                

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