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Quantitative Methods Diploma

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A Distance Learning Course of 9 Lessons. Course Description: Many business problems cannot be solved without the use of mathematical methods. All businesses collect masses of data during the course of their daily activities. This data must be organised and analysed in such a way that all of the key decision-making staff can make sense of it. Data collection requires techniques which are often sophisticated. Collected data must then be analysed; the business must have some idea of the meaning of their data. The data can be used to diagnose the problems faced by the business. When business problems have been diagnosed, then a whole range of techniques (many of them mathematical) can be used to help provide solutions to problems. This is why this course is inevitably concerned with the techniques used for problem solving. But as you will see from the above, the concern does not just end at the use of the technique, it extends back to the collection of the data required by the technique, and the inevitable questions raised about whether the correct methods are being used. The importance of the above is to prevent you from making the mistake of thinking that QM will merely consist of a set of techniques. Techniques are important, but the reasons why we use them, and the degree of success we can expect from them are much more important. Overview Analysis and organisation of data acquired during the course of a business's daily activities, using mathematical methods, so that all key decision-making staff can make sense of it and apply it to problem-solving.
Regions:
  • All Areas
Delivery:
  • Distance
  • Online
Category:
Difficulty:
  • Not applicable

Further Details

Course Syllabus: UNIT ZERO - BASIC MATHS - Section 1. Numbers, Section 2 Algebra, Section 3 Equations and Coeffecicients, Section 4 Using a Calculator. UNIT ONE - BUSINESS MATHS - Section 1 Financial Analysis, Section 2 Graphs. UNIT TWO - DATA PRESENTATION - Section 1 Data, Variables and Measurement, Section 2 The Frequency Distribution, Section 3 Measures of Central Tendency, Section 4 Understanding Averages, Section 5 Measures of Dispersion or Variation, Section 6 Interpreting the Variance and Standard Deviation. UNIT THREE - LINEAR PROGRAMMING - Section 1: A Case Study, Section 2: Developing a Linear Programming Model, Section 3: Solving Linear Programming Problems Using Graphical Methods, Section 4: Practising the Graphical Solution Technique, Section 5: Shadow Prices and Sensitivity Analysis, Section 6: The Role of Computer Software. UNIT FOUR - REGRESSION AND CORRELATION - Section 1. Relationships Between Variables, Section 2. The Coefficient of Correlation, Section 3. Interpreting the Coefficient of Correlation, Section 4. Regression Analysis, Section 5. How Effective is Regression Analysis?, Section 6. What Next?. UNIT FIVE - PROBABILITY - Section 1. The Problem of Measurement, Section 2. Events, contingency Tables and Venn, Section 3. Rules for Calculating Probabilities, Section 4. Putting the Rules of Probability to Work, Section 5. Probability Trees, Section 6. Counting Techniques. UNIT SIX - PROBABILITY DISTRIBUTION - Section 1. Random Variables, Section 2. Mathematical Functions of Probability Distributions, Section 3. Summing Up Probability Distributions, Section 4. Binomial Distribution, Section 5. Normal Distribution, Section 6. Using the Normal Distribution. UNIT SEVEN - INTRODUCTION TO SAMPLING - Section 1 Sample and Population, Section 2 The Behaviour of Sample Estimates, Section 3 Point Estimates and Interval Estimates, Section 4 Proportions and Percentages, Section 5 Sample Size Problems, Section 6 Significance Testing. UNIT EIGHT - INDEX NUMBERS - Section 1 The Measurement of Change, Section 2 Weighted Indices and Aggregative Methods of Calculation, Section 3 Quantity and Value Indices, Section 4 Time Series, Section 5 Moving Averages, Section 6 Forecasting a Time Series. Payment plans are available on request.

Guide price

£260.00

 

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