Description

Book Synopsis
Throughout banking, mathematical techniques are used. Some of these are within software products or models; mathematicians use others to analyse data. The current literature on the subject is either very basic or very advanced.

Table of Contents
Introduction.

1 Introduction to How to Display Data and the Scatter Plot.

2 Bar Charts.

3 Histograms.

4 Probability Theory.

5 Standard Terms in Statistics.

6 Sampling.

7 Probability Distribution Functions.

8 Normal Distribution.

9 Comparison of the Means, Sample Sizes and Hypothesis Testing.

10 Comparison of Variances.

11 Chi-squared Goodness of Fit Test.

12 Analysis of Paired Data.

13 Linear Regression.

14 Analysis of Variance.

15 Design and Approach to the Analysis of Data.

16 Linear Programming: Graphical Method.

17 Linear Programming: Simplex Method.

18 Transport Problems.

19 Dynamic Programming.

20 Decision Theory.

21 Inventory and Stock Control.

22 Simulation: Monte Carlo Methods.

23 Reliability: Obsolescence.

24 Project Evaluation.

25 Risk and Uncertainty.

26 Time Series Analysis.

27 Reliability.

28 Value at Risk.

29 Sensitivity Analysis.

30 Scenario Analysis.

31 An Introduction to Neural Networks.

Appendix Mathematical Symbols and Notation.

Index.

The Mathematics of Banking and Finance

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    A Hardback by Dennis Cox, Michael Cox

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      Publisher: John Wiley & Sons Inc
      Publication Date: 31/03/2006
      ISBN13: 9780470014899, 978-0470014899
      ISBN10: 047001489X
      Also in:
      Banking

      Description

      Book Synopsis
      Throughout banking, mathematical techniques are used. Some of these are within software products or models; mathematicians use others to analyse data. The current literature on the subject is either very basic or very advanced.

      Table of Contents
      Introduction.

      1 Introduction to How to Display Data and the Scatter Plot.

      2 Bar Charts.

      3 Histograms.

      4 Probability Theory.

      5 Standard Terms in Statistics.

      6 Sampling.

      7 Probability Distribution Functions.

      8 Normal Distribution.

      9 Comparison of the Means, Sample Sizes and Hypothesis Testing.

      10 Comparison of Variances.

      11 Chi-squared Goodness of Fit Test.

      12 Analysis of Paired Data.

      13 Linear Regression.

      14 Analysis of Variance.

      15 Design and Approach to the Analysis of Data.

      16 Linear Programming: Graphical Method.

      17 Linear Programming: Simplex Method.

      18 Transport Problems.

      19 Dynamic Programming.

      20 Decision Theory.

      21 Inventory and Stock Control.

      22 Simulation: Monte Carlo Methods.

      23 Reliability: Obsolescence.

      24 Project Evaluation.

      25 Risk and Uncertainty.

      26 Time Series Analysis.

      27 Reliability.

      28 Value at Risk.

      29 Sensitivity Analysis.

      30 Scenario Analysis.

      31 An Introduction to Neural Networks.

      Appendix Mathematical Symbols and Notation.

      Index.

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