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Palani Murugappan

Microsoft Excel Statistical and Advanced Functions for Decision Making

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Perform various data analysis using statistical functions, filters and histograms! Learn all about pivot tables and pivot charts! Use the Solver and Goal Seek to find optimum results! Perform sales forecasting and various predictions using Excel's built-in functions!

This book was written to help any users wanting to have a good grasp on the advanced functions and an analysis of the various statistical tools for the purpose of decision making. It goes further by introducing the concepts of filters, estimating and forecasting, data validation, conditional formatting, goal seek, using the solver, and finally, pivot tables and pivot charts.

Many books have been written on Excel. However, this book explains most of the advanced functions and features in a rather simplified manner with plenty of screen captures wherever possible. New users and existing users on Excel will find this book handy.
Denne bog er ikke tilgængelig i øjeblikket
571 trykte sider
Oprindeligt udgivet
2015
Udgivelsesår
2015
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Vurderinger

  • herawan19har delt en vurderingfor 7 år siden
    👍Værd at læse

    It help you a lot in analyzing the data in practical way.

  • Valeria Trifiltsevahar delt en vurderingfor 7 år siden
    👍Værd at læse

    I picked up a few tricks, but I already knew 90% of stuff described in this book. The Excel version used for this tutorial is ancient, though it is still a very good tutorial for beginners.

Citater

  • b3628642019har citeretfor 4 år siden
    There are four aspects to managerial decision making. These are as follows i.e. Risk, Uncertainty, Conflict, and Lack of Structure
  • Albert Leonardohar citeretfor 6 år siden
    should bear in mind that just because two variables are strongly correlated does not imply that there is a relationship between them. The following example highlights this.
  • Albert Leonardohar citeretfor 6 år siden
    The following categories indicate a quick way of ding so.If the r value is:
    0.0 to 0.2 : Very weak to negligible correlation
    0.2 to 0.4 : Low correlation (not very significant)
    0.4 to 0.7 : Moderate correlation
    0.7 to 0.9 : High correlation
    0.9 to 1.0 : Very high correlation

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