# Microsoft Excel Statistical and Advanced Functions for Decision Making von Murugappan, Palani (eBook)

• Erscheinungsdatum: 02.09.2014
• Verlag: Blue Micro Solutions
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## Microsoft Excel Statistical and Advanced Functions for Decision Making

Microsoft Excel Statistical and Advanced Functions for Decision Making By Palani Murugappan

## Produktinformationen

Format: ePUB
Seitenzahl: 500
Erscheinungsdatum: 02.09.2014
Sprache: Englisch
ISBN: 9789671275696
Verlag: Blue Micro Solutions
Größe: 1979kBytes
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## Microsoft Excel Statistical and Advanced Functions for Decision Making

A short introduction to statistics

This book emphasizes on the use of statistical functions for the purpose of decision making. While every attempt is made as not to get "too technical", it would be wise for any reader to "brush up" on some of the basic terminology and understanding of what statistics is all about.

The very mention of the word statistics tends to get many to avoid this topic. However, in this book, attempt is made to link and show how you can use some of the more commonly used phrases such as standard deviation, regression, correlation, linear and exponential growth, etc in terms on analyzing data using the software Microsoft Excel. Wherever possible, Excel is used to show how you can use some of its built-in functions to perform data analysis and interpret the results.

Many out there are extremely good at performing "number crunching" calculations but most are unable to interpret the results. For example, when given a raw set of data, how then do you try to establish if a relationship or pattern exists? What tools will you use? To answer these questions, Excel can perform most of the analysis but the interpretation still has to come from the user.

Another example is when you have collected data on sales figures based on week days and the temperature outside, you can perform analysis as to check if there exists a relationship on the sales based on the week day or temperature i.e. do people buy more on certain days or do people buy less when the temperature drops. These questions can be answered when an analysis is performed. This is an example of "modeling" and Excel can be used to perform much of the calculations.

Furthermore, you can also perform comparative analysis such as a "what if" condition and highlight some of the cells when a positive or negative results occur. All this and much more will be shown in this book.

Why statistics?

To be competitive, a business must design its products to be of certain quality and robust. For a product to fall in this category, the processes involved in making the product must facilitate a never ending improvement (what is known as "gemba kaizen" in Japanese which literally means "continuous improvement". Toyota applies this principle in all of its manufacturing plant across the globe) at all stages of manufacturing beginning from the design stage.

One strategy to ensure that this is a success is to employ statistical methods such as statistically designed experiments and produce processes that provide high yield with low failure or reject rate. A well planned statistical study can reduce much of the obstacles or hindrances to high quality production which saves time and money. This is where the use of cost effective experiments can prove useful in improvising and optimizing products and processes.

Statistics can help you in making decisions under uncertainties based on some numerical and measurable scales. A decision making process can only be made when relevant data is available, not on personal belief or opinion. Where then do you get the relevant data? This is where knowledge on data collection method is important. Once the data is collected, it can be compiled and analyzed as information. With much information, it can be turned to facts and finally facts to knowledge.

Let us look around us. How often does any manufacturing company embark on a project without an initially study on the marketability and demand of the product, quality, design, and pricing issues? This is where the compilation of data is required to study the analysis of the data before proceeding with the design and making the product finally. Of course there is still no guarantee that the product will be a s

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