Book Image

QlikView for Developers Cookbook

By : Stephen Redmond
Book Image

QlikView for Developers Cookbook

By: Stephen Redmond

Overview of this book

QlikView has been around since 1993, but has only really taken off in recent years as a leader in the in-memory BI space and, more recently, in the data discovery area. QlikView features the ability to consolidate relevant data from multiple sources into a single application, as well as an associative data model to allow you to explore the data to a way your brain works, state-of-the-art visualizations, dashboard, analysis and reports, and mobile data access. QlikView for Developers Cookbook builds on your initial training and experiences with QlikView to help you become a better developer. This book features plenty of hands-on examples of many challenging functions. Assuming a basic understanding of QlikView development, this book provides a range of step-by-step exercises to teach you different subjects to help build your QlikView developer expertise. From advanced charting and layout to set analysis; from advanced aggregations through to scripting, performance, and security, this book will cover all the areas that you need to know about. The recipes in this book will give you a lot of the information that you need to become an excellent QlikView developer.
Table of Contents (19 chapters)
QlikView for Developers Cookbook
Credits
Foreword
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Creating a Statistical Control Chart using Standard Deviation


Control charts were developed by a statistician named Walter Shewhart in the 1920's. He was working for Bell Labs, who, at that time, were rolling out a telephony network across the US. For this network, amplifiers and other such equipments needed to be buried underground, and it was expensive to have to dig it up for repairs. They were worried about the variations in the manufacturing process leading to increased cost in repairs.

Shewhart used control charts to show that variation was normal and reacting to small variations by making changes to the manufacturing process was wrong. As long as the variation was within control limits and not trending in any particular direction, there was nothing to worry about.

A simple control chart uses the mean of the data (or a subset of that data) to draw a center line around which the data varies. Control limits are set at two or three standard deviations (on the basis that under a normal distribution...