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My Reading on ASQ CQA HB Part V Part 1 small

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Charlie Ch<strong>on</strong>g/ Fi<strong>on</strong> Zhang<br />

<strong>Part</strong> VC<br />

Chapter 20<br />

Basic Statistics/<strong>Part</strong> VC<br />

_________________________<br />

Descriptive statistics furnish a simple method of extracting informati<strong>on</strong> from what often seems at first glance to<br />

be a mass of random numbers. These characteristics of the data may relate to:<br />

1. Typical, or central, value (mean, median, mode)<br />

2. A measure of how much variability is present (variance, standard deviati<strong>on</strong>)<br />

3. A measure of frequency (percentiles)<br />

Statistics is c<strong>on</strong>cerned with scientific methods for collecting, organizing, summarizing, presenting, and<br />

analyzing data, as well as drawing valid c<strong>on</strong>clusi<strong>on</strong>s and making reas<strong>on</strong>able decisi<strong>on</strong>s <strong>on</strong> the basis of such<br />

analysis. In a narrower sense, the term statistics is used to denote the data themselves or numbers derived<br />

from the data, such as averages.<br />

An auditor must look at how an auditee defines the process and necessary c<strong>on</strong>trols, and must establish some<br />

type of measurement system to ensure that the measurements or the process was properly defined. The<br />

auditor looks at the results of what other people have d<strong>on</strong>e, and if they used statistical tools, the auditor must<br />

be knowledgeable enough to decide whether the informati<strong>on</strong> being gathered from the data is valid.<br />

Descriptive Statistics<br />

The phase of statistics that seeks <strong>on</strong>ly to describe and analyze a given group (sample) without drawing any<br />

c<strong>on</strong>clusi<strong>on</strong>s or inferences about a larger group (populati<strong>on</strong>) is referred to as deductive or descriptive statistics.<br />

Measures of central tendency and dispersi<strong>on</strong> are the two most fundamental c<strong>on</strong>cepts in statistical analysis.

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