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Introduction

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Decision makers make better decisions when they use all available information in an effective and meaningful way. The primary role of statistics is to to provide decision makers with methods for obtaining and analyzing information to help make these decisions. Statistics is used to answer long-range planning questions, such as when and where to locate facilities to handle future sales. 2

Definition

s Statistics is defined as the

science of collecting, organizing, presenting, analyzing and interpreting numerical data for the purpose of assisting in making a more effective decision. 3

Applications in Management

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Accounting Public accounting firms use statistical sampling procedures when conducting audits for their clients. Economics Economists use statistical information in making forecasts about the future of the economy or some aspect of it.

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Applications in Management

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Marketing Electronic point-of-sale scanners at retail checkout counters are used to collect data for a variety of marketing research applications. Production A variety of statistical quality control charts are used to monitor the output of a production process.

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Types of Statistics

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There are two types of statistics 1. Descriptive Statistics is concerned with summary calculations, graphs, charts and tables. 2. Inferential Statistics is a method used to generalize from a sample to a population. For example, the average income of all families (the population) in India can be estimated from figures obtained from a few hundred (the sample) families. 6

Statistical Population

s A Population is a collection of all

distinct individuals or objects or items under study. The number of entities in a population, Called the Population Size, is denoted by N s A descriptive measure of a population is called a Parameter

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Sample

s A Sample is a part of a

population and the sample size is denoted by n. A sample should be a representative of the population. population is called a Statistic

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s A descriptive measure of a

Data and Data Sets

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Data are the facts and figures collected, summarized, analyzed, and interpreted.

The data collected in a particular study are referred to as the data set.

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Elements, Variables, and Observations

The elements are the entities on which data are collected. A variable is a characteristic of interest for the elements. The set of measurements collected for a particular element is called an observation. The total number of data values in a complete data set is the number of elements multiplied by the number of variables.

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Data, Data Sets, Elements, Variables, and Observations

Observation

Element Names Variables

Company Dataram EnergySouth Keystone LandCare Psychemedics

Stock Annual Earn/ Exchange Sales($M) Share($) NQ N N NQ N 73.10 74.00 365.70 111.40 17.60 Data Set

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0.86 1.67 0.86 0.33 0.13

Scales of Measurement

Scales of measurement include:

Nominal Ordinal Interval Ratio

The scale determines the amount of information contained in the data. The scale indicates the data summarization and statistical analyses that are most appropriate.

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Scales of Measurement

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Nominal

Data are labels or names used to identify an attribute of the element. A nonnumeric label or numeric code may be used.

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Scales of Measurement

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Nominal

Example: Students of a university are classified by the school in which they are enrolled using a nonnumeric label such as Business, Humanities, Education, and so on. Alternatively, a numeric code could be used for the school variable (e.g. 1 denotes Business, 2 denotes Humanities, 3 denotes Education, and so on).

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Scales of Measurement

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Ordinal

The data have the properties of nominal data and the order or rank of the data is meaningful. A nonnumeric label or numeric code may be used.

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