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1.7 Glossary of Terms

Statistics :

Statistics is the use of data to help the decision maker to reach better decisions.

Data :

It is any group of measurements that interests us. These measurements provide information for the decision maker. (I) The data that reflects non-numerical features or qualities of the experimental units, is known as qualitative data. (ii) The data that possesses numerical properties is known as quantitative data.

Population:

Any well defined set of objects about which a statistical enquiry is being made is called a population or universe.

The total number of objects (individuals) in a population is known as the size of the population. This may be finite or infinite.

Individual : Each object belonging to a population is called as an individual of the population.

Sample:

A finite set of objects drawn from the population with a particular aim, is called a sample.

The total number of individuals in a sample is called the sample size.


Characteristic:

The information required from an individual, from a population or from a sample, during the statistical enquiry (survey) is known as the characteristic of the individual. It is either numerical or non-numerical. For e.g. the size of shoes is a numerical characteristic which refers to a quantity, whereas the mother tongue of a person is a non-numerical characteristic which refers to a quality. Thus we have quantitative and qualitative types of characteristics.

Variate:

A quantitative characteristic of an individual which can be expressed numerically is called a variate or a variable. It may take different values at different times, places or situations.

Attribute:

A qualitative characteristic of an individual which can be expressed numerically is called an attribute. For e.g. the mother-tongue of a person, the color of eyes or the color of hair of a person etc.

Discrete
variate :

A variable that is not capable of assuming all the values in a given range is a discrete variate.

Continuous
Variate :

A variate that is capable of assuming all the numerical values in a given range, is called a continuous variate. Consider two examples carefully, viz. the number of students of a class and their heights. Both variates differ slightly, in the sense that, the number of students present in a class is a number say between 0 and 50; always a whole number. It can never be 1.5, 4.33 etc. This type of variate can take only isolated values and is called a discrete variate. On the other hand heights ranging from 140 cm to 190 cm can take values like 140.7, 135.8, 185.1 etc. Such a variate is a continuous variate.

Example

Individual

Characteristic

Type Of Characteristic

1

A person

Height in cm

®

Continuous variate

Color of eyes

®

Attribute

Age

®

Continuous variate

Weight in lbs

®

Continuous variate

Sex

®

Attribute

Mother tongue

®

Attribute

Marks in statistics

®

Discrete variate

2

Mr. Brown's family

Number of members

®

Discrete variate

Monthly income in dollars

®

Discrete variate

3

A washer

Diameter and thickness in cm

®

Continuous variate

Defective or non-defective

®

Attribute

Index

1.1 What is Statistics
1.2 Uses
1.3 Distrust of Statistics
1.4 Statistics can be misused
1.5 Types of Statistics
1.6 Common mistakes committed in interpretation of Statistics
1.7 Glossary Of Terms

Chapter 2





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