Organisation of Data Class 11 Economics

Classification of Data

Classification is the technique of categorizing data into groups that share common characteristics or features. It involves sorting data into homogeneous classes or groups based on their similarities.

Data in its raw form is often difficult to comprehend and unsuitable for analysis and interpretation. The organization of data into categories aids in its comparison and analysis. For instance, the population of a town can be categorized based on factors like gender, age, marital status, and so on.

Objectives of Data Classification

• Simplification and Briefness
• Utility
• Distinctiveness
• Comparability
• Scientific arrangement
• Attractive and effective

Characteristics of a Good Classification

• Comprehensiveness
• Clarity
• Homogeneity
• Suitability
• Stability
• Elastic

Raw Data

Raw data is unstructured and requires processing and organisation before it can be used effectively to derive meaningful insights.

Chronological Classification

Chronological classification is a method of categorising data based on time, where the data is arranged either in ascending or descending order with respect to a particular time frame such as years, quarters, months, or weeks. This type of classification is also referred to as "temporal classification".

Geographical Classification

Geographical Classification refers to the classification of data based on geographical locations such as countries, states, cities, districts, etc. It is also known as Spatial Classification.

Qualitative Classification

Qualitative Classification is a type of data classification that provides descriptive information about the quality of something or someone. For example, skin colour, eye colour, hair texture, etc. can give us qualitative information about a person.

Condition Series

Condition Series involves the classification of data according to changes occurring in variables under specific conditions. Variables such as height, weight, age, marks, income, etc. can be used for condition series.

Attributes

Attributes refer to additional information about the characteristics of each spatial data in the survey. For instance, in a population survey, attributes of the individuals may include their name, age, height, weight, etc.

Variable

Variable refers to a characteristic that varies or changes from one investigation to another, such as person to person, time to time, or place to place. It can be a quantity or attribute that has different values.

Class Limits

Continuous variables refer to variables that can take any possible value (including fractions) within a specified range. Examples of continuous variables include temperature, height, weight, and marks.

Class Interval or Class Width

Discrete variables, on the other hand, are variables that can only take exact values and not fractional values. For example, the number of workers or students in a class is a discrete variable, as is the number of children in a family.

Class Mid Point or Class Mark

A frequency distribution table is a comprehensive way of representing the organization of raw data of a quantitative variable. This table shows how various values of a variable are distributed and their corresponding frequencies. Frequency distributions can be classified as discrete or continuous.

• Class limits are the numerical figures that specify the lower and upper limits of a class interval.
• A class interval (or class width) is an interval used to group variable values. For example, a group of people can be classified according to age group, with class intervals such as 15-19 years, 20-24 years, 25-29 years, and so on.

Class Mid Point or Class Mark

The class midpoint (or class mark) is the number in the middle of a class interval, found by adding the upper and lower limits and dividing them by two.

Frequency Curve

A frequency curve is obtained by joining the points of a frequency polygon through a freehand smoothed curve rather than straight lines.

Tally Marking

Tally marking is a method of keeping count using a unary numeral system. The general way of writing tally marks is as a group or set of five lines, where the first four lines are drawn vertically and the fifth line runs diagonally over the previous four vertical lines. Tally marks were used in earlier times when keeping track of individual belongings, such as domestic animals like goats and cows, was challenging.

Frequency Array 

A frequency array is a way of organizing data for a discrete variable, showing the different values of the variable along with their respective frequencies.

Bivariate Frequency Distribution 

When the frequency distribution involves two variables, it is called a bivariate frequency distribution. This type of distribution shows the frequencies of two variables together, such as the income and expenditure data of households.

Univariate Frequency Distribution 

A statistical data series that shows the frequency of only one variable is referred to as univariate frequency distribution. This type of frequency distribution displays the frequency distribution of a single variable, such as the income of people or marks scored by students.

Multivariate Distribution 

Multivariate distributions represent the correlation between at least two estimates and the relationships among them. For each univariate distribution with one random variable, there is a broader multivariate distribution. For example, the univariate normal distribution has a broader counterpart, the multivariate normal distribution, which is the most commonly used model for examining multivariate data. However, there are other types of multivariate distributions as well, including the multivariate lognormal distribution, the multivariate binomial distribution, etc.