Organisation of Data

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Organisation of data includes the gathering of essential information and concluding its conclusion through statistics. Through reading the explanation below, students can gather relevant information about what is organisation of data and ways of determining it.


Terms Determining Organisation of Data in Statistics

This method uses the classification of data which is an act of arranging similar things into groups or classes. This process eases out the collection of raw data and variables for calculation.


What is the Objective of the Classification of Data?

The objects are classified into five major types that are geographical, chronological, alphabetical,   quantitative, and qualitative. This is done for the following reasons -

  • To expand the idea of distinction.

  • To abridge the complex data.

  • To segregate data according to their characteristics and nature.

  • For easy analysis and calculation.

An organisation of data is characterized correctly when it has the following properties -

  • Homogeneity 

  • Clarity

  • Diversification

  • Suitability

  • Clarity

What is Raw Data in the Organisation of Data Class 11 Notes?

Raw data in the organisation of data is the unorganized information which is arranged to find out a comparison or conclusion.  It is calculated by an investigator who uses forms of series which are those data sets in sequence. One can organize a piece of information in the way of a numerical series. This base of the preparation of raw data can differ according to reason.


What is Variable in the Organisation of Data in Statistics?

Variables are usually data that can differ depending on time and measurement. It is an occurrence that can change over time. Ideally, a variable can be categorized into two types -

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(a) Discrete 

It is a variable whose value changes in the complete number or keeps rising with every jump. This variable signifies an amount that will never be infractions but whole numbers. 


(b) Continuous 

This variable is in fractional value, or its worth does not change with a jump. A good example will be the weight of students, etc.


What is the Basic Difference Between Bivariate and Univariate Frequency?

A frequency distribution is an inclusive way of classifying raw data and quantitative variables for statistics. It is done to estimate the different values of variables in the organisation of data distributed into class frequencies. There are two essential forms of frequencies - Univariate and Bivariate.


Variables

Bivariate Frequency

Univariate Frequency

Alternate name

Two-way frequency

One-way frequency

Definition

When data classified based on two or more variables, this distribution is known as bivariate.

When data is classified on one variable, it is called a univariate distribution.


The organisation of data is a vast chapter that deals with crucial concepts for an in-depth understanding of statistics. A student can read the notes offered by Vedantu, which gives a discrete idea about the related topics. Moreover, students can find budget-friendly live classes and solutions based on this topic from the site and app. Check Vedantu today!

FAQ (Frequently Asked Questions)

1. How is the Data Collected? What is its Primary Source?

Ans. Data is collected from distinctive sources. Ideally, there are two types of data, namely statistical data and non-statistical sources.  Statistical data gathered for official purposes and to include census for official surveys. An individual can file an RTI to collect information from variable sources. Non-statistical data are used for administrative purposes or the private sector. 


There are different sources of data - (a) Internal source: When data is collected from records or reports of an organization, it is called an internal source, (b) External Source: When data is collected from outside sources like newspaper, stock files, etc. It is known as an external source.

2. What is Raw Data in the Organization of Data?

Ans. Raw data is also known as atomic data or source data. It is information that has not been processed. Raw data that has gone through checking is sometimes called cooked data. Although raw data can become information, it is distinct in the end product. 


It ideally requires extraction, organizing, analyzing, and formatting for proper output. Once data is processed, it may indicate that a particular item an individual chooses and its demand based on price or other variables. Such information can be further used for an organization’s future endeavour like increasing sales.

3. What is the Basis of the Classification of Raw Data?

Ans. Raw data is ideally classified based on five factors. Those are – (a) Chronological classification: In this classification, the data is arranged in ascending or descending order based on time variables like years, months, quarter, weeks, etc., (b) Geographical classification: This data are classified concerning geographical location such as cities, countries, districts, states, block, etc., (c) Qualitative classification: These data are classified based on graphic characteristics like religion, sex, caste, literacy rate, etc. (d) Quantitative classification:  Quantitative data are classified based on some measurable characteristics such as weight, age, income, height, marks of students., (e) Conditional classification: When data are classified based on condition, this type of category is called conditional classification.