Organization of Data Class 11 Notes

Organization of data refers to the arrangement of figures in such a form that compares the mass of similar data. Here is the organization of data class 11 notes.

Classification

Classification is the grouping of related facts into different classes. In other words, the process of dividing data into different classes based on their similarity or diversity is called classification.

Objectives of Classification

• Simplification and briefness: The main objective of classification is to present data in a form that appears to be brief and simple.
• Utility: Classification enhances the utility of the data as it brings out similarities within the diverse set of data.
• Comparability: It makes data comparable and estimative.
• Distinctiveness: Classification renders obvious differences among the data more distinctly.
• Attractive and Effective: Classification makes data more attractive and effective.

Characteristics of good classification

• Elastic: There should be scope for change in the classification matching with the change in the purpose of our study.
• Comprehensiveness: Classification of the raw data should be so comprehensive that every item of the data gets into some group or class.
• Clarity: Classification of the raw data should be clear and simple.
• Stability: A particular kind of investigation should be based on the same set of classifications.
• Homogeneity: All items in a group or class must be homogenous or similar to each other.

Basis of Classification

1. Geographical Classification: This classification of data is based on geographical or locational differences of the data.
2. Chronological Classification: When data are classified based on time is known as chronological classification.
3. Qualitative Classification: This classification is according to the qualities or attributes of the data.
   a) Simple Classification: It is called classification according to dichotomy. This is because data is divided based on the existence or absence of quality.
   b) Manifold Classification: When classification according to quality of data involves more than one characteristic, it is called manifold classification.
4. Quantitative or Numerical Classification: Data is classified or grouped based on their numeric values. Quantitative classification is also called classification by variables.

Tabular Presentation of Data Class 11 Notes

Variable

A Characteristic or phenomenon capable of being measured and changing its value over time is called a variable. A variable may be either discrete or continuous.

Discrete Variable

These are those variables that increase in jumps or complete numbers.

Continuous Variable

Variables that assume a range of value or increase not in jumps but continuously or in fractions.

Raw Data

A mass of data in its crude form is called raw data. It is an unorganized mass of various items.

Series

Arranging data in different classes according to a given order and sequence is called a series.

Types of Series

1) Individual Series

These are those series in which the items are listed singly. These series may be presented in two ways:

• According to serial numbers
• Ascending or descending order of data

2) Frequency Series

These are of two types:

• Discrete Series/ Frequency Array: It is a series in which data is presented in a way that exact measurements of times are clearly shown.
• Frequency distribution: It is that series in which items cannot be exactly measured. The items assume a range of values and are proud within the range or limits.

Frequency = It is the number of times an item occurs.

Class Frequency = The number of times an item repeats itself corresponding to a range of values.

Types of Frequency Distribution

• Exclusive Series: It is a series in which every class interval excludes items corresponding to its upper limit.
• Inclusive Series: It is that series that includes all times up to its upper limit.
• Open Ended Series: It is a series in which the lower limit of the first class interval or the upper limit of the last class interval is missing.
• Cumulative Frequency Series: It is a series in which the frequencies are continuously added corresponding to each class interval in the series.
• Mid-Value Frequency Series: Mid-value frequency series are those series in which we have only mid-values of the class intervals and the corresponding frequencies.