The following Topics and Sub-Topics are covered in this chapter and are available on MSVgo:

In statistics, the term “data handling” refers to a principle that protects the privacy of research data by addressing issues such as protection, confidentiality, and research data protection. This provides details in the form of numerical figures. This type of statistic is referred to as an observation. Data is the term used to describe the compilation of all observations. Statisticians use a variety of data collection techniques to deal with the data.

Data handling entails gathering a collection of data and displaying it in a new format. A list of numerical figures that reflects a certain type of information is referred to as data. The raw data is a list of measurements that are collected at the start. Every kind of data may be used. Words, figures, ratios, explanations, and observations are all possibilities. During and after the review phase, data handling is the process of ensuring that study data is collected, archived, or disposed of securely.

Depending on the types of data, different data handling methods may be used. The data is divided into two categories:

- Qualitative data
- Quantitative data

Quantitative data provides empirical statistics for something, while qualitative data provides descriptive information. The quantitative data is further classified into two categories here. There are two types of data: discrete and continuous. Only specific values, such as whole numbers, are allowed in discrete results. The continuous data will take any value that falls within the given range.

Quantitative data is the category of data, the significance of which is calculated in the form of numbers or counts, with a particular numerical value associated with each data collection. Quantitative data, also known as numerical data, further explains numeric variables.

The three indicators of central tendency are the mean, median, and mode. The arithmetic average of a data set is called the mean. This is calculated by multiplying the number of measurements in a data set by the sum total of the data set numbers. When numbers are classified in ascending or descending order, the median is the number in the centre. The range is the contrast between the highest and lowest values in a data collection, and the mode is the value that appears the most often.

**Mean **The “average” amount is calculated by multiplying all data points by the number of data points.

**Median **The middle number is determined by sorting all of the data points and selecting the one in the middle (or two middle numbers, taking the mean of those two numbers).

**Mode **The most occurring number—that is, the number that appears the most often.

The most common occurrence of ungrouped data is equivalent to the data’s mode. More than one mode may exist in data.

Unimodal data distributions have just one mode value, while multimodal data distributions have several mode values.

**Example:**

**Find the mode of the marks given below:**

**2, 3, 5, 6, 2, 4, 7, 8, 8, 7, 6, 8, 9, 2, 3, 6, 2, 3, 2, 4, 5, 7, 2, 5, 3, 2**

Solution:

Arrange the data in ascending order:

2, 2 ,2 ,2 ,2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 5, 5, 5, 6, 6, 6, 7, 7, 7, 8, 8, 8, 9

Therefore, mode: 2

Numbers, images, charts, graphics, and other data types will all be used to display data. Bar graphs are the most popular method of graphical representation of results. A bar graph, also known as a bar map, depicts a graphic interpretation of data using vertical or horizontal rectangular bars of similar width that are evenly spaced concerning one another and whose distances are relative to the data to be displayed.

**Example: **

Subject | English | Hindi | Maths | Science | Social Science |

1st Term (M.M. 100) | 67 | 72 | 88 | 81 | 73 |

2nd Term (M.M. 100) | 70 | 65 | 95 | 85 | 75 |

**In which subject has your friend improved his performance the most?****In which subject is the improvement the least?****Has the performance gone down in any subject?**

Solution:

- By observing the double bar graph, there was an increase in the Maths subject. So, the friend has improved his performance in Maths.
- By observing the double bar graph, the improvement was the least in Social Science.
- By observing the double bar graph, the performance in Hindi has gone down.

In this chapter, we learned about the basics of data handling. We learned about the **Probability Handling of Raw Data **and many more concepts.

Data handling types:**What are the various forms of data handling?**

- Graph with bars
- Pictograph
- Graph with a line

**In data handling, what is a mode?**

In data collection, the mode is the value that occurs the most often.

To keep track of books in libraries.**What role does data analysis play in our everyday lives?**

And keep track of the river’s water levels.**How many different kinds of data are there?**

Nominal, ordinal, discrete, and continuous data are the four types of data.

**What is the data handling median?**

The median is the point in a data set that is in the centre.