Data Set

 A dataset is a set of data or a collection of data. Typically, this data is displayed in a tabular manner. Each column represents a separate variable. And, according to the question, each row corresponds to a specific data set member. This is a necessary step in the data management procedure. Unknown quantities like as an object’s height, weight, temperature, volume, and other attributes, as well as the values of random numbers, are described by data sets. Each row in the data collection corresponds to one or more members’ information.

Types of Datasets

Different sorts of data sets are accessible in statistics for different types of information. They are as follows:

1. Numerical data sets
2. Bivariate data sets
3. Multivariate data sets
4. Categorical data sets
5. Correlation data sets

Lets discuss about each type in detail:

1. Numerical Data Set:

 A numerical data set is one in which the information is expressed in numbers rather than natural language. Quantitative data is a term used to describe numerical data. The numerical data set is the collection of all quantitative/numerical data. Numerical data is always in the form of numbers, allowing us to execute arithmetic operations on it.

A person’s weight and height

In a medical report, the number of RBCs is counted.

The number of pages in a book.

1. Bivariate data set:

A bivariate data set is one that contains two variables. It is concerned with the relationship that exists between the two variables. Typically, a bivariate dataset has two categories of connected data.

To find the percentage score and the age of the pupils in a class, for example. Two variables can be considered: score and age.

Ice cream sales vs. the temperature on that particular day. Ice cream and temperature are the two factors here.

1. Multivariate dataset: 

A multivariate dataset is defined as one that has three or more data kinds (variables). To put it another way, the multivariate dataset is made up of individual measurements taken as a function of three or more factors.

For instance, if we need to determine the length, breadth, height, and volume of a rectangular box, we must utilize many variables to differentiate between those things.

1. Categorical Datasets:

Categorical data sets represent a person’s or an object’s attributes or qualities. A categorical variable, also known as a qualitative variable, exists in the categorical dataset and can take just two values. As a result, it’s known as a dichotomous variable. Polytomous variables are categorical data/variables that have more than two possible values. Unless otherwise stated, qualitative/categorical variables are frequently believed to be polytomous variables.

Example:

The person’s Gender (male or female)

Status of marriage (married/unmarried)

1. Correlation Datasets:

Correlation data sets are a collection of variables that have some sort of relationship with one another. The values are found to be interdependent in this case.

A statistical relationship between two entities/variables is defined as correlation. In some cases, you may be required to forecast the relationship between the variables. Understanding how correlation works is critical. There are three different sorts of correlations. They are as follows:

Two variables move in the same direction when they have a positive correlation (Either both are up or both or down)

Two variables move in opposite directions when they have a negative correlation. (One variable is higher than the other, and vice versa.)

There is no or very little association between two variables.

A tall individual, for example, is thought to be heavier than a short person. As a result, the weight and height factors are interdependent.

Datasets: Mean, Median, Mode and Range 

Before calculating the required mean, median , mode and range we must first prepare our data set by rewriting it from least to greatest in ascending order.

The average of all the observations in a table is the dataset’s mean. It’s the ratio of the total number of elements in the data collection to the sum of observations. The mean formula is as follows:

Mean = Total Number of Elements in Data Set / Sum of Observations

When data is sorted in ascending and descending order, the median of the dataset is the middle value.

The variable, number, or value in a dataset that is repeated the most times in the set is called the mode.

A dataset’s range is the difference between its maximum and minimum values.

Range = Maximum Value – Minimum Value

Dataset Properties

Understanding the nature of the data is critical before undertaking any statistical analysis. Different Exploratory Data Analysis (EDA) techniques can be used to help uncover data features so that relevant statistical procedures can be applied to the data. The following properties of the dataset can be checked using EDA techniques.

• The data center
• Data skewness
• Members of the data are dispersed.
• Outliers are present
• There is a correlation of the data.

Conclusion:

 A dataset is a collection or set of data. This information is usually presented in a tabular format. Each column denotes a distinct variable. According to the question, each row has relation with a certain member of the data set. This is part of the data management process. The Data sets describe the values for every variable for unknown quantities such as a height of the object, weight, temperature, volume, and other characteristics, as well as the values of random numbers. Each row in the given data collection corresponds to data of one or more members.