Data Visualization Concepts in Statistics

Learn about how the data are visualized in different ways

This is the continuation of the Statistics you can check out the first article here

Type of Data:

Visualizing Data:

visualizing Categorical Data:

The categorical data can be displayed in the way of Frequency Distribution Tables, Bar charts, Pie charts, and Pareto diagrams.

Frequency Distribution Table:c

Pie chart:

This chart is widely used in the market sector.

Pareto Diagram:

Pareto diagram uses 80–20 rule 80% of the effect comes from 20% of the causes. In Pareto diagram, it uses Cumulative frequency.

Visualizing Numerical Data:

we can use the Frequency Distribution Table and Histogram.

we can choose the class interval between 5 -20 I will take the desired interval as 5 and the interval width can be calculated by subtracting the large number and the small number from the dataset followed by several desired intervals.

In my case, the largest number from the dataset is 38 and the smallest number from my dataset is 1

By subtracting the largest number and the smallest number I got 37 and dividing by the number of the desired intervals I got 7.4 which will be taken as 8

• Relative Frequency can be calculated by

Categorical Variables Visualization:

The visualization of the categorical variables follows

1. Cross Tables
2. Scatter plots

Cross Tables :

This table uses a side-by-side bar chart.

Scatter plots:

mostly the visualization of the scatter plots is widely used to represent two numerical variables.

Measures Of Central Tendency :

1. Mean
2. Median
3. Mode

Mean:- It is used to calculate an average value which is denoted by μ for the population mean and x̄ (x bar) for the sample mean.

• Adding all components and dividing by the number of components.

Dataset: 1, 1, 1, 3, 3, 3, 5, 5

Median:-To find the mean arrange all the values in order and find the middle value.

When median has two values?

To find median for two value

Mode:- mode is defined as “most frequently occurring value” or counting the most repeated value. In other words, we can easily find out the mode value by a value that has multiple occurrences.

• Example:- Dataset: 4, 1, 5, 2, 1, 2, 4, 4, 5, 5, 4
• From the above dataset, 4 is the mode because it occurs frequently.

Bi-modal: If the mode has two mode values.

Multi-modal: multi-modal occurs when the dataset contains more than one mode is called multi-modal. It is the same as bi-modal.

• Dataset: 4, 4, 4, 4, 3, 2, 6, 5, 5, 8, 5, 7, 4, 5, 5
• From the above, we have two repeated values so it refers to multimodal.

Thank you

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