Almost every student studies statistics graphs and charts in their academic lives. These charts and graphs are used for the representation of complex data into a more straightforward form.
Do you still remember all the graphs you have studied in your schools or colleges?
Most probably No, because we select different subjects after passing matrices and make a career in those fields.
But statistics students are well aware of these graphs, how to use them, and the purpose of these graphs in statistics.
If you are interested to know about the graphs widely used in statistics, you are at the right place. This blog will explore some commonly used of Statistics Graphs and why we use these graphs to represent the data.
The data in graphs cover a wide range of knowledge and information. Statisticians use various types of graphs in statistics to represent data in an easy-to-understand form. Below we are going to discuss some common types of statistics graphs.
Types of statistics Graphs
The graphs that are mostly used in statistics for data representation are bar graphs, line graphs, pie graphs, histograms, etc.
All these graphs represent a particular set of data in different places concisely. We will explain these graphs further so that you can understand the purpose of these graphs and how to select the correct type of graph according to data and information.
The pictorial representation of statistical data into graph format is known as statistics graphs. Statistics graphs are also very helpful to reveal data features and characteristics to make it simple and easy to understand and interpret. Below are the types of graphs we commonly use in statistics.
Bar graph consists of vertical or horizontal rectangular bars to represent data. The length of bars varies with the measurement of data. Moreover, the horizontal axis of a bar graph represents categorical data; however, the vertical axis implies discrete data.
A bar graph is also known as Pareto Diagram and can be single, grouped, and stacked. It is easy to compare the data or check the performance of data with the help of bars.
The bar graph shows the changes and trends over time, and we can identify patterns with this data.
For example you need to compare independent variables such as number of people who like different cuisines all over the world be it an italian, chinese, indian, maxican foods etc. You can easily represent them with the help of bars in a bar graph with different cuisine categories.
A line that covers all the points and defines a relation between these points. It reveals the data between two varying variables with a line or curve. It compares the variables either horizontally or vertically.
Statisticians use the line graph to detect the trends and patterns with the help of data that varies with the passage of time.
For example, a line graph can represent the number of tourists in different months of a year for a particular place or different places as well. Here you can notice the increasing or decreasing trends for different time periods.
A pie chart refers to a circle divided into different sections or sectors and represents qualitative data in percentage. Here individual sectors show the proportion of specific elements as a total value. The sum of the percentage of all the sectors should be equal to 100%.
Each slice of a pie refers to different categories with information of a trait or attribute. This chart is helpful for you in order to compare data respective to different categories or sectors.
Suppose you want to compare the students in different streams in a school, you can use a pie chart to represent the number of students in percentage with respect to different categories such as science, arts, medical, commerce, etc. Each section will show the total number of students in different streams.
In the histogram, with the help of rectangular bars, we represent the frequency of discrete and continuous data. Here rectangular bars show the numbers of observations that come in a predefined class interval.
The bottom displays the ranges of values(classes), and large frequency classes show the taller bars.
A histogram looks like a bar graph, but their level of measurement is different. Well, this is not the end of statistics graphs, a statistician uses in the different statistical calculations.
In this blog we have discussed some commonly used statistics graphs for data representation. Moreover, statisticians need to represent different data with different methods that are easy to read and understand.
In order to take valuable information, these graphs help all the viewers make different decisions regarding numerous actions. I hope this blog will be helpful for you in terms of understanding different graphs for data representation in statistics.