Anyone can learn for free on OpenLearn, but signing-up will give you access to your personal learning profile and record of achievements that you earn while you study. Start this free course now. Just create an account and sign in. Enrol and complete the course for a free statement of participation or digital badge if available. Discrete data is information that can only take certain values.
The number of each type of treatment a salon needs to schedule for the week, the number of children attending a nursery each day or the profit a business makes each month are all examples of discrete data. This type of data is often represented using tally charts, bar charts or pie charts. Continuous data is data that can take any value. Height, weight, temperature and length are all examples of continuous data. Some continuous data will change over time; the weight of a baby in its first year or the temperature in a room throughout the day.
This data is best shown on a line graph as this type of graph can show how the data changes over a given period of time. Other continuous data, such as the heights of a group of children on one particular day, is often grouped into categories to make it easier to interpret.
The best choice here is b the tally chart since you can add to this data as each customer makes their choice. A bar or pie chart would also be suitable. The only choice here is c the line graph as it shows how the temperature changes over time.
Each point, stroke, color, or shape on a graph has a different meaning that helps in interpreting a graph. They are of different types and vary in structure, with some having just points, others have points joined together by lines, and so on.
Although sometimes used interchangeably, it is important to note that there is a difference between graphs and charts. Summarily, we can say that all graphs are charts but not all charts are graphs. A graph is a mathematical diagram that depicts the relationship between two or more sets of numerical data over a period of time.
Basic data is mainly 2-dimensional with a focus on raw data represented through lines, curves, etc. Charts, on the other hand, is a representation of datasets with the intent of making the user understand the information in a better manner. Graphs are a good example of charts used for data visualization. There are various types of graphs and charts used in data visualization. However, in this article, we'll be covering the top 11 types that are used to visualize business data. A bar chart is a graph represented by spaced rectangular bars that describe the data points in a set of data.
It is usually used to plot discrete and categorical data. The horizontal axis of the chart represents categorical data while the vertical axis of the chart defines discrete data. Although the rectangular bars in a bar chart are mostly placed vertically, they can also be horizontal.
For horizontally placed rectangular bars, the categorical data is defined on the vertical axis while the horizontal axis defines the discrete data. Grouped bar charts are used when the datasets have subgroups that need to be visualized on the graph. Each subgroup is usually differentiated from the other by shading them with distinct colors.
The stacked bar graphs are also used to show subgroups in a dataset. But in this case, the rectangular bars defining each group are stacked on top of each other. This is the type of stacked bar chart where each stacked bar shows the percentage of its discrete value from the total value.
A pie chart is a circular graph used to illustrate numerical proportions in a dataset. This graph is usually divided into various sectors, where each sector represents the proportion of a particular numerical element in the set. Just like a pizza is divided into different slices, each sector in a pie chart represents the proportion of an element in the dataset. The proportion is defined by the degree of the sector and the percentage area with respect to the area of the circle.
In an exploded pie chart, one of the sectors of the circle is separated or exploded from the chart. It is used to lay emphasis on a particular element in the data set. As the name suggests, a pie of pie is a chart that generates an entirely new usually small pie chart from the existing one.
It can be used to reduce clutteredness and lay emphasis on a particular group of elements. This is similar to the pie of pie, with the main difference being that a bar chart is what is generated in this case rather than a pie chart. Line graphs are represented by a group of data points joined together by a straight line. Each of these data points describes the relationship between the horizontal and the vertical axis on the graph.
The value is presented by an anchor on the axis. This data point is connected with the axis by a line. As you may notice, it reminds a spider web; hence the name. We truly hope this overview will help you decide which charts are best suited for your data and get a general idea about how you can compare discrete groups of data graphically.
What is discrete data? Data is discrete if you can answer affirmatively on the following questions about it: Is it countable? Is it possible to divide the data into smaller parts? The following charts work especially well for representing the discrete data: Bar chart Stacked bar chart Column chart Stacked column chart Spider chart Bar chart The simplest and the most popular type of chart. Purpose Use it to compare data points that are spread across categories with each other.
Pros Makes data more readable if the categories have long names or if you have more than 10 categories Recommendation Arrange bars on the chart in a logical ordering: ascending or descending one Examples and variations A single-series chart in which the values are compared inside one category. Compare the population across different cities This is an example of a clustered grouped bar chart. When values in a data set are countable and can only take certain values, it is called discrete data.
For example, number of students in a class, number of players required in a team, etc. Bar graph is the most suitable way to represent discrete data, as finite values can be presented clearly through vertical or horizontal bars.
In frequency table , values are represented through tally marks and frequency of each variable. On number line , we marked the value of each variable on the number line. In a survey with 14 children on their favourite ice-cream flavour, it was found that 4 children like butterscotch flavour, 5 children like chocolate flavour, 3 children like vanilla flavour and 2 children like strawberry flavour of ice-cream.
It is an example of discrete data as we can count the number of children who like a particular flavour of ice-cream. Carefully observe the graphical representation of this data through all three modes of representation.
Given below are the representation of two different sets of data in two different forms of graph. Find which one of the following represents discrete data and why?
Amon the two graphs, on the right side we have histogram and on the left side, we have bar graph. Data given in bar graph represents discrete data as we consider number of girls class-wise in that graph that contains only finite values and is countable. While data given in histogram represents continuous data as we consider marks obtained by students within a range in that graph.
For example, 2 students obtained marks between 5 to 10, that means the marks could be any number within this range, for instance, 7. Look at the data given below of favourite sport of 58 people. Represent the data graphically and also write whether it is discrete data or not. Given data is an example of discrete data, as the values are given are whole numbers. We can count the number of people who like each sport. On the x-axis, we mention the names of favourite sport as it is an independent variable and on y-axis, we mention the number of people as it is a dependent variable.
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