What charts are used for quantitative data
Quantitative data is information about quantities; that is, information that can be measured and written down with numbers. Some other aspects to consider about quantitative data:. A diagram in which the numerical values of variables are represented by the height or length of lines or rectangles of equal width. A diagram consisting of rectangles whose area is proportional to the frequency of a variable and whose width is equal to the class interval.
Graphs for Quantitative Data
Using this table, it would be possible to create a standard bar chart from this summary, like we did for categorical data:. It would be more correct to treat the horizontal axis as a number line. This type of graph is called a histogram.
Notice that in the histogram, a bar represents values on the horizontal axis from that on the left hand-side of the bar up to, but not including, the value on the right hand side of the bar.
Unfortunately, not a lot of common software packages can correctly graph a histogram. About the best you can do in Excel or Word is a bar graph with no gap between the bars and spacing added to simulate a numerical horizontal axis. If we have a large number of widely varying data values, creating a frequency table that lists every possible value as a category would lead to an exceptionally long frequency table, and probably would not reveal any patterns.
For this reason, it is common with quantitative data to group data into class intervals. Suppose that we have collected weights from male subjects as part of a nutrition study. We could create 7 intervals with a width of around 20, 14 intervals with a width of around 10, or somewhere in between.
Often time we have to experiment with a few possibilities to find something that represents the data well. Let us try using an interval width of We could start at , or at since it is a nice round number. In many software packages, you can create a graph similar to a histogram by putting the class intervals as the labels on a bar chart. Other graph types such as pie charts are possible for quantitative data. The usefulness of different graph types will vary depending upon the number of intervals and the type of data being represented.
For example, a pie chart of our weight data is difficult to read because of the quantity of intervals we used. The total cost of textbooks for the term was collected from 36 students. Create a histogram for this data.
When collecting data to compare two groups, it is desirable to create a graph that compares quantities. The data below came from a task in which the goal is to move a computer mouse to a target on the screen as fast as possible. On 20 of the trials, the target was a small rectangle; on the other 20, the target was a large rectangle. Time to reach the target was recorded on each trial.
An alternative representation is a frequency polygon. A frequency polygon starts out like a histogram, but instead of drawing a bar, a point is placed in the midpoint of each interval at height equal to the frequency. Typically the points are connected with straight lines to emphasize the distribution of the data. This graph makes it easier to see that reaction times were generally shorter for the larger target, and that the reaction times for the smaller target were more spread out.
Skip to main content. Describing Data. Search for:. Presenting Quantitative Data Graphically Quantitative, or numerical, data can also be summarized into frequency tables. Example 9 A teacher records scores on a point quiz for the 30 students in his class.
The scores are: 19 20 18 18 17 18 19 17 20 18 20 16 20 15 17 12 18 19 18 19 17 20 18 16 15 18 20 5 0 0 These scores could be summarized into a frequency table by grouping like values: Score Frequency 0 2 5 1 12 1 15 2 16 2 17 4 18 8 19 4 20 6 Using this table, it would be possible to create a standard bar chart from this summary, like we did for categorical data:. Histogram A histogram is like a bar graph, but where the horizontal axis is a number line.
Class Intervals Class intervals are groupings of the data. In general, we define class intervals so that: Each interval is equal in size. For example, if the first class contains values from , the second class should include values from Frequency polygon An alternative representation is a frequency polygon. Licenses and Attributions.
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Quantitative Data. No. Bar graphs, pie charts, line graphs, and histograms are an excellent way to A pie chart is a circular chart used to compare parts. Another common way to represent data graphically is a pie chart. It gets its name This type of graph is used with quantitative data. Ranges of.
Graphs should contain:. Descriptive statistics are numbers and processes that describe a group of data. The most common descriptive statistics focus on determining the "average" of the data. However, there is more than one "average," so we must be specific when finding them. As you can imagine, data sets very rarely are all one value.
With current technologies, it is possible for almost anyone to distill quantitative data into text, or more visually, into a table or chart.
Skip to content. Skip to navigation. For a printer-friendly PDF version of this guide, click here This guide offers practical advice on how to incorporate numerical information into essays, reports, dissertations, posters and presentations.
Presenting numerical data
Making sense of facts, numbers, and measurements is a form of art — the art of data visualization. There is a load of data in the sea of noise. To turn your numbers into knowledge, your job is not only to separate noise from the data, but also to present it the right way. Many of us come from the "PowerPoint generation" — this is where the roots of our understanding of data visualization and presentation lie. Unfortunately, it is far from anything related to good, and I stand before you as guilty myself.
Data Visualization: Quantitative vs. Qualitative
One goal of statistics is to present data in a meaningful way. This is far too many to print out in a journal article or sidebar of a magazine story. That's where graphs can be invaluable, allowing statisticians to provide a visual interpretation of complex numerical stories. Seven types of graphs are commonly used in statistics. Good graphs convey information quickly and easily to the user. Graphs highlight the salient features of the data. They can show relationships that are not obvious from studying a list of numbers. They can also provide a convenient way to compare different sets of data. Different situations call for different types of graphs, and it helps to have a good knowledge of what types are available. The type of data often determines what graph is appropriate to use.
A plot is a graphical technique for representing a data set, usually as a graph showing the relationship between two or more variables.
Using this table, it would be possible to create a standard bar chart from this summary, like we did for categorical data:. It would be more correct to treat the horizontal axis as a number line. This type of graph is called a histogram.
7 Graphs Commonly Used in Statistics
There are many types of graphs that can be used to portray distributions of quantitative variables. The upcoming sections cover the following types of graphs: 1 stem and leaf displays, 2 histograms, 3 frequency polygons, 4 box plots, 5 bar charts, 6 line graphs, 7 scatter plots discussed in a different chapter , and 8 dot plots. Some graph types such as stem and leaf displays are best-suited for small to moderate amounts of data, whereas others such as histograms are best-suited for large amounts of data. Graph types such as box plots are good at depicting differences between distributions. Scatter plots are used to show the relationship between two variables. Quantitative Variables Author s David M. Height, weight, response time, subjective rating of pain, temperature, and score on an exam are all examples of quantitative variables. Quantitative variables are distinguished from categorical sometimes called qualitative variables such as favorite color, religion, city of birth, and favorite sport in which there is no ordering or measuring involved. Please answer the questions: feedback.
Data Visualization – How to Pick the Right Chart Type?
You will learn about the various excel charts types from column charts, bar charts, line charts, pie charts to stacked area charts. Data visualization is the presentation of data both qualitative and quantitative data in graphical format. Through data visualization you can easily:. Data presentation is a very important skill for an optimizer marketer, analyst. In fact, it is so valuable that LinkedIn lists it as one of the top skills that can get you hired. Excel charts are commonly used for data visualization and presentation.
