# How to Read Scientific Graphs & Charts

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• 0:41 Data in Tables and Line Graphs
• 3:58 Interpreting Line Graphs
• 5:30 Bar Charts, Pie…
• 9:05 Lesson Summary

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Lesson Transcript
Instructor: April Koch

April teaches high school science and holds a master's degree in education.

How do scientists summarize their findings with visual aids? In this lesson, explore the different types of tables, charts and graphs that scientists use. Learn to read these effectively as a preview to your science studies.

## Representation of Scientific Work

The scientific method is a set of procedures that scientists use to learn about the world. Scientists generally follow this method, but they also compete and collaborate on their work in order to reach a consensus within the scientific community. Sometimes, a scientist's work can take years to complete, but he still has to communicate his ideas to others. How do scientists summarize their findings so that other scientists can understand it in a matter of minutes? The answer is in the tables, graphs and charts that illustrate their data. In this lesson, we'll look at the basic types of charts and learn how to read them effectively.

## Data in Tables & Line Graphs

Let's say that you were a scientist who wanted to investigate how fast a sunflower grows compared with a daisy. You'd plant a sunflower seed and a daisy seed, grow them both with plenty of sunshine and water and measure the height of each plant every day. To keep all of your measurements organized, you'd likely use a table. Most scientists use tables as a way of arranging information into vertical columns and horizontal rows. Tables are useful for data that describes two different factors, or variables, because it reads in two directions. In your plant growth experiment, you'd collect data about two different things: time and the height of the plants. Let's say you'd record time measurements in the first column and the measurements for plant height in the second column. To be clear, you'd specify which units you're using for each variable. This is what a basic table looks like for most scientific experiments.

The two variables that you're recording are different, in that one variable is dependent upon the other. Since the height of the plant changes due to the passage of time, we say that height is dependent on time. So in this case, height is called the dependent variable. A dependent variable is the factor being measured in an experiment, which changes in response to the independent variable. The factor that's not dependent on anything is time. That is, nothing is going to change how time elapses during the experiment. Therefore, we call time the independent variable. It is the factor that is considered to be constant during an experiment, which affects the dependent variable. In tables, the independent variable is usually listed in the first column and the dependent variable is listed to the right.

But remember, you'll need to add a third column to collect your data about the daisy. Every day, you'll make two measurements: one of the height of the sunflower plant and one of the height of the daisy plant. So you should be filling up one row for every day in your experiment. By the time the experiment's done, your table should be full of useful data.

This table is a great way to keep your data organized. But it's not so easy to draw any conclusions by taking a quick glance. A better way to look at this information would be to transform it into a line graph. A line graph depicts the relationship between the dependent and independent variables. Each variable is plotted along one of the two axes in the graph. The x-axis is the horizontal axis, which usually plots the independent variable. Since your independent variable is time, then you'd plot time in days along the x-axis. The other axis is called the y-axis. This is the vertical axis that usually plots the dependent variable. So your dependent variable is plant height. You're actually going to have two lines on the graph: one to show the growth of the sunflower plant, and one to show the growth of the daisy. Let's make the sunflower line orange and the daisy line blue. You'll need to add a key to the bottom to show which line describes the growth of which plant.

As you're transferring your data, you'll need to be sure to plot all the numbers correctly. The first measurement for the sunflower says that it was half a centimeter tall on the first day. So you'd find the first day on the x-axis, and draw a dot that lines up with '0.5 centimeters' on the y-axis. You'd continue the same way for all of your data in the second column. Then, to plot the growth of the daisy, you'd use the data from the third column and draw the line in blue.

## Interpreting Line Graphs

Creating a graph is pretty simple, but interpreting it can be tricky. Looking at our graph of plant growth rates, what kind of conclusions can we make? Well, we can easily see that the sunflower grew faster than the daisy on average. It reached a greater height in the first nine days, and it sprouted a full day ahead of the daisy. By comparing the slope of the lines at separate intervals, we can also see that the sunflower had the highest peak growth rate. In other words, the highest growth speed in the sunflower was greater than that of the daisy.

Alright, enough with the easy stuff! Let's take a look at a less familiar line graph. Can you read and interpret a graph like this? It looks like it's relating the percentage of basal metabolic rate to the time that has passed after eating a meal. They've put time on the x-axis (as the independent variable), just like you did in your plant growth chart. The dependent variable here is the percentage of basal metabolic rate. Um, do you know what basal metabolic rate is? Well, guess what? You don't have to! To interpret this chart, you just need to see that proteins, carbohydrates and lipids account for different percentages that fluctuate over several hours. It looks like carbohydrates account for the highest percentage in the first 45 minutes. But after that, proteins win out and take the highest percentage. Proteins peak at about 30 percent, and lipids stay fairly constant as the lowest contributor. You see how easy it can be to read a line graph? I don't even have to understand the terminology. I only need to use the labels and the x- and y-axes to interpret the relationship between these two variables.

## Bar Charts, Pie Charts & Flow Charts

Line graphs aren't the only way that scientists represent their data. Different types of charts may be better suited for the type of information a scientist wants to show. All charts are visual representations of data that use symbols to indicate information. In a line graph, the data is represented in lines. But data can also be represented as bars in a bar chart or wedges in a pie chart. Let's take a closer look at these two charts.

### Bar Charts

In a bar chart, information is represented in rectangular bars that are proportional in length to the data. Here's a typical bar chart depicting numerical values for several geographic regions. Without even knowing what the values represent, we can tell from the relative heights of the bars that the United States has the most, Japan has the least and South Africa and Europe are somewhere in the middle. We typically use a bar chart when we want to compare the amounts of something between unrelated groups.

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