Graphing Tutorial

This tutorial is designed to try and help you understand the basics of graphical interpretation. Please work through the entire tutorial.

Click on the Y-axis.

Question 1 I'm sorry, you didn't click on one of the axis. Please try again.

Question 1

Yes, you chose the green axis, and the Y-axis is the verticle axis.

Question 1

NO, the Y-axis is the verticle axis (runs up and down), you clicked on the horizontal axis (runs left to right. This is called the X-axis.

Question 2

What are the units of the Y-axis?
(A) Individuals
(B) Frequency
(B) Proportion
(C) None of the above

Yes, the units on the Y-axis are individuals. Because the values are given in whole numbers rather than percentages you know it can't be a frequency.

No, frequencies must be between 0.0 - 1.0. Since the values on the Y-axis are in whole numbers they can't be frequencies.

No, proportions must be between 0.0 - 1.0. Since the values on the Y-axis are in whole numbers they can't be frequencies.

No, one of the answers is correct.

Click on the graph(s) that have transformed variables in them.

No, this graph does not have any of the variables transformed. Typicall if the variable is transformed you can tell because the scale looks different.

Yes, this graph has had its X-axis log10 transformed. You can tell this because it is an equal distance from 1 - 10, as between 10 - 100, and 100 - 1000.
Other graphs also have transformed data, have you found them all?

No, this graph does not have any of the variables transformed. Typicall if the variable is transformed you can tell because the scale looks different.
Other graphs also have transformed data, have you found them all?

Yes, this graph has had its Y-axis log10 transformed. You can tell this because it is an equal distance from 1 - 10, as between 10 - 100, and 100 - 1000.
Other graphs also have transformed data, have you found them all?

Yes, this graph has had its X-axis log10 transformed. You can tell this because it is an equal distance from 1 - 10, as between 10 - 100, and 100 - 1000. Any type of numerical data can be transformed, so don't let the units fool you.
Other graphs also have transformed data, have you found them all?

Yes, both of the X- and Y-axis have been log transformed using base 10. You can tell this because it is an equal distance from 1 - 10, as between 10 - 100, and 100 - 1000.
Other graphs also have transformed data, have you found them all?

How many different groups of data are there on this graph?

No, you can always tell how many different groups of data there are by the number of different symbols on the graph. On this graph there are more than 1 types of symbols.

No, you can always tell how many different groups of data there are by the number of different symbols on the graph. On this graph there are more than 2 types of symbols.

Yes, there are three different symbols on the graph, thus there must be three different groups of data the scientist wants us to notice.

No, you can always tell how many different groups of data there are by the number of different symbols on the graph. On this graph there are less than 4 types of symbols.

What is the shape (also called distribution) of the data like in this graph?

Yes, a normal distribution is bell shaped. That means that most frequently observed value is the mean value.

No, a normal distribution is bell shaped, like the graph above.
You said that this was a uniform distribution. In a uniform distribution all values are observed with equal probability, so the graph would look like this,

No, a normal distribution is bell shaped, like the graph above.
You said that this was a skewed distribution. In a skewed distribution the shape is more like a deformed bell where on side (tail) is stretched out further than the other side. The distribution is said to skewed towards the side that has the longer tail. For example, a right skewed distribution would look like this,

No, a normal distribution is bell shaped, like the graph above.
You said that this was a bimodal distribution. In a bimodal distribution there are two peaks in occurances, so you should see two humps or spikes. For example, a bimodal distribution would look like this,

Question 6

Click on the axis that represents the independent variable.

Yes, you said that the independent variable was the green line (X-axis). The convention is that the X-axis represents the independent variable. Thus the Y-axis represents the dependent variable, which means that the Y-values depend on the X-values. In this case as the X-value increases so does the Y-value so it is called a positive relationship.

No, you said that the independent variable was the green line (Y-axis). The convention is that the X-axis represents the independent variable. Thus the Y-axis represents the dependent variable, which means that the Y-values depend on the X-values. In this case as the X-value increases so does the Y-value so it is called a positive relationship.

Question 6 I'm sorry, you didn't click on one of the axis. Please try again.

What type of relationship is shown in this graph?
(A) asymptotic
(B) exponential
(C) sigmoidal

No, you said that this relationship is asymptotic. An asymptotic is one where the Y-value increases as the X-value increases, but the rate at which it increases slows so that eventually the Y-vale is not increasing at all. An asymptotic relationship looks like this,

Note: the above description is of a positive asymptotic relationship. You can also have a negative asymptotic relationship where the Y-value continually decreases as the X-value changes but eventually the Y-value stops changing.

Yes, you said that this relationship is exponential. An exponential relationship is one where when the X-variable increase the Y-variable increases also, but the Y-variable increases at a faster rate than the X-variable does. This gives an exponential relationship its characteristic shape of a curved line where the slope increases until it reaches 1.
Note: the above description is of a positive exponential relationship. You can also have, among others, a negative exponential relationship that would look like this,

No, you said that this relationship is sigmoidal. In a sigmoidal relationship the Y-values increase with the X-values but they increase more quickly, and they only do so for a while. Eventually the Y-values start to increase more slowly than the X-values do finally stopping to increase at all. A sigmoidal relationship looks like the one below.

Question 8

Click on thegraph that shows a positive relationship between body weight and body size?

No, remember you have to look at the axis. This graph shows that there is a relationship between body weight and head size.

No, this graph shows a negative relationship between body weight and body size. A positive relationship is one where when the X-value increases the Y-value also increases.

No, this graph shows no relationship between body weight and body size. A positive relationship is one where when the X-value increases the Y-value also increases. In this graph the X- and Y-values seem to change independently of each other.

Yes, this graph shows a positive relationship between body size and body weight. A positive relationship is one where when the X-value increases the Y-value also increases.

What does this graph tell you?
a) The number of individuals in the population depends on the per capita birth rate.
b) the per capita birth rate gets lower as time goes on.
c) the per capita birth rate of each individual depends on the number of individuals in the population.
d) the population's birth rate is high when the number of individuals in the population is low.

You said that this graph,

tells you (a) that the number of individuals in the population depends on the per capita birth rate.
no -- in any graph, the thing that is plotted on the vertical (y) axis is the "dependent" variable. So this graph tells you that birth rate depends on N, not the other way around.

You said that this graph,

tells you that (b) the per capita birth rate gets lower as time goes on.
no -- this graph tells you nothing about time. The horizontal axis is N, or population size, not time. The first step in interpreting a graph is always to figure out what the axes represent.

You said that this graph,

tells you that (c) the per capita birth rate of each individual depends on the number of individuals in the population.
Yes! the vertical or dependent axis is birth rate, so this graph means that birth rate depends on N. Specifically, it tells you that the average individual produces many kids when N is low, but only a few kids if N is high.

You said that this graph,

tells you that d) the population's birth rate is high when the number of individuals in the population is low.
no -- you've correctly worked out that birth rate is the dependent variable here, but "b" is the number of kids produced by an individual, not the number of births to the whole population.

Question 10

Click on the graph that shows that the number of matings a bird gets is related to the length of the bird's tail.

No, this graph shows no relationship between tail length and the number of maitings the bird receives. If you look, the birds with the shortest tail lengths get the same number of matings as the birds with the longest tail and the birds with the second longest tail get the most matings.

Yes, this graph shows that the shorter a bird's tail is the more matings the individual gets. There is also another graph which shows a realtionship between tail length and maitings.

Yes, this graph shows that the longer a bird's tail is the more matings the individual gets. There is also another graph which shows a realtionship between tail length and maitings.

No, this graph shows that no matter what the tail length of the bird is, they get the same number of matings.

Question 11

In Yellowstone National Park red fox coat color can be several different colors, including red, gray and black and it seems that the gray coat color is found most commonly in high elevation, and red coat colors are most common in low elevations. Click on the graph that supports this suggestion.

No, while this graph does show that red coat colors are most common in low elevations it also indicates that the gray coat color is most frequent at middle elevations and lowest at high elevations.

No, this graph shows the opposite of what the question asked. In this graph the red coat color is most common in the high elevations (the tallest bar) and lowest at low elevations (the shortest bar), while the gray coat color is most frequent in the low elevations (the tallest bar) and lowest in the high elevations (the shortest bar).

No, this graph indicates that the gray coat color is the most common at all elevations, its bar is always the tallest.

Yes, this graph shows that the red coat is most frequent at low and middle elevations (the tallest bar) and lowest at high elevations (the shortest bar). The gray coat color on the other hand is most common in the high elevations (tallest bar) and least common in all other areas (shortest bar).

This is the end of the tutorial. Time to stroll on out of here, I hope that you found it helpful.