Ocean Waves and Graphs A group of science students was on a kayaking trip in Puget Sound. They noticed that different waves seemed to travel at different speeds. One student described some waves as traveling over the top of other waves. Another student said that to her it looked more like the waves that she called slow rollers scooted underneath the others. The students decided to see whether they could find a pattern in the speeds of these waves. The students thought that the easiest things for them to measure would be the size and speed of the waves. They decided that they wanted to study some waves that looked different from each other and that it would take a lot of teamwork to get the job done. So with some students paddling, some holding boats still, and others making measurements, they measured the height, length, and speed of several waves. Measurements they made of eight waves are shown below. Height (ft) Length (ft) Speed (ft/sec) 0.3 0.8 5.1 0.5 0.5 4.0 0.8 9.5 17.4 1.0 4.9 12.5 1.2 1.9 7.8 1.3 3.6 10.7 1.7 1.2 6.2 1.9 6.3 14.2 So what do we learn from this? Does the height of the wave influence the speed? Does the length influence the speed? Does the height influence the length? The jumble of numbers above is hard to interpret. Your mission is to make graphs from this data and see if you can find patterns that help us learn about wave speeds. Since the students were interested in wave speed, we ll call that our responding variable or dependent variable. We have two choices for manipulated or
IDS 101 Ocean Waves and Graphs page 2 independent variable. We don t know which variable makes the most sense so we ll have to try both. It is customary for scientists to put the dependent (or responding) variable on the vertical or y axis of a graph. The independent (or manipulated) variable goes on the horizontal or x axis of the graph. We often use the language that the dependent variable is plotted as a function of the independent variable. In math classes we often think of y as a function of x. We ll make two graphs (you can use two sheets of graph paper). On each graph, plot the responding variable on the vertical axis and the manipulated variable on the horizontal axis as in the diagrams below. independent Eggs purchased A generic graph showing the orientations of dependent and independent variables. A real graph would have better labels to tell us what is being displayed. The meaning of a graph should be clear to all who read it. A graph showing the amount that would have to be spent to purchase different quantities of eggs. To be useful, this graph should also have a title and scales (numbers of eggs and units of money) on each axis. Now get some graph paper and make a couple of graphs. Make a different graph for each choice of independent variable. Make your graphs large enough so that they are easy to read (you can use one sheet for each graph if you like). While making your graphs, check them over to see if you remembered to include all of the features of a good graph. Here are some things a good graph should always have: Do your graphs have titles at the top so that a reader would immediately know what the graph is about)? Do the axes of the graphs have labels (on the left and on the bottom) so that the reader knows what is being graphed as a function of what? Do the axes have scales shown by tick marks labeled by numbers with units? The units can be shown in the label (as in length of wave in feet ) or they can be shown along the axes (as in 1 foot 2 feet 3 feet, etc.).
IDS 101 Ocean Waves and Graphs page 3 Once you have two graphs, compare your graphs with those of your classmates and try answering the following questions. Scientists often test their ideas or models by making predictions. Based on your graphs, predict the speed of a wave that is 0.7 ft high and 2.8 feet long. Which graph(s) did you use for your prediction? Why? Explain your reasoning. Scientists are often looking for correlations or connections between things. Which would you say is more closely correlated with the speed of a wave, the height or the length? Explain your reasoning. Be honest. Was the answer to the previous question as obvious when you first looked at the table of data on page 1? Why or why not?
IDS 101 Ocean Waves and Graphs page 4 End of Module Questions: 1. A student at the Knotvery Sound School used a microphone to record sounds made by an acoustic guitar. She plucked different strings and she used a video camera to measure how much the plucked string was vibrating (in millimeters). The microphone automatically measured the frequency (or note) in hertz (Hz) and the volume (or loudness) in decibels (db). The data is shown in the table below: Vibration (mm) Frequency (Hz) Volume (db) 1.3 520 42 0.8 440 38 0.3 590 30 0.5 780 34 2.1 700 46 So the student wants to know: what does the size of the vibration influence? Does it influence the frequency (which is the same as the note)? Does it influence the volume (which is the same as the loudness)? Or both? Make a couple of graphs to help the student sort this out. If we want to know what is influenced by the size of the vibration, then the size of the vibration should be the independent (or manipulated) variable. We have two choices for dependent (or measured) variable: frequency and volume. Graphs of each are shown below. Frequency vs. Vibration size Volume vs. Vibration Size Frequency (Hz) 900 800 700 600 500 400 300 200 100 0 0 0.5 1 1.5 2 2.5 Fibration Size (mm) Volume (db) 50 40 30 20 10 0 0 0.5 1 1.5 2 2.5 Vibration Size (mm) There may be a pattern in the graph on the left but it isn t very obvious. The graph on the right shows a very clear pattern. A larger vibration seems to produce a definitely larger volume. Most people would conclude that the graph on the right suggests a definite correlation while the one on the left does not.
IDS 101 Ocean Waves and Graphs page 5 2. According to a popular web search engine, the following is one of the most frequently viewed graphs on the Internet. It was apparently created by a humorist named Bobby Henderson who noticed (he claims) that as global warming worsened as pirate populations decreased [editor s note: global warming is a serious issue but we don t have much faith in Henderson s research]. Pretend for a moment that Henderson s data is reliable. Take a look at the graph (which looks remarkably Excel-ish) and suggest a few ways it could be improved. Arghh! tis a mess of a graph if ever I saw one, matie. Not only do the numbers on the horizontal axis fail to change in regular intervals but in one case they increase while in the others they decrease. Shiver me timbers, it isn t really clear how the horizontal axis is to be read at all. The graph is connected with a dot-todot line as though all of the data is exact and we re naught but humble pirates.
IDS 101 Ocean Waves and Graphs page 6 3. Here is another graph taken from the Internet. In the interest of protecting the privacy of the people who posted it, we aren t going to tell you anything about it. Simply comment on the graph. List some aspects of the graph that could stand improvement. How many can you find? This is rather sad. The title doesn t tell us what this graph represents. The legend gives us no information at all. The numbers on the horizontal axis don t make sense. We only know this has something to do with weight in pounds and length in inches for something that tends to be roughly three feet long.
IDS 101 Ocean Waves and Graphs page 7 According to the Australian website Census at School the following table shows real data of student heights, right foot lengths, and belly button heights (all in units of centimeters). Investigate the correlations. Is belly button height a good predictor of height? Is total height closely correlated with the length of the right foot? (And when dealing with this much data, what s the most reasonable way of dealing with the data?) Total Height (cm) Right Foot (cm) Belly Button Height (cm) 131 20 80 162 22 92 151 20 90 157 21 92 144 22 88 154 20 96 172 28 102 166 26 90 174 29 112 158 26 92 144 20 86 156 15 78 154 23 93 160 23 103 188 30 114 150 15 90 151 20 95 161 26 106 154 22 90 139 22 85 133 23 82 178 29 107 168 26 107 156 26 96 177 25 101 166 28 93 163 25 101 162 24 100 147 24 88 163 26 100 150 23 73 148 23 89 164 24 97 170 27 120 168 26 95 160 29 110 135 20 86 173 28 103 166 25 106
IDS 101 Ocean Waves and Graphs page 8 There are lots of things one can investigate here, so there are many possible solutions to this problem. What follows is just one. One might ask which is a better predictor of overall height: length of the foot or height of the belly button. Here are a couple of graphs that test those correlations: Total Height (cm) Total Height vs. Length of Foot 200 180 160 140 R 2 = 0.4717 120 100 10 15 20 25 30 35 Length of Right Foot (cm) Total Height (cm) Total Height vs. Belly Button Height 200 180 160 140 R 2 = 0.5881 120 100 60 80 100 120 140 Height of Belly Button (cm) Since a computer was used to generate the graphs, it was a fairly simple operation to get the computer to produce a trend line and even display the R value which tells us how good the correlation is. An R value of 1.00 means a perfect linear correlation while an R value of 0.00 means no correlation. As you can see, both graphs show some trend but a wide spread in the data. Thus is isn t surprising that the R values are both sort of in the middle (0.47 and 0.59) but the correlation is stronger with the height of the belly button.