Here is the data folks submitted to the Google Form in class on Friday. I sorted according to each variable so you can easily figure out mean, median and mode etc. Use this data to complete the handout you received in class on Tuesday. THEN... read below to learn how to complete this assignment on in a comment on this blog post.
NOTE: There are several "outliers" or unusual data points in our data set. According to this, one person has a foot that's only 9 cm long. Another person is only 54 cm tall. How can that be? There are no such people in our class. In psych or any type of research, our conclusions are only as good as the data we use to form them. How we deal with errors in data collection is an important issue.
I strongly suggest you write the comment in Word or another program and then copy and paste it into the comment section below. This way, if the comment doesn't go through or is accidentally deleted you'll have a record of your work. Feel free to e-mail it to me if you are afraid it didn't post. Please also remember that I have to approve all comments, so it may take a while for it to show up on the blog. You don't need to resubmit it over and over.
Click on graphs to enlarge.
Graph 1 Height v. Hair Length
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| Height vs. Hair Length Correlation Coefficient = 0.166 |
What can we see from the above scatter plot of hair length vs. height? Is there a correlation? How strong is it? If so, is it positive or negative; strong or weak?
Graph 2
Height vs. Shoe Size
Height vs. Shoe Size
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| Height Vs. Shoe Size Correlation Coefficient = 0.526 |
Above is the data we collected about our shoe sizes vs our heights. Can you see a relationship? Is there a correlation? If so, is it positive or negative? How strong is it? Does shoe size cause height to change? Does height cause shoe size to change? Why are some values so common while others are rare? Nobody in our class is only 50 cm tall. How do you think those low outlying data points happened?
Graph 3
Hair Length vs Shoe Size
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| Hair Length vs. Shoe Size Correlation Coefficient = 0.016 |
Finally, the above graph shows the relationship between shoe size and hair length. Is there a correlation? If so, is it positive or negative? How strong is it? Are the points clustered in an interesting way? Does correlation imply causation? Why or why not? Three people have shoe sizes that are less than 10 cm. How did that data happen? What would the data look like without those outliers?
And a video about ice cream and polio...
Hank on Research Methods
And... more about the Standard Deviation
While you don't need to calculate the Standard Deviation on the AP exam, this video explains how to do it. You may find it helpful to go through the math to help you understand the concept better.
12 comments:
In the scatter plot from height vs hair length we can see that most people’s hair is above 150cm. There is a small positive correlation between the height and the hair length. There are two people who seem unusual, this seems to be because of errors when entering data. If we eliminate the outliers our correlation would be even weaker. In the scatter plot between height and shoe size we can see that the taller the person the larger their shoe size, the correlation on this graph is a lot stronger positively compared to the previous graph. I believe that a person's can cause a person’s shoe size to change in various cases. A person who is a lot taller often times has bigger feet compared to a shorter person that would have smaller feet. Some values are common because they are people’s size in cm and others entered their actual shoe size. The outlying points might have occurred due to people entering incorrect data. In the hair length vs shoe size there is a very weak positive correlation. Most people have a shoe size between 20 cm and 25.cm and their hair length varies. Correlation does not imply causation because people’s shoe size has nothing to do with how long their hair is. People entered their actual shoe size instead of their shoe size in cm. Without these outliers the data would be a lot more together.
Vanessa G.
In graph number 1 we can see that it shows as height increases , so does hair length . There is a correlation but it is a weak one . The info on the graph tells me that most people in our class have their hair near 150 cm . There are a couple of outliners . If these outliners were to be removed then the correlation might rise a bit . When analyzing graph 2 there is a strong , positive correlation . Shoe side doesn't cause height to change . In the graph there are some common data points because that seems to be the average shoes size for females . The low lying data points probably happened because people were confused on measuring or put the wrong data in the wrong location .
For graph 3 there is a slight positive correlation but it's weak . It's interesting because in between 20-25 cm , shoe size seems to stay in a similar area as hair length increases . Correlation does not imply causation . This is because one variable isn't the cause for the other . Without the outliners in this graph , there probably wouldn't be a correlation .
Jessica T.
A experiment was conducted to collect data to see how can gender effect women/men hair,height and shoe size.Graph one clearly shows that the taller the individual tends to have longer hair.There is corralation between the hair and height the taller the individual wasbrhe longer their hair was. the correlation coefficient is positive and weak. In graph two it shows that data for height vs shoe size. Just like the hair vs height; individual with bigger height had a bigger shoe size as well.I believe the low outlying data came up in the data someone missed measured.The correlation is positive,weak.The final graph is hair vs shoe size.The data is inaccurate because most of the students have "extension" so there is no real proof is hair length effecting shoe size.The coefficient is negative,weak.
Juanita V.
In the scatter plot which shows the relationship between height and hair length we see that there is a correlation. It is a weak and positive correlation, however I think that there isn’t a correlation between these two relationships. There are a few outliers for example the data portrays someone in our classroom to be approximately 54 cm tall which shows that having a certain amount of hair length does not correlate with height. The scatter plot also shows us that as a whole, our classroom has individuals with similar height and hair length.
The relationship between height and shoe size shows that there is a correlation between them. It is a positive and strong correlation, shoe size doesn’t cause height to change however our height might have an impact on the size of our shoe. I see that there are individuals in our classroom that have the same shoe size, and have similar height as well. Some shoe sizes might be rarer than others due to someone being relatively shorter than the average person. I think the outliers in the data happened because there might’ve of been some errors in calculations specifically in units.
The relationship between hair length and shoe size shows that there isn’t a correlation. Someone hair length does not impact their shoe size, and vice versa. It is a positive, but weak correlation. The points are clustered in an interesting way, some of the points are scattered close together while others are far away from each other. The correlation does not imply causation because hair length does not have an affect on shoe size. Some people have a shoe size of less than 10 cm I think it was a result of miscalculating data. Without the outliers the data would probably have points clustered together.
A.L
Graph 1 shows there is a correlation between the two. But the coefficient is low and has a weak, positive correlation and the hair length vary around the height of 150 and does not increase.Their are 2 outliers and it wouldn’t change what the data is, technically it wouldn’t be apart of the data.Graph 2 is the taller you are the bigger your shoe size is, this is a positive and strong correlation . Yes sure size can cause height to change and height can cause shoe to size to change. Maybe the outlying data could’ve been done wrong and someone shoe size is really small. It’s positive and strong. Graph 3 to me it seems like there is no correlation is positive and weak . The points are cluster and correlation does not imply causation because hair length vs shoe size has no type of relationship.
Diamani.W
In the Height vs. Hair Length graph, there is no correlation. The points in the graph form somewhat like a straight line. This tells me that the height of my classmates does not affect their hair length. There are two outliers in the graph, but taking it out of the picture will alter the correlation; there will still be no correlation.
Like the first graph, there is no correlation between the height and shoe size. Neither variable causes the other to change. Some values are rare, like the points at ten and below ten (shoe size), because the students have entered the data wrongly. I feel that what they entered were their “normal” shoe sizes, and by that I mean they failed to measure their shoe sizes in centimeters. In addition, the outliers that indicated their heights are around 50 cm entered their data wrong also. Since the measuring tool used in obtaining the height was a meter stick, the students probably forgot to add the 100 cm of the first meter stick because they were already looking at the second one.
The points are much more scattered here, therefore there is still no correlation. All three graphs show no correlation, however, it doesn’t imply causation. The latter is more “cause and effect”, but correlation is simply the connection or relation. An example discussed in class is the sales of ice cream and murder cases in the summer. While the two both showed an increase, it doesn’t mean that ice cream is causing people to kill others. Moving on, I previously mentioned that the 3 points that are less than 10 in shoe size were most likely the shoe sizes that were on the shoes or their sizes as they know it, not the measurement in centimeters. Without these outliers, the data would still be scattered in different directions.
Stephany B.
In the first scatter plot-height vs. hair length-there was a weak positive correlation because the two variables move in opposite directions. I can see that short people tend to have shorter hair than tall people. There are three outliers in the data that we can remove, but the data won't give us information on short people. The graph would be an indeterminate correlation if we take out the three outliers. I think most people in the class are tall with long hair.There is one person who stands out from rest of the data because the person is a male and the rest are females.
The second graph-which is height and shoe size- has a weak positive correlation because the variable move opposite direction like the first graph. I can say that tall people tend to have bigger feet;making an exception of the three outliers because it doesn't make sense how someone's shoe size can be 8,9 or 10 cm;those who have unusual measurements might have been looking at the wrong measurement. I think shoe size doesn't change the height of a person or vice versa;according to the data it can affect it. This would be an example of how correlation doesn't imply causation.
According to the trend-line, the graph shows a weak positive correlation. The points are clustered in an interesting way because they increase and decrease. If we take out the three outliers from the data it would be an intermediate correlation. I don't think correlation implies causation because the variables are unusual and they don't make each other cause a change.
In graph number 1, it shows that as height increases , so does hair length . There is a weak correlation because there are two people whose data doesn't make sense, maybe they entered the wrong data.
Graph 2 has a strong and positive correlation. We can see that shoe size does not cause height to change . There are points in the graph that are the same because most of the class is female and it looks like half of the class has an average of 20-25 cm foot, but we can also see that the taller person has the largest shoe size. Which makes sense because a taller person needs a larger foot to balance themselves.
For graph 3 has a positive correlation but it's weak . Between 20-25 cm , shoe size seems to be the same area as hair length increases. I still believe that that shoes size doesn’t affect hair length in any way.
marelyn V
What we can infer from the graph 1 scatter plot is that students with similar height also have similar hair length.There is a correlation and it's a positive weak correlation.The information tells us that there are many people with similar height but they each don't fall under the same hair length.There isn't unusual data.Other information that would help interpret the data is knowing the percentage of females and male that participated.
In graph 2 ,I can see a relationship. The taller the person the bigger the shoe size.There is a correlation but it is a positive weak correlation.Shoe size does not cause height to change but height does cause shoe size to change. The taller you are the more you seem to grow and shoe size is one that grows as you get taller. I think those outlying data points happen because student don't pay attention and measured themselves incorrectly.
In graph 3,there seems to be a positive correlation but really weak.The points are clustered in an interesting way on the scatter plot because some students again measured incorrectly.Correlation does not imply causation because the length of a students hair isn't causing change to a students shoe size.The data might've looked a bit more understanding if students measured in cm .Some were using there actual U.S shoe size ( standard).The data might look clearer instead of having points everywhere if the outliers were taken out.
Jacqueline R.
According to the scatter plot the taller the person is the longer the hair length is in females. The scatter plot is positive but weak because the correlation coefficient is 0.166. I would say that depending on how tall the person would be, the majority would want to have short or long hair that goes with their height. There were two out of everyone else that was separated apart because of their height and length of hair. If I were to cut out the correlations then it would be strong positive.
The relationship in shoe sizes and heights is that students had about the same and it increases. The correlation of the scatter plot is positive but weak. No shoe size does not cause height to change because it’s all in genetics. Yes height does cause show size to change because it would not seem normal for a person who is short to have a big shoe size. The height and the shoe size are close in range from each other. I think that the outliers’ points happened because we only have one male in our class.
The correlation is positive but weak. The points are clustered in an interesting way because there isn’t any relationship that depending on what shoe size you have it will affect your hair length. No correlation does not imply causation because it does not cause the other. The reason that three people would have shoe sizes less than 10 cm is because of their height. It would not change the scatter plot.
Melissa.A
I can see from the scatter plot above of hair vs. height that the variables are increasing. There would be a correlation although it would be a weak one. The correlation will be positive but it will still be considered weak. The outliers in the data will be unusual but they might be there due to miss communication of the what the graph was asking. Without outliers the graph will be constantly increasing. I do not see a relationship between heigh and shoe size. The correlation will be positive and strong. The shoe size and the height of a person doesn’t connect nor have anything to do with one another both ways. The outlying data points must have happened when people miss interpret the variables on the graph or if they have a bias mind set that they have a certain believe and do mind over matter. The size of your shoe will not have to do anything with your hair length. There will be a small correlation that is a bit positive. The points in the data are interesting because there is a cluster section between 21-25 although it is empty from 11-20. The correlation does not imply causation because there is two different variables that have nothing to do with one another. The data might have happened if someone messed up the y axis and the x axis depending on the variables on the graph. the graph without outliers would be clustered to only one section of the graph. -Lisbeth D
In the first graph it shows that although there are some differences like that being the coefficient is low and the hair length varies there is a relationship between the two. Graph 2 shows a strong and positive correlation. Apparently this means the taller you are the bigger your shoe size is. The data possibly could’ve been graphed wrong or the data is inaccurate. It’s positive and strong. It seems as though there is no correlation in graph 3 but I'm not entirely certain. The points are mashed and correlation does not imply causation because hair length vs shoe size has no type of relationship.
Jordan Zamudio
(Sorry it was late)
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