# data[].attributes.body
Data is an assortment of statistics collected for analysis.

# data[].attributes.body
A scatter plot is basically a line graph but they show how one variable effects the other.

# data[].attributes.body
A statistical relationship is a special type of relationship between two variables.

# data[].attributes.body
A correlation/association is a relationship between two things.

# data[].attributes.body
A positive correlation is when two variables have a statistical relationship in which both increase.

# data[].attributes.body
A negative correlation is when the y-variable increases but the x-variable decreases in a statistical relationship.

# data[].attributes.body
A strong correlation/association is a correlation/association in which the points on a scatter plot are close together and are going in an obvious direction.

# data[].attributes.body
A weak correlation/association is a correlation/association in which the points in a scatter plot are more spread out and are not going in an obvious direction.

# data[].attributes.body
When there is no correlation/association, the scatter plot does not have a negative correlation nor a positive correlation.

# data[].attributes.body
Causation is when one variable that is being compared effects the other variable in a certain way.

# data[].attributes.body
A trend line is a line on a scatter plot indicating a trend of the data

# data[].attributes.body
A line of best fit is a line on a scatter plot that best describes the data being shown.

# data[].attributes.body
A cluster is a group of similar points on a scatter plot that are generally in the same spot.

# data[].attributes.body
An outlier is a point on a scatter plot that is separated from the rest of the points showing that the point is an oddity in the data.

# data[].attributes.attachment_link.readable_text
Aubrey wanted to see if there's a connection between the time a given exam takes place and the average score of this exam. She collected data about exams from the previous year. Plot the data in a scatter plot. And let's see, they give us a couple of rows here. This is the class. Then they give us the period of the day that the class happened. And then they give us the average score on an exam. And we have to be a little careful with the study-- maybe there's some correlation depending on what subject is taught during what period. But let's just use her data, at least, just based on her data, see if-- well, definitely do what they're asking us, plot a scatter plot, and then see if there is any connection. So let's see. On the horizontal axis, we have Period. And on this investigation, this exploration she's doing, she's trying to see, well, does the period of the day somehow drive average score? So that's why Period is on the horizontal axis. And the thing that's driving is on the horizontal, the thing that's being driven is on the vertical. So let's plot each of these points. Period 1, average score 93-- right over there. Period 6, 87. Oh, that's not the right place, and then we can move it if we want-- 87, right over there. Period 2, 70. Period 4, 62-- right over there. Period 4 and 86, that's right over there. Period 1, 73. Period 3, average score of 73 as well. Period 1, 80, average score of 80. And then Period 3, average score of 96. So there we go. And it doesn't really seem like there's any obvious trend over here. So let's make sure that we got this right. And we did.

# data[].attributes.attachment_link.description
Aubrey wanted to see if there's a connection between the time a given exam takes place and the average score of this exam. She collected data about exams from the previous year. Plot the data in a scatter plot. And let's see, they give us a couple of rows here.