# data[].attributes.body
All the information given in the five different charts have the same outcome, but they all high light different information. The most visual way to high light the peaks and gaps are by using the line graph and histogram bar graph. In these two charts we can clearly see the highest frequencies at 5, being 336-340 ounces in weight and 361-365 ounces in weight; along with the lowest frequency at zero being 331-335 ounces in weight. The outliers are best depicted in the box plot chart. Unfortunately we do not have any outlying numbers. If we did, however, they would be dots on the outside of the maximum and minimum numbers. Going back to the histogram, that is the best way to see the clusters of data information. The clusters can be found by looking and seeing where there is a break in the data. The first cluster is a small one only ranging from 325-330 ounces in weight. The second cluster is much bigger going from 336-390 ounces in weight. As you can see we have a break at 331-335 ounces in weight. To tell if the information is skewed to the right or left we could revisit the histogram and line graph. In these two charts you can clearly see that the bulk of the data is on the right side of the charts. Therefore, the weight of broccoli packed in boxed, in both charts, is skewed to the right. Our data, for the most part, is spread out. You can see this best by looking at the line graph, but you could also see that in the pie chart. Our standard deviation can be found in the excel chart. Since our number is around 16 this also back up our statement that our information is spread out evenly. All of the charts display the same information, but each of them have a distinct use and purpose.

# data[].attributes.body
As the graphs are being made some of the graphs will show the spread of the data where as one of the graphs, such as the pie chart, will not show how much the data is spread.  This chart will only show the percentage of these data points that fall within the smaller ranges.  Throughout the 36 different data entries, our group noticed that the most entered weight of the broccoli was the 359oz.  From this we can come to the conclusion that more times then none; we will find more boxes weighing 359oz.  The range of the data was one that we thought was large than we would have expected being at a 62oz. difference.  The interquartile range was slightly smaller being only 24oz.  This made more sense to us because this meant the boxes were less than a 2-pound difference.

# data[].attributes.body
We expected the broccoli to be heavier. It surprised us how much a box actually weighs. The histogram illustrated the data best because you can see the gap and you can see how the data is distributed in the histogram. The histogram illustrates the data the best compared to the other graphs because the line graph makes the data look more pointed. The pie chart doesn't display the data very well because the chart looks random and unorganized.

# data[].attributes.body
The mean of our set of data is 358.17 ounces. This tells us the average weight of a box of broccoli but does not tell us the minimum and maximum value. The mean is important to know because it a combination of all the data numbers combined into one. The median is 360 ounces and tells us the number that is in the very middle of the data set. Although the median is very similar to our mean, they represent our data set in two different ways.

The five-number summary tells us the minimum, quartile 1, median, quartile 3, and the maximum. All five of these numbers give us a good representation and range of our data set. We are able to see where the numbers fall and if there is a greater amount of numbers closer to one specific range. In this case all of data is pretty equally spread out evenly distributed. When looking at the box plot you are able to see how symmetrical our data is.

We chose this data set because we wanted to pick something no one has ever done before. We all agreed that it was a topic that was pretty much "out there" and random. It is also an interesting topic that none of us have really researched before or have thought about. Lastly we al agreed that we love broccoli.