# data[].attributes.body
The data could represent the number of students who attended 4 different after school clubs. Each column could be a different clubs attendance for the week. The rows would be week 1, week 2, and week 3. Students could determine which club grew the most over 3 weeks.

# data[].attributes.body
This data could represent the number of Girl Scout cookies sold by three different troops in this area (rows). These numbers could be divided into four different age groups  (columns). These numbers could be the figures for each group after one week of selling.  These numbers can be totaled together for a total sum. They can also be used to find the mean, median, and mode. Students can also use these numbers to find the averages sold by each age group and by each troop.

# data[].attributes.body
Looking at the table of numbers I would interpret it by column 1 (2, 5, 7) the days and columns 2-4 (22, 17, 28, 6,4,8,10,2, and 6) as the types and amount of trees sold. So the days are the days of a week and the other numbers are the amount sold. So in week 1 day 2  there were 22 big trees sold, 6 medium trees, and 10 small trees. In week 1 day 5 there were 17 big trees sold, 4 medium trees, and 2 small trees. In week 1 day 7 there were 28 big trees sold, 8 medium trees, and 6 small trees sold.

# data[].attributes.body
The data that is given could represent sports team during each season of the year (summer, fall, winter, and spring) and the number of teams that are made depending on school level (elementary, middle, and high) The first row would represent elementary, the second row would represent middle school, and the third row is high school. Each column would represent a season of the year. And the number represents the number of team that a certain school level had during a season of the year. For example, For middle school (the middle row) in the fall (the second column) would have a number of 17 teams.

# data[].attributes.body
The data given could represent rainfall in the matter of 3 years. The columns could represent quarters of the year and the rows would represent 3 years. It shows the difference of rain each year in the spring, summer, autumn, and winter. For example in year two it rained 3 more times than in year one in Spring. You can also determine the average of rainfall for each. For example year one would average out to be 10.

# data[].attributes.body
The data given could be represented as possibly a way of seeing the number of people that attended a restaurant during it's opening week. The first row: 2,5,7 could represent the night it is during the first week and each row after that could represent breakfast lunch and dinner. So, on day number 2, there were 22 for breakfast, 6 for lunch, and 10 for dinner. Day 5 there were 17 for breakfast, 4 for lunch, and 2 for dinner. Day 7 there were 28 for breakfast, 8 for lunch, and 6 for dinner. We could use this to data to see that breakfast is the most popular meal that they served throughout the first week. Students could use this data to find the average for each meal of the day and which one is the most popular meal that the new restaurant serves.

# data[].attributes.body
This data could represent the average temperatures during Winter months in different cities. For example, the rows would be labeled December, January, and February. The columns would represent 4 different cities in the U.S.  Students could find the mean, median, and mode of the data. They could also separate the data into a stem-and-leaf plot or practice graphing data on a plane.

# data[].attributes.body
This table can be used to find the average snowfall (in inches) in four cities in three years. Each column would be labeled "city A, city B, city C, city D," and each row would be labeled "Year 1, Year 2, Year 3." Each number is the number of inches of snow for that year in that city. For example, City A had 2 inches of snow in Year 1.
City A's average snowfall would be 4.7 inches
City B= 22.3 inches
City C= 6 inches
City D= 6 inches

# data[].attributes.body
I interpreted this data as making these numbers into a stem and leaf plot.

0- 2,2,4,5,6,6,7,8

1- 0,7

2-2,8

I think this is the perfect representation to find the mean, range, and median. I think you could interpret it as there are a total of 12 clubs at the local high school. Each club is listed in the data set. Each number that is listed shows how many people are in each club. The principal is wanting to know what the average number of students in each club, how many people total from the school are in the club.

# data[].attributes.body
Consider the following data set.  Notice there are no labels.  Instead, each of you has the opportunity to determine how you interpret the data.  Explain your interpretation of the data.