Today Aiden and I discussed some of the ways we can study data. We defined mean, median, mode, inference, and upper/lower quartile. We discussed how these “measures of central tendency” can be helpful in studying data in various ways. We discussed (as an example) the total household income of every home in Palm Beach County. How the median and mean would both be helpful, but probably very different numbers. For example, if there are far more homes where there are lower incomes and very few homes with larger incomes, the mean would be a skewed representation of the true data (since the higher incomes would bring the average to a larger number than what many homes actually bring in). So we considered in this case, the median would be a more fair representation of what the household incomes represent. We considered this happens when the data is spread far apart. We looked at an example of the number of hours of sleep a student gets per night and we could see the mean and median were fairly close in quantity since the data set had values close together. We also practiced creating box plots (whisker plots) for given data sets. Aiden practiced coming up with his own data set (the number of flies on cows), he computed the mean, median, upper and lower quartile, and then created a box plot to show the data.