How do your peers’ measures of central tendency compare to yours? Are they are lower or higher? What does this signify?
How do the measures of variability compare? What does this signify?
In what ways are their data similar to or different from your own? Why are those similarities or distinctions meaningful?
POST # 1 ?
When I gathered the 14 day high temperatures for my area they tended to remain within a 20 degree difference. The 14 day high temperatures were 78, 78, 69, 68, 73, 74, 76, 82, 75, 66, 69, 69, 70, and 70. Upon the input of these temperatures python then calculated the mean with a total of 72.64 degrees. The next calculation was the median which produced an output of 71.5 degrees. A variance of 21.79 degrees was calculated with a standard deviation of 4.67 from the data set that was provided. According to this particular data during this time of year the temperature tends to fluctuate slightly. Over a 14 day period many different variables come into play when dealing with temperatures. The minimum high temperature was 66 degrees due to a cool front coming from Canada. A maximum high temperature of 82 degrees was encountered due to a warm front from the south. From these two outputs the median was calculated by adding all the temperatures in the data set and dividing it by the 14 day period. The first quartile can then be calculated from the minimum high temperature and the median to produce an answer of 69 degrees. The third quartile can also be calculated from the median and the maximum high temperature with an outcome of 75.75. Upon finding the answers for the minimum, Q1, median, Q3, and maximum temperatures the standard deviation can then be calculated with an output of 4.67. A line plot graph was then utilized to visually display the highest temperatures for the 14 days. By using variability and central tendency analysts are able to see the changes within the data and then create possible solutions that could benefit the outcome. They can also utilize variability to determine what might occur next and take steps to divert disastrous outcomes. The box plot diagram was utilized to visualize the data sets between my location and Zion. A difference between Zion’s data set and mine is that Zion’s median temperature tends to be higher than mine. Minimum and maximum temperatures are also a larger range difference in Zion where mine tend to stay more towards the lower end of the temperature range. Zion’s temperature range display seems to have very little variability within them. Overall Zion displays less of a standard deviation in temperature than my area for the high daily temperature.
POST # 2 ?
The central, northern area of Utah tends to have valleys bordered by mountains on both east and west sides which tend to take in some of the precipitation. The result is that the weather tends to have a dry feel and the air can be stagnant due to an inversion which is a reverse of normal atmospheric conditions in that colder air is near the surface and warmer air is above it. As a result, conditions of summer tend to be hot and dry.
The temperature highs for Tooele, Utah in the past two weeks:
100, 100, 97, 99, 99, 97, 99, 95, 97, 91, 91, 93, 88, 79
The resulting statics were taken out of a 2-week period of Tooele, Utah:
count 14.000000 | mean 94.642857 | std 5.878345 | min 79.000000
25% 91.500000 | 50% 97.000000 | 75% 99.000000 | max 100.000000
The above stats share that much of the temperature was in the higher 90’s. Standard deviation is high which means that the temperature has a widespread from the 90’s dropping down into the 70’s. In the graph, the trend in temperature shows a gradual to an eventual significant decline. This is due to the records displaying the last week of summer, to a transition into fall. Central tendency is used in the weather report to display where most of the values lie which is the mean. As in the box plots below, the mean between the two cities are nearly identical at 97 degrees. The difference between these two is that Zion has a larger third quartile than Tooele, which means that most of the time the temperature sat between 107 degrees and 97 degrees. Variability in these box plots displays the range of temperature from low to high. The variability for Tooele for the past two weeks compared to Zion is low, which means that there is gradual change in the season. Tooele is displaying an outlier which means that there was a significant drop in weather from the mean. The meaning of this outlier is like the light switch effect that I experienced just recently with the weather: one day it’s hot and the next day it is cold and dark. As for Zion, the variability for the past two weeks is high due to the greater distance between 130 degrees to nearly 80, which presents a dramatic change in the seasons. Since there aren’t any outliers, this means that the change in the weather was gradual.