1-5 Discussion Descriptive Statistics
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1-5 Discussion: Descriptive Statistics
Hello everyone! My name is Kaelyn Murphy, and I live in Louisville, KY. I am pursuing a degree in
Data Analytics with a concentration in Project Management. I am a mother to two amazing kiddos, and I
help my sister with her three children. My home is always full and chaotic, but I wouldn’t have it any
other way. I have three brothers and three sisters, so I am used to madness all the time. I am very
excited for this class because I haven’t ever taken a statistics class before. I work at Spectrum
Communications in the construction department but I want to move into a reporting role so I hope this
class will further help me in that endeavor.
1.
My data set for the temperatures in Louisville, KY from the past 14 days was:
1.
The descriptive statistics for my data set was:
Based on the data collected for the past 14 days, the mean of the maximum temperatures for my
city was 86.6 °F which represents the central tendency of probability of distribution along median and
mode for the temperatures. The median was 84.0°F which represents the midpoint where my data falls.
The standard deviation (calculated by taking the square root of the variance) is low at 6.8 which means
the data is clustered closely around the mean indicating the data is reliable.
2.
The graph that showed the general trend of daily maximum temperature in my city was the Line
plot of temperature data displayed below:
3.
We use measures of central tendency to show the average collection of data. The measurements
tell us where most data points collected lie. The measure of variability helps us analyze the
spread of the data points collected by showing us how they vary in relation to each other.
4.
The Boxplot for comparison graph shown below shows the difference in distribution of my data
and Zion’s data:
The median line in the box or Zion is higher than the median line my data which is an indication
of higher temperatures. The longer box plot data for Zion indicates the temperatures are more spread
out than my data.
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