In your initial post, address the following items: 1. Share your data set. See Step 1 in the Python script. 2. What were your descriptive statistics for this data set? Report the mean, median, variance, and standard deviation. Based on these statistics, what can you say about the distribution of daily maximum temperature in your

MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
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Chapter1: Starting With Matlab
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For this discussion, you will collect data from a public source and calculate
descriptive statistics, including measures of central tendency and variability. You
will then interpret the results and provide feedback to your peers.
In your initial post, use the World Temperatures website (or a similar website of
your choice) to find the daily maximum temperature data rounded to the nearest
integer (whole number) in your city or zip code for the past fourteen days. You will
use this data set to calculate measures of central tendency and variability. You will
also provide a detailed analysis based on your results.
In your initial post, address the following items:
1. Share your data set. See Step 1 in the Python script.
2. What were your descriptive statistics for this data set? Report the mean,
median, variance, and standard deviation. Based on these statistics, what
can you say about the distribution of daily maximum temperature in your
city or zip code? Use all of the statistics that you calculated to explain the
distribution in detail. See Step 2 in the Python script.
3. Which graph showed the general trend of daily maximum temperature in
your city or zip code? See Step 3 in the Python script.
4. In general, how are the measures of central tendency and variability used to
analyze a data distribution?
5. The Python script also provides you with temperature data for a city called
Zion. Which graph showed the difference in the distribution of your data
and Zion's data? What can you say about the differences in data
distributions? See Step 4 in the Python script.
6. Your graphs will not show up in your html document when attached to your
discussion board post. Please embed them in your posts by right clicking on
the graph while in your Python script, select "save image as", save it and
then attach to your discussion board post using the camera icon in the
menu bar.
In your follow-up posts to other students, review your peers' data sets and
statistics and discuss the significance of these results. Here are some questions
that you should address in your follow-up posts:
1. How do your peers' measures of central tendency compare to yours? Are
they are lower or higher? What does this signify?
2. How do the measures of variability compare? What does this signify?
3. In what ways are their data similar to or different from your own? Why are
those similarities or distinctions meaningful?
Remember to attach your Python output and respond to all questions in your
initial and follow-up posts. Be sure to clearly communicate your ideas using
appropriate terminology. Finally, be sure to review the Discussion Rubric to
understand how you will be graded on this assignment.
Rubrics
Transcribed Image Text:For this discussion, you will collect data from a public source and calculate descriptive statistics, including measures of central tendency and variability. You will then interpret the results and provide feedback to your peers. In your initial post, use the World Temperatures website (or a similar website of your choice) to find the daily maximum temperature data rounded to the nearest integer (whole number) in your city or zip code for the past fourteen days. You will use this data set to calculate measures of central tendency and variability. You will also provide a detailed analysis based on your results. In your initial post, address the following items: 1. Share your data set. See Step 1 in the Python script. 2. What were your descriptive statistics for this data set? Report the mean, median, variance, and standard deviation. Based on these statistics, what can you say about the distribution of daily maximum temperature in your city or zip code? Use all of the statistics that you calculated to explain the distribution in detail. See Step 2 in the Python script. 3. Which graph showed the general trend of daily maximum temperature in your city or zip code? See Step 3 in the Python script. 4. In general, how are the measures of central tendency and variability used to analyze a data distribution? 5. The Python script also provides you with temperature data for a city called Zion. Which graph showed the difference in the distribution of your data and Zion's data? What can you say about the differences in data distributions? See Step 4 in the Python script. 6. Your graphs will not show up in your html document when attached to your discussion board post. Please embed them in your posts by right clicking on the graph while in your Python script, select "save image as", save it and then attach to your discussion board post using the camera icon in the menu bar. In your follow-up posts to other students, review your peers' data sets and statistics and discuss the significance of these results. Here are some questions that you should address in your follow-up posts: 1. How do your peers' measures of central tendency compare to yours? Are they are lower or higher? What does this signify? 2. How do the measures of variability compare? What does this signify? 3. In what ways are their data similar to or different from your own? Why are those similarities or distinctions meaningful? Remember to attach your Python output and respond to all questions in your initial and follow-up posts. Be sure to clearly communicate your ideas using appropriate terminology. Finally, be sure to review the Discussion Rubric to understand how you will be graded on this assignment. Rubrics
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