Paper details: Using the data set that you identified in week 1, use Excel to find the following descriptive statistics for the price data.
Use these summary statistics to make two conclusions or observations about the typical vehicle in the sample. One conclusion must relate to the measure of center (mean/median) and one to the variability (standard deviation) of the vehicles.
Next, add an 11th vehicle to the data set. Choose a “supercar” that costs at least $1 million. Recalculate the summary statistics to include this vehicle.
Which summary statistics were affected the most by the addition of this outlier? How were they changed, and were you surprised by the results? I encourage you to review the Week 2 descriptive statistics PDF at the bottom of the discussions. This will give you a step by step example on how to calculate these values using Excel. I DO NOT recommend doing this by hand. Let Excel do the heavy lifting for you.
Once you have posted your initial discussion, you must reply to at least two other learner’s post. Each post must be a different topic. So, you will have your initial post from one topic, your first follow-up post from a different topic, and your second follow-up post from one of the other topics. Of course, you are more than welcome to respond to more than two learners.”
Instructions: You must respond to at least 2 other students outside your initial thread. Responses may include direct questions. In your peer posts, consider the summary statistics of your classmates’ data sets. After the supercar was added to the data set, which summary statistic do you think more accurately reflects the typical vehicle price – the mean or median? Compare the standard deviation before the supercar was added and after it was added. Does this indicate greater variability in the original or modified data set? Based on this information, do you feel the standard deviation can help you identify the presence of an outlier? Why or why not? In your responses, refer to the specific data from your classmates’ posts. Make sure you incluaqwde your data set in your initial post as well.
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