1280-DF-2
docx
keyboard_arrow_up
School
University of the People *
*We aren’t endorsed by this school
Course
1280
Subject
Mathematics
Date
Nov 24, 2024
Type
docx
Pages
4
Uploaded by ziadtsoubra
lOMoARcPSD|32831911
Downloaded by May Fares (mayfares@icloud.com)
Math 1280 Discussion Post Unit 2
Introduction to Statistics (University of the People)
Studocu is not sponsored or endorsed by any college or university
lOMoARcPSD|32831911
Downloaded by May Fares (mayfares@icloud.com)
Discussion Post - Unit 2
Math 1280 - Introduction to Statistics
Baythsaeda Lewis
University of the People
Travis Svensson (Instructor)
September 14-20, 2023
lOMoARcPSD|32831911
Downloaded by May Fares (mayfares@icloud.com)
An important practice is to check the validity of any data set that you analyze.
One goal is to detect typos in the data, and another would be to detect faulty
measurements. Recall that outliers are observations with values outside the
“normal” range of values of the rest of the observations.
Specify a large population that you might want to study and describe the type of
numeric measurement that you will collect (examples: a count of things, the
height of people, a score on a survey, the weight of something) for your study.
What is the best course of action statistically if you found few outliers in a
sample of size 100?
To answer the above questions:
Outline the method (s) you will use if two values twice as big as the next
highest value were identified in the sample.
You may use examples from your area of interest, such as monthly sales levels
of a product, file transfer times to different computer on a network,
characteristics of people (height, time to run the 100-meter dash, statistics
grades, etc.), trading volume on a stock exchange, or other such things.
One large population that I might want to study is the population of students in the Turks
and Caicos Islands. The type of numeric measurement that I would collect for this study
is the student's height in inches.
Best Course of Action if Few Outliers Are Found in a Sample of Size 100?
If I found a few outliers in a sample of size 100, the best course of action statistically
would be to investigate the outliers to determine if they are legitimate data points or
errors. I could do this by checking the data collection process for any mistakes, and by
looking at other variables in the data set to see if the outliers are consistent with those
variables.
If I determine that the outliers are legitimate data points, then I would need to decide how
to handle them in my analysis. One option would be to simply remove the outliers from
the data set. This is a reasonable approach if the outliers are very different from the rest of
the data and are likely to have a significant impact on the results of my analysis.
Another option would be to transform the data in such a way that the outliers are less
influential. For example, if the data is skewed, I could log-transform the data before
performing my analysis.
Finally, I could also choose to keep the outliers in the data set and to use a statistical
method that is robust to outliers. For example, I could use a median instead of a mean to
calculate the central tendency of the data.
Example: Outliers in Monthly Sales Data
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
lOMoARcPSD|32831911
Downloaded by May Fares (mayfares@icloud.com)
Suppose that I am a marketing analyst for a company that sells software. I am interested
in studying the monthly sales of our product. I collect data on the monthly sales for the
past 100 months.
When I plot the sales data, I notice that there are two outliers. The sales for two of the
months are twice as high as the sales for any other month.
I investigate the outliers and determine that they are legitimate data points. The high sales
for those two months were due to special promotions that the company ran.
I decide to keep the outliers in the data set and to use a median instead of a mean to
calculate the central tendency of the data. This is because the median is a more robust
measure of central tendency when there are outliers in the data.
Conclusion
The best course of action statistically if you find few outliers in a sample of size 100 is to
investigate the outliers to determine if they are legitimate data points or errors. If the
outliers are legitimate, then you need to decide how to handle them in your analysis. You
can remove the outliers, transform the data, or use a statistical method that is robust to
outliers.
Word Count: Three hundred and eighteen (318) words