Data into Information Four kinds of useful information about a set of data: center‚ variability‚ shape and outlier Types of center: mean‚ median and mode (and their definitions) Types of variability: range‚ standard deviation and IQR (and their definitions) Types of shape: symmetric‚ skew to the left‚ skew to the right‚ unimodal and bimodal (and their definitions) Definition of outlier (unusual values): Section 7.2 Picturing Data Stem-and-leaf plot and how to make a stem-and-leaf plot Step
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you can see that Dick’s salary is an outlier compared to the mean. b) The median of these seven salaries is $23‚500. I got the median by first putting the numbers in order. Since it is an odd amount of numbers‚ I just find the center of the data after they were in order. This value does not really compare to all of the individual salaries; it has no relation other then it is just in the center. Dick’s salary does not compare to the median because it is the outlier‚ but mostly everyone else’s does because
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are three mild outliers in Eagle boy’s data‚ so we have run Box –Plot on data including mild outliers and excluding mild outliers. Fig 1.1 (With Mild Outliers) Fig 1.2 (Excluding Mild Outliers) Fig 1.2 (Excluding Mild Outliers) Result and Conclusion: After analysing the data with Box Whisper plot of comparison‚ it is found that an average diameter of eagle boys large pizza is 29.174 cm and of dominos large pizza is 27.442 (including Outliers). There are three outliers in Eagle boys’
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What Makes Success------ Nature or Nurture? --a book review on Outliers George Eliot has said: “it is never too late to be what one might have been.” Indeed‚ what makes success? People have been questioning for more than a century. Is it by nature or by nurture? In Malcolm Gladwell’s newest book Outliers which narrates the story of success‚ we can see the answer. Is it hard to being a successful person surrounded with glory and applause? Is it hard to being a successful
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possible that some of the data gathered can be considered invalid. These outliers are usually the highest or the lowest value in a set of data which differ significantly from the other observations. In presence of which‚ some statistics‚ like the mean‚ are greatly affected especially if there is a small number of observations. Hence‚ for this experiment to have accurate and precise conclusions‚ a test for detecting outliers must first be performed before proceeding with the analysis. The Dixon’s
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first good we are going to talk about is coke. The data shows that the prices within our sample are usually between one and two Euros. However‚ there are small fluctuations between the prices and there is one extremely high outlier that goes up to 211.93€. This extraordinary outlier is from Qatar. It is possible that the price is that high because the group forgot to type in decimals‚ leading to these extreme price. During our research we found out that Qatar is relatively
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English 101 15 April 2014 Finding Forrester and Outliers My views on the book were that it was inspiring and show the realistic views on life. The Outliers is set of stories that shows the errors in human nature‚ however‚ it also shows the paths of those who overcame the obstacles on the way to success. Outliers is a book that reveals how the most powerful people‚ those that have become idols when talking about success‚ had the greatest luck and opportunities already around them. When Bill
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higher power‚ success is more obtainable due to the respect you will receive if you are associated with someone already well respected. In the play‚ The Crucible‚ and in the Civil Rights movement‚ Abigail and Dr. King are outliers in their fight for what they want. By being outliers‚ they will not get the respect from the public they are looking for right away. To gain respect‚ one must be associated with a person with more respect to hopefully been seen at the same status as them. Abigail positioned
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"Definition of Calories in Food." LIVESTRONG.COM. Livestrong‚ Oct.-Nov. 2013. Web. 09 Dec. 2013. r=(721550-50(6.46)(2194))/√(2297-50(〖6.46)〗^2 √(256925000-50〖(2194)〗^2 )) r=12888/(√210.42 √16243200) r=12888/(14.50586088×4030.28535) Testing for Outliers: 〖Upper Boundary〗_Calories=2650+1.5(1200) 〖Upper Boundary〗_Calories=4450 〖Lower Boundary〗_Calories=1450-1.5(1200) 〖Lower Boundary〗_Calories=-350
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drag the trend line and if there are outliers. I have found one possible outlier (in red). I need to run a multiple regression with and without the possible outlier. If there is an important change in the output‚ I can consider to deleting the outlier but it is always important to think about some reasons why I need to delete the outlier. Regression MSHARE = 4.0303 - 7.5977 * PDUB + 2.6223 * PMAY + 3.4727 * PBPREG + 1.0249 * PBPALL Without the outlier MSHARE = 4.2352 - 6.9540 * PDUB + 2
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