In July 2015‚ there was a study conducted by Jamie Kwon on the correlation between final high school grade point averages and standardized test scored scores titled "The Correlation Between Standardized Test Scores of Entering [College] Freshman and Their Final [College] Grade Point Average Upon [College] Graduation." In the report made on the study‚ there are two scatter plots that show correlations between high school GPA‚ college GPA‚ and ACT scores. The first shows the correlation between both
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existing adaptive methods and constant parameter methods when the estimation and evaluation samples both contain a level shift or both contain an outlier. An empirical study‚ using the monthly time series from the M3Competition‚ gave encouraging results for the new approach. Keywords: Adaptive exponential smoothing; Smooth transition; Level shifts; Outliers INTRODUCTION Exponential smoothing is a simple and pragmatic approach to forecasting‚ whereby the forecast is constructed from an exponentially
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variance‚ range‚ and standard deviation. Moreover‚ the outliers movies were identified by calculating the z-score of each variable. Finally‚ it was measured the association between two variables (correlation coefficient) to understand the relationship between more than one variable. Four variables were examined‚ and the results are described as follows: a. Opening Weekend Gross Sales (OWGS): From the sample data analyzed for OWGS‚ three outlier movies were identified: War of the World‚ Harry Potter
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conventional= 5631695 + 4.74 wind. There was 23 cases used and 28 cases contain missing values and we got a p value of .183. We achieved a r-squared of 8.3% which is far too low‚ so we knew that we had to take out outliers in order to get a high R-squared. Washington was a large outlier because they have a large number of hydroelectric plants‚ so we took Washington out of our data. This gave us a regression equation of hydroelectric conventional = 2996890 + 4.41wind. There were 22 cases used now
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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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