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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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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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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"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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STA 600 ASSIGNMENT 2 CHAPTER 3: DIAGNOSTICS AND REMEDIAL MEASURES Diagnostic For Predicted Variable Probems can occur when: * Outliers exist among X levels * X levels are associated with run order when experiment is run sequentially Useful plots of X levels: * Dot plot for discrete data * Histogram /stem-and-leaf plot * Box plot * Sequence plot (versus time order) Departures From Model To Be Studied By Residual 1. The regression function is not
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Patel & Bruce © Galit Shmueli and Peter Bruce 2010 Data Visualization • “A picture is worth a thousand words” • Data visualization and summary statistics help condense data • Effective presentation • Supports data cleaning (identify missing values‚ outliers‚ incorrect values‚ duplicates) and exploring (combine some groups) • Helps identify suitable variables • Mandatory initial step for most data mining applications Graphs for Data Exploration Basic Plots Line Graphs Bar Charts Scatterplots Distribution
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the analysis of the motion picture industry data first presented in Chapter 2. Developing and interpreting descriptive statistics such as the mean‚ median‚ standard deviation and range are emphasized. Five-number summaries and the identification of outliers are also of interest. Interpretations and insights can vary. We illustrate some below. Descriptive Statistics Variable N Mean SE Mean StDev Range Opening Gross 100 9.38 1.89 18.87 108.43 Total
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Hypothesis: Female unemployment in the North West is greater than female unemployment in the South East. To test my hypothesis I am going to compare 40 values of data from each region. I will collect my data by using a random sample. I am going to use a random sample because this method of sample gives each separate value an equal chance of being used and it is also completely unbiased. I will assign a number from 1 to 80( because there is a total of 80 pieces of data) to every piece of data. I
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huge problem in all of our categories. We did find out that was a severe multicollinearity that occurred between SG&A and the operating income. Because of this we determined that the five variable model would not work for our regression. Outliers: When one is comparing a variety of companies it is discovered that there is a difference in size from one company to another‚ even
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