...Outliers: The Story of Success Analysis Latasha D. McCullar Managerial Leadership MNGT 5670 Dr. Rebecca Elliott October 16, 2013 Abstract Genius is over-rated. Success is not just about innate ability. It’s combined with a number of key factors such as opportunity, meaningful hard work (10,000 hours to gain mastery), and your cultural legacy. Random factors of chance, such as when and where you were born can influence the opportunities you have. Malcom Gladwell , the author of Outliners: The Story of Success, brings alive his assertions and thesis primarily through the use of individual success stories of athletes, computer genius, musicians, artist and community cultures. Introduction Gladwell uses a straight-forward, easy-to-digest style of mixing facts with examples and anecdotes in making his point that it is not shear genius or hard work alone that results in success. Instead, the he dives deep into the story behind exceptional performance in cultures, aptitude testing trends and individual achievements around the world. Gladwell argues that the upbringing of individuals greatly impacts their likelihood to succeed, including birth dates, access to specialized resources, parenting, and community culture. Discussion Gladwell separates the book into chapters highlighting the circumstances that resulted in the creation of each "outlier" he chooses to emphasize. According to Gladwell, the vast majority of hockey stars are born in the months of...
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...trip participants included an aspiring woman who planned to major in biology, so she was put in charge of analyzing the water samples. My friend’s missionary group spent several weeks digging wells around the village that produced clean water, but they weren’t sure that the villagers were going to drink the water. At my friend’s request and because I had recently taken a math class, along with planning my own mission trip, I was asked to analyze their data to ensure the quality of the villager’s water that was from wells, and this is the results of my analyzation. In analyzing the data on the use of the mean or median as a better measure of central tendency, the data itself reveals that there are variables or outliners on the 2nd and 3rd columns of the data. These outliners have skewed the data to where the statistical data doesn’t represent the true mean value of the data that is presented. If this view tries to give way to the true meaning of the mean, then that would give rise to the disproportionate number increase on one side that would represent a very real uptick in the numbers that are being skewed. That is what the numbers seem to be doing as it relates to the 2nd and 3rd columns of the data, as they progressively jump upward “However, as the data becomes skewed the mean loses its ability to provide the best central location for the data because the skewed data is dragging it away from the typical value. However, the median best retains this position and is not as strongly...
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...DISPERSION * (also called variability, scatter, or spread) denotes how stretched or squeezed * Contrasted with location or central tendency and together they are the most used properties of distributions. * A quantifiable variation of measurements of differing members of a population. Common examples of measures of statistical dispersion: * variance * standard deviation * interquartile range Measures of statistical dispersion * A measure of statistical dispersion is a nonnegative real number that is zero if all the data are the same and increases as the data become more diverse. If the measurements are in metres or seconds, so is the measure of dispersion. Such measures of dispersion include: * Standard deviation * Interquartile range * Range * Mean difference * Median absolute deviation * Average deviation * Distance standard deviation Range * Is the simple measure of dispersion, which is defined as the difference between the largest value and the smallest value. Mathematically, the absolute and the relative measure of range can be written as the following: R=L – S Where R= Range. L= largest value, S= smallest value Quartile deviation * This is a measure of dispersion. In this method, the difference between the upper quartile and lower quartile is taken is called the interquartile range. Symbolically it is as follows: Mean deviation * Mean deviation is a measure of dispersion, which is known as...
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...2. One of the most popular TV Shows in America, Wheel of Fortune, has been around for a while, but it is still a very popular show. What is unique about this show is the fact that letters play a bigger role than anything else. In the bonus round of the show, contestants are automatically given the letters R, S, T, L, N, E because back when the show was started, early contestants mostly chose those letters. This is case with my data as well. As you can see on the data table, the most common letters from the article are R, S, T, L, N and E. Today, the contestants are given additional 3 consonants and an additional vowel. If I was a contestant in the show, I would choose G, H, M as my consonants since they are the mostly used consonants after R, S, T, L, N and E in my data. Letter | Frequency | Relative Frequency | A | 122 | 8.5% | B | 23 | 1.6% | C | 51 | 3.6% | D | 46 | 3.2% | E | 193 | 13.4% | F | 24 | 1.7% | G | 57 | 4.0% | H | 65 | 4.5% | I | 129 | 9.0% | J | 4 | 0.3% | K | 17 | 1.2% | L | 61 | 4.2% | M | 32 | 2.2% | N | 126 | 8.8% | O | 11 | 0.8% | P | 26 | 1.8% | Q | 2 | 0.1% | R | 87 | 6.1% | S | 113 | 7.9% | T | 133 | 9.3% | U | 41 | 2.9% | V | 15 | 1.0% | W | 25 | 1.7% | X | 2 | 0.1% | Y | 31 | 2.2% | Z | 0 | 0.0% | 3. Looking at the stem-and-leaf plot, it is obvious there is a big difference between some of the letters. The percentage of relative frequency for the letters ranges from 0% to 13.4% meaning that while...
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...Google SketchUp THE MISSING MANUAL The book that should have been in the box® Google SketchUp THE MISSING MANUAL ® Chris Grover Beijing • Cambridge • Farnham • Köln • Sebastopol • Taipei • Tokyo Google SketchUp: The Missing Manual by Chris Grover Copyright © 2009 O’Reilly Media, Inc. All rights reserved. Printed in the United States of America. Published by O’Reilly Media, Inc., 1005 Gravenstein Highway North, Sebastopol, CA 95472. O’Reilly books may be purchased for educational, business, or sales promotional use. Online editions are also available for most titles (safari.oreilly.com). For more information, contact our corporate/institutional sales department: (800) 998-9938 or corporate@oreilly.com. Printing History: May 2009: First Edition. Nutshell Handbook, the Nutshell Handbook logo, the O’Reilly logo, and “The book that should have been in the box” are registered trademarks of O’Reilly Media, Inc. Google SketchUp: The Missing Manual, The Missing Manual logo, Pogue Press, and the Pogue Press logo are trademarks of O’Reilly Media, Inc. Many of the designations used by manufacturers and sellers to distinguish their products are claimed as trademarks. Where those designations appear in this book, and O’Reilly Media, Inc. was aware of a trademark claim, the designations have been printed in caps or initial caps. While every precaution has been taken in the preparation of this book, the publisher and author assume no responsibility for errors or omissions...
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...Chapter Seven Problem 1) Look at the scatterplot below. Does it demonstrate a positive or negative correlation? Why? Are there any outliers? What are they? [pic] The scatterplot is an example of a positive correlation, the outlier in the scatterplot is 6.00. A ; “Outliners are a set of data, a value so far removed from other values in the distribution that its presence cannot be attributed to the random combination of chance causes” (http://www.statcan.gc.ca/,2013)scatterplot is considered positive when the point runs from the lower left to the upper right such as the circles shown on the example. Problem 2) Look at the scatterplot below. Does it demonstrate a positive or negative correlation? Why? Are there any outliers? What are they? [pic] The scatter plot is the opposite of example one, it is actually a negative correlation because the points run from the upper left to the lower right. As with example one there is an outer liner which is 6.00 as well, it does not fall within line with the other points. Problem 3) The following data come from your book, problem 26 on page 298. Here is the data: Mean daily calories Infant Mortality Rate (per 1,000 births) 1523 154 3495 6 1941 114 2678 24 1610 107 3443 6 1640 153 3362 7 3429 44 2671 7 For the above data construct a scatterplot using SPSS or Excel (Follow instructions on page 324 of your textbook)...
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...Buying a vehicle can be stressful time for anyone, whether you a veteran or a first time buyer. For this consideration, I have decided to utilize a data set from Elementary Statistics written by Mario F. Triola. Cars, which can be found in the Appendix section under Data Sets on page 784. By utilizing this data, I can decide from a list of 32 cars, which one would be the best for a person who want powers, efficiently or environment friendly. At the same time comparing data against itself and seeing if there any outliner or any infrequent in the data set. In addition to the text book I also will be using a program call Statdisk. STATDISK is a software program designed specifically for use with textbooks in the Triola Statistics Series. Using a full featured statistical analysis package, it includes over 70 functions and tests, dozens of built-in datasets, and graphing. To get a better understand of the 32 cars themselves I have construct a chat from statdisk. In figure 1.1 we can see the data which was taken from data set in Appendix B from Elementary Statistics. As we look closer at the chart we can see that there are nine categorizes, one of them being the make/model of the 32 cars that we will be deciding on. Each category has a unit for it set of data. As we look at the first one we can see that weight is in pound, length is in inches and displacement is in litters. Cylinders is determine on how many pistons or cylinders are in the engine. The City and ...
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...LaShantel Wilson Strayer University Dr. Richard Brown April 18th 2016 Error handling are routines in a program that responds to errors (Encyclopedia). The measurement of quality in error handling is based on how the system informs the user of such conditions and what alternatives it provides for dealing with them (Encyclopedia). This paper will give a narrative which describes the changes and added error handling pathways in the diagram within this paper. There will be an overview of the errors, an explanation as of the main changes checking are imperative within the process, and overview of possible errors. A diagram will illustrate the updates of two (2) error handling pathways. Error Handling Pathway Ridgeline Mountain Outliners (RMO) is a large retail company that specialize in clothing and related accessories for all types of outdoor and sporting activities (BOOK). One approach to handling errors in received data is for the receiving system to send the data back to the sending system, often with an indication that an error has been detected by the receiving system (GOOGLE). When an enterprise IT system includes a sales system and a financial system, the sales system may send data to the financial system, which is only capable of accepting data that passes particular types of validity checks and other types of data consistency checks. When data received by the financial system does not pass the data consistency checks, an error occurs in the financial system and...
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...Tyldum initially sets up his setting by way of a voiceover of Alan Turing in an interrogation room, this creates a sense of calmness but ultimately apprehension. This is a juxtaposition to Sully, as Eastwood establishes his setting in the sky in a plane with twin engine loss, battling towards an unknown city; instilling suspense and shock to the viewer, with flashbacks between the actions of the main protagonists. Personified descriptions in Tyldum's The Imitation Game, attributes human characteristics to Turing's ‘Christopher,' the first computer Alan constructs. This computer is named after his very close friend in boarding school, who had tragically died. This allows the viewers to sympathise with Turing's situation of being an outliner in society as he is lonely, striving to keep his integrity in a world that only wants his code cracking ability. Sully strives to prove the NTSB investigations wrong as he defends his professional judgement, explaining why he couldn’t land the plane, and wasn’t purposely endangering the lives;...
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...Oppurtunity is a set of circumstances that makes it possible to do something. In the Outliners Chapter two “ The 10,000 Hour Rule” is all about oppurtunities that have led some of the most iconic people in history to success. They say to truly master your craft you must have 10,000 hours of practice under your belt. Which made me think, do you really need 10,000 hours of practice to be great? Or can you be purely be talented at something without having the 10,000 hours of practice? How Gladwell explains this method is that first all the children start off in the same playing field. Overtime you are able to distingush who is talented , who is good and who is just getting by. The way you are able to tell is that the most talented have the time to practice which increases is over time. They’re able to reach the 10,000 hours rule of mastery because they have one people around them that support them and want them to be great. Two their parents are most likely able to afford to put them in extra tutoring, are extra music classes etc. So they don’t have to work to support themseleves, they have time to practice. As opposed to the child who is good and the the other that is...
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...What are the purposes of data display? 1- Present an easy to read summary of the data 2- allows you to see and point out important features in the data What is the relation between data displays and data analysis? Data display precede (come before) data analysis in order to check conditions needed for data analysis and to help in guiding the right analysis Terminology Word | Meaning/examples | Variable | Any characterestistics of interest and it varies from on individual to another | Quantitative variable | Numbers/ special case (time in time series data) Ex: 68,14,512,642, | Categorical variable | Gender, opinion, Yes/no, M/F, (places data into groups or categories) | Distribution (the whole graph) | List of all possible values of variable and how often they occur | Compare between categorical variable and quantitative variable Type | Categorical | Quantitative | Examples | Opinion, region, gender | Unemployment rates, stock price, length of time for phone service | Types of display | Pie chart, bar graphs | Histogram | What is the difference between pie chart and bar graph? Pie charts: show percent (relative frequency) and sum to 100% bar groups: shoe counts (frequency) or percentage (relative frequency) in each category What is the difference between Histogram and bar chart? Similar to bar chart except it uses number line and the bars are connected to other Exercise: if there were 10 male and 14 females in a class, what is the variable & type...
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...Euy Hyun Chong N9718605 Euy Hyun Chong N9718605 Numerical descriptive measures Take Home Assignment - Topic 2 Numerical descriptive measures Take Home Assignment - Topic 2 Question 1: Data Set | | | | | | | | | 11 | 12 | 14 | 15 | 16 | 18 | 24 | 25 | 28 | 32 | Min | Quartile 1 | | Median | | Quartile 3 | Max | Table [ 1 ]. Ages of 10 randomly selected students in a Judo school in Brisbane. (a) Mean (x) : 19.5 Standard Deviation (S) : 7.24568 (b) Median: 16+182=17 When comparing the mean and the median it tells the distribution is skewed to the right, which is positively skewed. The skewness of the dataset is positive due to bigger mean value than the median, as mean pulls the dataset to the right. (c) Coefficient of Variation: CV= Sx= 7.2519.5=0.37157 (d) Using Excel: * First Quartile (Q1) = 13.5 [=QUARTILE.EXC(array,quart)] * Third Quartile (Q3) = 25.75 [=QUARTILE.EXC(array,quart)] * 80th Percentile = 27.4 [=PERCENTILE.EXC(array,k)] Working out by common sense: * First Quartile (Q1) = 12+142=13 * Third Quartile (Q3) = 25+282=26.5 * 80th Percentile = Lp=n+1×P100=10+1×80100=8.8 ≈9th value * Therefore, the approximate of 80th percentile is 28 (9th value in data set). (e) Range: highest value – lowest value = 32 – 11 = 21 IQR: Q3-Q1=12.25 (Used excel values) (f) Data...
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...data and then drawing conclusion based on them. * Population – is the complete collection of all measurements or data that are being considered. * Census – is the collection of data from every member of the population. * Sample – is a sub-collection of members selected from a population Statistics Cheat Sheet Chapter 2 – Summarizing and Graphing Data Section 2-1: Review and Preview * Characteristics of Data * 1. Center: A representative value that indicates where the middle of the data set is located. * 2. Variation: A measure of the amount that the data values very. * 3. Distribution: The nature or shape of the spread of the data over the range of values (such as bell-shaped). * 4. Outliners: Sample values that lie very far away from the vast majority of the other sample values. * 5. Time: Any change in the characteristics of the data over time. * Study Hint: Blind memorization is not effective in remembering information. To remember the above characteristics of data, it may be helpful to use a memory device (or mnemonic) for the first five letters CVDOT. Remembering the sentence “Computer Viruses Destroy Or Terminate” is an easy way to help us remember the five key characteristics of data. Chapter 3 Statistics for Describing, Exploring, and Comparing Data 3-1 Review and Preview * Critical Thinking and Interpretation: Beyond Formulas * The methods and tools presented in...
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...Review for Exam 1 Chapters 1-4 Chapter 1 |1. |An information system can be defined as: | |A) |An organized combination of people, hardware, software, communications networks, and database resources. | |B) |As a system that collects, transforms, and disseminates information in an organization. | |C) |Is composed of hardware, software, networks, and data resources. | |D) |All of the above would apply to the definition of an information system. | | |Ans: D | |2. |In the internetworked E-business enterprise, an extranet refers to: | |A) |A network inside the enterprise. | |B) |A network between an enterprise and its trading partners. | |C) |A local area network within the enterprise. | |D) |A wide area network within the enterprise. ...
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...MY INTRODUCTION Intellectual Inquiry & Critical Thinking Professor Philpot PERSONAL: 1. Your first name (as you preferred to be called): Beau 2. Nicknames: None 3. Place of birth? Waterbury, CT Places lived? : Bethany Presently living on campus or commuting from where? : Living in Wilkinson 4. What courses are you taking this semester? : Microbiology, Algebra, Inquiry, American History, and Anthropology Critical issues. 5. What jobs or volunteer experiences have you had? : 6. Will you have family responsibilities this term? Nope 7. Will you be working or volunteering this semester? If so, how many hours? On campus or off? Working at an ice cream place called Billy’s. 8. Has anyone in your immediate family (parents or siblings) graduated from college? No but both my parents attended Southern. FUTURE PLANS: 1. Intended major? How sure are you about this choice? What lead you to this choice? I’m a Nursing major, I thought it would be a good choice to help people and get a high paying job. 2. What plans do you have for after graduating college (definite or tentative)? Tentative, I am very unsure what I want to do after college. 3. What is your intended career? How sure are you about this choice? What lead you to this choice? A full time nursing career is what I’m striving for. Although I am very unsure about this choice. PERSONAL ABILITIES, ACHIEVEMENTS & DISTINCTIVE QUALITIES: 1. What are you really good at? My strong suit is history...
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