market values) are 0.201 and -1.112 respectively, while the values for a normal distribution should be both zero (Table 1.1). The skewness value of 0.201 shows a slight pile-up of scores on the left of the distribution (the mean of $4.62 million is still close to the median of $4.36 million). The kurtosis value of -1.112 (a negative value) indicates the tails of the distributions are lighter than that of normal distribution. Figure 1.1 On the other hand, the values of skewness and kurtosis of
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Dave’s Crash Course in Statistics using SPSS 1.0 Classifying the different types of data There are four types of variables: nominal, ordinal, interval and ratio. Distinguishing between these types of variables is important, as several statistical tools may only be used for certain types of data. Nominal variables: where values are assigned to categories in no particular order. This assignment of values is arbitrary and holds no particular meaning or order to them. For example, “sex”
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Testing There are many tests we can run on this sample of data to determine if it is viable. First we need to turn this data into numbers that we can use in our equations to calculate our values. So we need to convert the numbers into the mean, median, mode, range of values, x, x2 and the standard deviation of the data. Second, we will use the data to construct several graphs, such as a boxplot, histogram, stem and leaf plot and a scatter plot to determine if or how the data is skewed and if there
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Rank 1 2 3 Movie Title 91 Quarantine Transporter 90 3 Seven 46 Pounds Tyler Perry's 78 The Family That Preys 76 First Sunday 99 Untraceable Nick and Norah's 92 Infinite Playlist Lakeview 73 Terrace Tyler Perry's 68 Meet the Browns 59 65 36 54 87 The House Bunny Prom Night (2008) 21 Saw V Definitely, Maybe Welcome Home Roscoe Jenkins The Strangers Death Race Made of Honor Pineapple Express Opening Gross Total Gross Theaters 14,211,321 31,691,811 12,063,452 14,851,136 31,715,062 69,951,824
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Definitions of Statistics Types of Data and Data Sources Types of Statistics Scope of Statistics Importance of Statistics in Business Limitations of statistics Summary Self-Test Questions Suggested Readings 1.1 INTRODUCTION For a layman, ‘Statistics’ means numerical information expressed in quantitative terms. This information may relate to objects, subjects, activities, phenomena, or regions of space. As a matter of fact, data have no limits as to their reference, coverage, and scope. At the macro level
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summary fashion in this report. The analysis will also include the distribution and confidence intervals for each company, along with an analysis of those findings. A hypothesis test was conducted on all three data sets in order to establish that the mean values were credible. Finally, a regression analysis was done to see if there was a relationship between each company and the S&P 500 index. All of the tables that are referenced can be located in Appendix A and all of the figures that are referenced
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for the statistician to compute by exactly how much the mean of different samples will vary. And using this it can be done without taking any other sample means to compare it with. Then by seeing how much varies, it allows the person to answer the questions that they need from the population as a whole. The entire theory of the Central Limit Theorem simply states basically says that for non-normal data, the distribution of the sample means has an approximate normal distribution, no matter what the
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Int. J. Computer Aided Engineering and Technology, Vol. 3, No. 1, 2011 19 Implementation of Six Sigma in Indian industries – a Delphi study R.K. Padhy and S. Sahu* Department of Industrial Engg. & Mgmt., Indian Institute of Technology, Kharagpur-721302, India E-mail: rkpadhy@iem.iitkgp.ernet.in E-mail: sahus@mech.iitkgp.ernet.in *Corresponding author R.K. Das Department of Mechanical Engg., College of Engg. & Technology, Bhubaneswar-751003, India E-mail: ranjitdas@gmail.com Abstract:
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93.33% | 80 | 2 | 100.00% | 80 | 2 | 100.00% | 0 | 0 | 100.00% | More | 0 | 100.00% | More | 0 | 100.00% | OUTPUT PROBLEM 2 OUTPUT PROBLEM 3 12 | | VALUE | STATISTIC | FORMULA | 56 | | 31.03333 | MEAN | =AVERAGE(B2:B31) | 15 | | 26.5 | MEDIAN | =MEDIAN(B2:B31) | 14 | | 15 | MODE | =MODE.MULT(B2:B31) | 34 | | | | | 7 | | 8 | P10 | =PERCENTILE.EXC(B2:B31,0.1) | 78 | | 15 | P37 | =PERCENTILE.EXC(B2:B31,0.37) | 23 | | 45 | P75 | =PERCENTILE.EXC(B2:B31,0.75) | 15
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we will use MySQL as the core database management system. MySQL is also freely available2 for several computer platforms. This means that you will be able to perform “serious” data mining without having to pay any money at all. Moreover, we hope to show you that this comes with no compromise in the quality of the obtained solutions. Expensive tools do not necessarily mean better tools! R together with MySQL form a pair very hard to beat as long as you are willing to spend some time learning how to
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