what is the purpose of order statistics?
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Order statistics are sample values placed in ascending order. The study of order statistics deals with the applications of these ordered values and their functions.
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['Chronological Order - follow a time pattern or demonstrate how to do something. ... ', 'Spatial Order - following a directional pattern. ( ... ', 'Causal Order - to show a cause effect relationship.']
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Statistics is a form of mathematical analysis that uses quantified models, representations and synopses for a given set of experimental data or real-life studies. Statistics studies methodologies to gather, review, analyze and draw conclusions from data. Some statistical measures include the following: Mean.
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Increasing average order value is one of the most important metrics to track for any retailer. It's how you can offset customer acquisition costs to reduce your payback period and increase ROI, which means you can accelerate your path to profitability or put more money into advertising and product development.
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Ogives are useful for determining the median, percentiles and five number summary of data. ... With an ogive we already know how many data values are above or below a certain point, so it is easy to find the middle or a quarter of the data set.
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The standard deviation measures the spread of the data about the mean value. It is useful in comparing sets of data which may have the same mean but a different range. For example, the mean of the following two is the same: 15, 15, 15, 14, 16 and 2, 7, 14, 22, 30. However, the second is clearly more spread out.
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An order set is a group of bundled standard orderables (a health care provider's instructions or directives to other health care workers regarding the treatment of a patient). These have been designed based on a condition, disease or procedure.
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Using the order initialisation parameter, you can set the table to display the data in exactly the order that you want. The order parameter is an array of arrays where the first value of the inner array is the column to order on, and the second is 'asc' (ascending ordering) or 'desc' (descending ordering) as required.
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Cumulative frequency is used to determine the number of observations that lie above (or below) a particular value in a data set. The cumulative frequency is calculated using a frequency distribution table, which can be constructed from stem and leaf plots or directly from the data.
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The goal of the inferential statistics is to draw conclusions from a sample and generalize them to the population. It determines the probability of the characteristics of the sample using probability theory.
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It involves collecting, classifying, summarizing, organizing, analyzing, and interpreting data. The main objective of Business Statistics is to make inferences about certain characteristics of a population in the business domain whether the population is people, objects, or collections of information.
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Descriptive statistics are very important because if we simply presented our raw data it would be hard to visualize what the data was showing, especially if there was a lot of it. Descriptive statistics therefore enables us to present the data in a more meaningful way, which allows simpler interpretation of the data.
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['Sample mean and sample median.', 'Sample variance and sample standard deviation.', 'Sample quantiles besides the median, e.g., quartiles and percentiles.', 'Test statistics, such as t statistics, chi-squared statistics, f statistics.', 'Order statistics, including sample maximum and minimum.']
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The distribution of a statistical data set (or a population) is a listing or function showing all the possible values (or intervals) of the data and how often they occur. When a distribution of categorical data is organized, you see the number or percentage of individuals in each group.
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Statisticians use variance to see how individual numbers relate to each other within a data set, rather than using broader mathematical techniques such as arranging numbers into quartiles. One drawback to variance is that it gives added weight to outliers, the numbers that are far from the mean.
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The type of statistical methods used for this purpose are called descriptive statistics. They include both numerical (e.g. mean, mode, variance…) and graphical tools (e.g. histogram, boxplot…) which allow to summarize a set of data and extract important information such as central tendencies and dispersion.
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['unordered list — used to group a set of related items in no particular order.', 'ordered list — used to group a set of related items in a specific order.', 'description list — used to display name/value pairs such as terms and definitions.']