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... SELECTION OF THE APPROPRIATE MEASURE The choice depends upon the nature of the data • If the data are symmetrically distributed, any one of these measures can be used • For skewed distributions, the AM is not suitable ( + vely skewed: AM gives a higher value – vely skewed: AM gives a lower value) • ...
The UNIVARIATE Procedure
The UNIVARIATE Procedure

... Example 2: Rounding an Analysis Variable and Identifying Extreme Values 1421 Example 3: Computing Robust Estimators 1424 Example 4: Performing a Sign Test Using Paired Data 1428 Example 5: Examining the Data Distribution and Saving Percentiles 1432 Example 6: Creating an Output Data Set with Multipl ...
Print Preview - C:\.aptcache\aea01540/tfa01540
Print Preview - C:\.aptcache\aea01540/tfa01540

... In addition, beneath the menus and dialog boxes, SPSS uses a command language. Some extended features of the system can be accessed only via command syntax. (Those features are not available in the Student Version.) Complete command syntax is documented in the SPSS 12.0 Command Syntax Reference, pro ...
Basic Analysis and Graphing
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... The correct bibliographic citation for this manual is as follows: SAS Institute Inc. 2009. JMP® 9 Basic Analysis and Graphing. Cary, NC: SAS Institute Inc. JMP® 9 Basic Analysis and Graphing, Copyright © 2010, SAS Institute Inc., Cary, NC, USA ISBN 978-1-60764-596-2 All rights reserved. Produced in ...
Basic Analysis
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... iODBC software ‐ Copyright © 1995‐2006, OpenLink Software Inc and Ke Jin  (www.iodbc.org). All rights reserved. Redistribution and use in source and binary forms, with or without modification, are  permitted provided that the following conditions are met: – Redistributions of source code must retain ...
Basic Analysis
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... iODBC software - Copyright © 1995-2006, OpenLink Software Inc and Ke Jin (www.iodbc.org). All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: ‒ Redistributions of source code must retain t ...
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... In order to get a feel for how likely it is that we could see such a difference due to chance we will simulate, using SPSS, a pair of populations where the total number of people who wanted the divorce more than their spouse is 119, and the total number who did not want the divorce more than their ...
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... Science is a process of asking questions, in most cases precise, quantitative questions that allow distinctions to be drawn between alternative explanations of events. Asking the right questions in the right way is a fundamental skill in scientific enquiry, yet in itself it receives surprisingly lit ...
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... part of the variable can be letters or digits. A name can’t end with a period, contain blanks or special characters, or be longer than 64 characters. Assigning Descriptive Labels  Variable Labels: Assign descriptive text to a variable by clicking the cell and then entering the label. For instance f ...
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... Getting Started: TTEST Procedure One-Sample t Test A one-sample t test can be used to compare a sample mean to a given value. This example, taken from Huntsberger and Billingsley (1989, p. 290), tests whether the mean length of a certain type of court case is more than 80 days by using 20 randomly c ...
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Categorical variable

In statistics, a categorical variable is a variable that can take on one of a limited, and usually fixed, number of possible values, thus assigning each individual to a particular group or ""category."" In computer science and some branches of mathematics, categorical variables are referred to as enumerations or enumerated types. Commonly (though not in this article), each of the possible values of a categorical variable is referred to as a level. The probability distribution associated with a random categorical variable is called a categorical distribution.Categorical data is the statistical data type consisting of categorical variables or of data that has been converted into that form, for example as grouped data. More specifically, categorical data may derive from either or both of observations made of qualitative data, where the observations are summarised as counts or cross tabulations, or of quantitative data, where observations might be directly observed counts of events happening or might be counts of values that occur within given intervals. Often, purely categorical data are summarised in the form of a contingency table. However, particularly when considering data analysis, it is common to use the term ""categorical data"" to apply to data sets that, while containing some categorical variables, may also contain non-categorical variables.A categorical variable that can take on exactly two values is termed a binary variable or dichotomous variable; an important special case is the Bernoulli variable. Categorical variables with more than two possible values are called polytomous variables; variables are often assumed to be polytomous unless otherwise specified. Discretization is treating continuous data as if it were categorical. Dichotomization is treating continuous data or polytomous variables as if they were binary variables. Regression analysis often treats category membership as a quantitative dummy variable.
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