By Serge Lee, Maria Cesaltina da Silveira Nunes Dinis, Lois Lowe, Kelly Anders
Statistics for foreign Social paintings And different Behavioral Sciences provides information utilizing common, available language, making it more straightforward for college students of all backgrounds -- rather social paintings scholar undergraduates, graduates and practitioners -- to profit and observe statistical techniques, instruments, and tactics. The ebook accommodates robust statistical software program courses, Statistical package deal for the Social Sciences (SPSS) and Microsoft Excel ToolPak, into statistical computations. The path contents were geared up pedagogically in an order that enables scholars to view the development of innovations and hand calculations along side automatic statistical research instruments. moreover, this article is exclusive in that it comprises appendices particularly designed to supply directions on getting ready information for facts access, build variable names, and information analysis-using SPSS; current directions to nonparametric records and submit hoc comparisons; and concentrate on Microsoft Excel ToolPak, that's to be had in so much in my opinion owned pcs and hand held units comparable to pills and clever telephones. The e-book additionally contains strong teacher and pupil fabrics through a significant other website.
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Extra resources for Statistics for international social work and other behavioral sciences
NOMINAL VARIABLE (NOMINAL DATA) The nominal-level variable (commonly known as nominal data) is the simplest measurement. A nominal variable classifies the values of the variable into discrete and separate categories based on some defined characteristic or “names” the variable. These are essentially name tags of each value of the variable. The categories are not numerically rank ordered. In some situations, categories can be divided into subcategories. For example, to make a nominal measurement of ethnic background among students, classification as members of various racial groups may be helpful, followed by counting the number of students in each racial category.
Common measures of variation are the range, quartile or interquartile range, mean deviation, variance, and standard deviation. THE RANGE The range is the simplest measure of variation. It is simply a measure of the difference between the highest and the lowest values in the distribution, and it is calculated as follows: Range = Maximum value (score) − minimum value (score) Suppose that 10 employees are randomly selected from a community-based agency and their ages recorded as 23, 24, 20, 24, 21, 26, 28, 27, 25, and 28 (10 values).
To create better measuring instruments, the following four levels of measurement must be taken into consideration: nominal, ordinal, interval, and ratio. Terms such as nominal data, nominal level of measurement, and nominal variable are used interchangeably throughout this book. NOMINAL VARIABLE (NOMINAL DATA) The nominal-level variable (commonly known as nominal data) is the simplest measurement. A nominal variable classifies the values of the variable into discrete and separate categories based on some defined characteristic or “names” the variable.