Fundamental Statistics for the Behavioral Sciences
Language: English
Pages: 672
ISBN: 1285076915
Format: PDF / Kindle (mobi) / ePub
FUNDAMENTAL STATISTICS FOR THE BEHAVIORAL SCIENCES focuses on providing the context of statistics in behavioral research, while emphasizing the importance of looking at data before jumping into a test. This practical approach provides readers with an understanding of the logic behind the statistics, so they understand why and how certain methods are used--rather than simply carry out techniques by rote. Readers move beyond number crunching to discover the meaning of statistical results and appreciate how the statistical test to be employed relates to the research questions posed by an experiment. An abundance of real data and research studies provide a real-life perspective and help you understand concepts as you learn about the analysis of data. Available with InfoTrac Student Collections http://gocengage.com/infotrac.
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Would show very short paw-lick latencies and heightened sensitivity. You may think that an experiment conducted 40 years ago, which is before most of the readers of this book were born, is too old to be interesting. But a quick Internet search will reveal a great many recent studies that have derived directly from Siegel’s early work. A particularly interesting one by Mann-Jones, Ettinger, Baisden, and Baisden (2003) has shown that a drug named dextromethorphan can counteract morphine tolerance.
Additional content at any time if subsequent rights restrictions require it. x Contents 17.5 17.6 17.7 17.8 Measures of Association and Effect Size 453 Reporting the Results 456 Unequal Sample Sizes 457 Masculine Overcompensation Thesis: It’s a Male Thing 458 17.9 Using SPSS for Factorial Analysis of Variance 461 17.10 Seeing Statistics 462 17.11 Summary 463 17.12 A Quick Review 464 17.13 Exercises 465 Chapter 18 Repeated-Measures Analysis of Variance 470 Chapter 20 Nonparametric and.
Calculating the ingredients of a boxplot is more complicated than it really needs to be, and in recent years most people have adopted a somewhat simpler approach that produces nearly the same plot with more easily understood steps. That is the approach that I will adopt in this edition. DefInITIon Boxplot: A graphical representation of the dispersion of a sample. Box-and-whisker plot: A graphical representation of the dispersion of a sample. The data and the accompanying stem-and-leaf display in.
Percentage of individuals in one of several categories just by adding the percentages for each category. The same thing holds in terms of areas, in the sense that we can find the percentage of incarcerated individuals by adding the areas devoted to prison and to jail. And finally, if we can find percentages by adding areas, we can also find probabilities by adding areas. Thus the probability of being incarcerated is the probability of being in one of the two segments associated with.
Computing these standard scores is called standardization. Every day, people use other transformational scoring systems with particular properties without realizing what they are. DefInItIon Standard scores: Scores with a mean of 0 and a standard deviation of 1. Standardization: The process of computing standard scores. Percentile: The point below which a specified percentage of the observations fall. A good example of such a scoring system is the common IQ. Raw scores from an IQ test are.