Introduction to Nonparametric Statistics for the Biological Sciences Using R, 2016, p.299-326
2016
Details
- Autor(en) / Beteiligte
- Titel
- Other Nonparametric Tests for the Biological Sciences
- Ist Teil von
- Introduction to Nonparametric Statistics for the Biological Sciences Using R, 2016, p.299-326
- Ort / Verlag
- Switzerland: Springer International Publishing AG
- Erscheinungsjahr
- 2016
- Link zum Volltext
- Quelle
- Alma/SFX Local Collection
- Beschreibungen/Notizen
- The purpose of this lesson is to highlight a few other nonparametric tests that may be of interest to those who work in the biological sciences. These additional nonparametric tests range in complexity and use. The Binomial Test can be fairly simple in structure and application. Other nonparametric tests, such as Binomial Logistic Regression, can become quite complex both in the way data are organized and in the way results are interpreted. This lesson ends with the reminder that nonparamteric tests are by no means less desirable than tests associated with parametric analyses. Quite the opposite, nonparametric tests have a valuable role in the use, analysis, and interpretation of real-world data—data that do not always meet the conditions needed for parametric analyses but data that still have value.
- Sprache
- Englisch
- Identifikatoren
- ISBN: 3319306332, 9783319306339DOI: 10.1007/978-3-319-30634-6_9Titel-ID: cdi_springer_books_10_1007_978_3_319_30634_6_9
- Format
- –
- Schlagworte
- Analysis of variance (ANOVA), Association, Bar plot (stacked, side-by-side), Beta values, Binomial logistic regression, Binomial probability, Binomial test, Box plot, Code book, Comma-separated values (.csv), Conditional density, Continuous scale, Correlation, Correlation coefficient, Cumulative probability, Density plot, Descriptive statistics, Distribution-free, Factor, Frequency distribution, Histogram, Interval, Kolmogorov-Smirnov (K-S) two-sample test, Mean, Median, Mode, Nominal, Nonparametric, Normal distribution, Null hypothesis, Odds, Odds ratio, Ordinal, Parametric, Percentile, Predictor variable, Probability & statistics, Probability (p-value), Quantile-Quantile (QQ, Q-Q), Scatter plot, Statistical significance, STEAM (Science, Technology, Engineering, Art + Design, and Mathematics), STEM (Science, Technology, Engineering, and Mathematics), Walsh test for two related samples