{"title":"Monte Carlo tests and randomization.","authors":"D. Quicke, B. A. Butcher, R. K. Welton","doi":"10.1079/9781789245349.0016","DOIUrl":"https://doi.org/10.1079/9781789245349.0016","url":null,"abstract":"Abstract\u0000 This chapter focuses on Monte Carlo tests and randomization. It involves randomizing the observed numbers many times and comparing the randomized results with the original observed data. It is shown how randomization can be used in experimental design and sampling.","PeriodicalId":167700,"journal":{"name":"Practical R for biologists: an introduction","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127191795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"More on manipulating text.","authors":"D. Quicke, B. A. Butcher, R. K. Welton","doi":"10.1079/9781789245349.0022","DOIUrl":"https://doi.org/10.1079/9781789245349.0022","url":null,"abstract":"Abstract\u0000 This chapter provides more information on manipulating text, presenting two examples. Example 1 focuses on standardizing names in a phylogenetic tree description, using R to reformat taxon names, create lists, sort data and use wildcards for when some things you are interested in don't have exactly the same length. The example tree description concerns parasitoids of caterpillars at a study site that have been DNA barcoded and their possible taxonomic identities added automatically. Example 2 deals with substrings of unknown length. This example search for a numeric substring of unknown length but with a standard prefix, using data of some DNA sequences from a set of Aleiodes wasps. The trimming of white spaces and/or tabs, use of wildcards to locate internal letter strings, finding of suffixes, prefixes and specifying of letters, numbers and punctuation, manipulation of character case, ignoring of character case, and specifying of particular and modifiable character classes are briefly described.","PeriodicalId":167700,"journal":{"name":"Practical R for biologists: an introduction","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122597548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Very basic R syntax.","authors":"D. Quicke, B. A. Butcher, R. K. Welton","doi":"10.1079/9781789245349.0003a","DOIUrl":"https://doi.org/10.1079/9781789245349.0003a","url":null,"abstract":"Abstract\u0000 R is a programming language that has a huge range of inbuilt statistical and graphical functions. Firstly, this chapter shows how R works by talking you through a number of exercises, often producing graphical output, so you will get to know how to write simple code and become familiar with some of the most commonly used R functions for manipulating data and doing simple calculations. For ease, the chapter will firstly use a non-biological type of example. Thereafter, it will enter, display and analyse a number of real biological or medical datasets as might be obtained in student class experiments or fieldwork projects. Further on, it will present an outline of statistical tests appropriate to various types of data that you will come across.","PeriodicalId":167700,"journal":{"name":"Practical R for biologists: an introduction","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128209829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Regression and correlation analyses.","authors":"D. Quicke, B. A. Butcher, R. K. Welton","doi":"10.1079/9781789245349.0119","DOIUrl":"https://doi.org/10.1079/9781789245349.0119","url":null,"abstract":"Abstract\u0000 This chapter focuses on regression and correlation analyses. Correlation and regression analyses are used to test whether, and to what degree, variation in one continuous variable is related to variation in another continuous variable. In correlation analysis, there are no control over either variable, they are just data collected, and indeed, even if two variables are strongly correlated, they may not be influencing one another but simply both being affected by a third which perhaps was not measured. The initial assumption of the analysis is that the values of both variables are drawn from a normal distribution. In regression analysis one of the variables are being controlled seeing whether changing its value affects the other. The variable being controlled is the explanatory variable (sometimes called the treatment) and the other is the response variable. As the explanatory variables are being controlled, they are probably going to be set at specified values or set increments and are therefore not normally distributed. There may be more than one explanatory variable. If all the explanatory variables are categorical then the regression is called an ANOVA.","PeriodicalId":167700,"journal":{"name":"Practical R for biologists: an introduction","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123866459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Commonly used measures and statistical tests.","authors":"D. Quicke, B. A. Butcher, R. K. Welton","doi":"10.1079/9781789245349.0103","DOIUrl":"https://doi.org/10.1079/9781789245349.0103","url":null,"abstract":"Abstract\u0000 There are a number of statistical tests that are frequently used, even by non-specialists. This chapter will cover tests such as Chi-squared, Fisher's exact test, Mann-Whitney U and several variations of the Student's t-test, amongst others.","PeriodicalId":167700,"journal":{"name":"Practical R for biologists: an introduction","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128250238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Dates and Julian dates.","authors":"D. Quicke, B. A. Butcher, R. K. Welton","doi":"10.1079/9781789245349.0227","DOIUrl":"https://doi.org/10.1079/9781789245349.0227","url":null,"abstract":"Abstract\u0000 This chapter deals with dates and Julian dates. To illustrate some date handling, the chapter will look at nest building and laying dates for breeding pairs of the blue tit (Cyanistes caeruleus) in Europe, on the mainland and on the island of Corsica. The problem with two-digit dates and POSIX (using data available online for burials at the Hope Cemetery, Derbyshire, UK); phenology and the density function (using data on European corn borer collected in 2003 at a light trap); extraction of day and month from Julian days; and the seasonal patterns and other smoothing curves (presenting data on the abundance (shell influx) of the foraminiferan Turborotalita quinqueloba amassed over a nearly 3-year sampling period at a given site) are described.","PeriodicalId":167700,"journal":{"name":"Practical R for biologists: an introduction","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117239068","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Food webs and simple graphics.","authors":"D. Quicke, B. A. Butcher, R. K. Welton","doi":"10.1079/9781789245349.0028","DOIUrl":"https://doi.org/10.1079/9781789245349.0028","url":null,"abstract":"Abstract\u0000 Food webs are fundamental in much of ecology and there has been a steady increase in studying their structure and properties over the past 50 years, nowadays often utilizing molecular methods too. First, this chapter will create code to draw a food web, then it will introduce the package cheddar. The reason for learning how to produce your own is not just to improve programming skill and logical thinking, it also means you are in a position to customize your diagrams in ways that perhaps are not available in pre-written packages. A parasitoid foodweb example is given. In this example from Thailand, 22 braconid parasitoid wasps, representing a total of 9 species were associated with 22 lepidopteran hosts representing a total of 11 species using DNA barcoding.","PeriodicalId":167700,"journal":{"name":"Practical R for biologists: an introduction","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115648513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Plotting biological data in various ways.","authors":"D. Quicke, B. A. Butcher, R. K. Welton","doi":"10.1079/9781789245349.0037","DOIUrl":"https://doi.org/10.1079/9781789245349.0037","url":null,"abstract":"Abstract\u0000 This chapter introduces plotting line graphs, bar charts, pie charts, box and whisker plots. It will troubleshoot the main areas where you are likely to encounter problems. It will show how to create log plots, add legends, error bars, notches and confidence limits, and introduce confidence limits and statistical testing. Examples are given, including bryophytes up a mountain; relationship between rural population size and the potential remaining intact forest; dietary differences between hornbill species (Buceros bicornis, Rhyticeros undulatus, Anthracoceros albirostris and Anorrhinus (Ptilolaemus) tickelli); and study of the level of trematode infection in various species of fish in Thailand.","PeriodicalId":167700,"journal":{"name":"Practical R for biologists: an introduction","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127132394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"More generalized linear modelling.","authors":"D. Quicke, B. A. Butcher, R. K. Welton","doi":"10.1079/9781789245349.0171","DOIUrl":"https://doi.org/10.1079/9781789245349.0171","url":null,"abstract":"Abstract\u0000 This chapter employs generalized linear modelling using the function glm when we know that variances are not constant with one or more explanatory variables and/or we know that the errors cannot be normally distributed, for example, they may be binary data, or count data where negative values are impossible, or proportions which are constrained between 0 and 1. A glm seeks to determine how much of the variation in the response variable can be explained by each explanatory variable, and whether such relationships are statistically significant. The data for generalized linear models take the form of a continuous response variable and a combination of continuous and discrete explanatory variables.","PeriodicalId":167700,"journal":{"name":"Practical R for biologists: an introduction","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131502259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"First simple programs and graphics.","authors":"D. Quicke, B. A. Butcher, R. K. Welton","doi":"10.1079/9781789245349.0013","DOIUrl":"https://doi.org/10.1079/9781789245349.0013","url":null,"abstract":"Abstract\u0000 This chapter presents the basics for handling text, numbers and simple data files. It focuses on basic R features, commas, brackets and concatenation, colon character, raise to the power symbol, exiting from R, and help pages.","PeriodicalId":167700,"journal":{"name":"Practical R for biologists: an introduction","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116192030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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