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- https://stats.libretexts.org/Bookshelves/Applied_Statistics/Mikes_Biostatistics_Book_(Dohm)/05%3A_Experimental_design/5.2%3A_Experimental_units_and_sampling_unitsIntroduction to sampling units, experimental units, and the concept of level at which units are independent within an experiment. The problem of pseudoreplication from lack of sufficient independence.
- https://stats.libretexts.org/Bookshelves/Applied_Statistics/Mikes_Biostatistics_Book_(Dohm)/04%3A_How_to_Report_Statistics/4.08%3A_Ternary_plotsTernary plots as a method of displaying 3 ratio variables that in total sum up to 1. Creating ternary plots in R, with examples of use cases.
- https://stats.libretexts.org/Bookshelves/Applied_Statistics/Mikes_Biostatistics_Book_(Dohm)/01%3A_Getting_Started/1.1%3A_A_quick_look_at_R_and_R_CommanderA quick tutorial for installing, starting, writing and executing commands on, and exiting R and R Commander.
- https://stats.libretexts.org/Bookshelves/Applied_Statistics/Mikes_Biostatistics_Book_(Dohm)/13%3A_Assumptions_of_Parametric_Tests/13.2%3A_Why_tests_of_assumption_are_importantErrors that can arise if data violate the assumptions upon which statistical tests like the ttt-tests or ANOVA are based. Introduction to some alternative methods that can be used in cases with such v...Errors that can arise if data violate the assumptions upon which statistical tests like the ttt-tests or ANOVA are based. Introduction to some alternative methods that can be used in cases with such violations.
- https://stats.libretexts.org/Bookshelves/Applied_Statistics/Mikes_Biostatistics_Book_(Dohm)/04%3A_How_to_Report_Statistics/4.01%3A_Bar_(column)_chartsDifferent forms of bar graphs, the situations in which they should be used, and how to create them in R.
- https://stats.libretexts.org/Bookshelves/Applied_Statistics/Mikes_Biostatistics_Book_(Dohm)/12%3A_One-way_Analysis_of_Variance/12.1%3A_The_need_for_ANOVAThe increasing rate of error when a series of t-tests is used to compare data from 3 or more groups, and why this creates a need for ANOVA. Brief discussion of other post-hoc tests that account for th...The increasing rate of error when a series of t-tests is used to compare data from 3 or more groups, and why this creates a need for ANOVA. Brief discussion of other post-hoc tests that account for the multiple comparison problem.
- https://stats.libretexts.org/Bookshelves/Applied_Statistics/Mikes_Biostatistics_Book_(Dohm)/07%3A_Probability_and_Risk_Analysis/7.1%3A_Epidemiology_definitionsList of definitions for key terms used in epidemiology.
- https://stats.libretexts.org/Bookshelves/Applied_Statistics/Mikes_Biostatistics_Book_(Dohm)/07%3A_Probability_and_Risk_Analysis/7.4%3A_Epidemiology_relative_risk_and_absolute_risk%2C_explainedHow absolute and relative risk reductions are calculated in an epidemiological context, with confidence intervals. Discussion of the Number needed to treat statistic. Includes worked examples.
- https://stats.libretexts.org/Bookshelves/Applied_Statistics/Mikes_Biostatistics_Book_(Dohm)/06%3A_Probability_and_Distributions/6.07%3A_Normal_distribution_and_the_normal_deviateUse of the Z score, or normal deviate, to normalize any given normal distribution to the standard normal distribution. Applications of this technique in data sets, including a worked example.
- https://stats.libretexts.org/Bookshelves/Applied_Statistics/Mikes_Biostatistics_Book_(Dohm)/20%3A_Additional_TopicsBrief discussions and R script for various additional biostatistics topics. Note: many sections are still under construction.
- https://stats.libretexts.org/Bookshelves/Applied_Statistics/Mikes_Biostatistics_Book_(Dohm)/08%3A_Inferential_StatisticsIn biology, experimental results are usually not clear-cut, so tests to support decisions between competing hypotheses are needed. This chapter starts our introductions to specific types of statistica...In biology, experimental results are usually not clear-cut, so tests to support decisions between competing hypotheses are needed. This chapter starts our introductions to specific types of statistical tests, using the frequentist Null Hypothesis Significant Testing (NHST) approach.
