It is assumed that you have been introduced to the ideas of parametric descriptions of statistical data (e.g., mean, standard deviation, etc.) in the context of physical measurements. These concepts must be broadened and generalized in their interpretations when used in the context of biological data. It is the purpose of this module to introduce appropriate biological examples and employ them to generate and illustrate these broader notions of statistical analysis. Of particular interest will be questions such as: What is it that the mean value of a data set seeks to represent when there is no \u27true value \u27 underlying the measurements? What are the consequences of not being able to reduce data \u27errors\u27 (sic; better \u27varia...
Knowledge in statistics is essential to draw solid conclusions from data. This chapter covers the ba...
Technological advancements in biology and microscopy have empowered a transition from bioimaging as ...
and technical replicates. The quality of an experiment design is commonly assessed by calculating it...
It is assumed that you have been introduced to the ideas of parametric descriptions of statistical d...
This open access textbook provides the background needed to correctly use, interpret and understand ...
In spite of the title, this is really a textbook for a one‐semester, introductory statistics course ...
There is an increasing need for students in the biological sciences to build a strong foundation in ...
Statistics should be considered as a tool by the animal experimenter in much the same way that a che...
Most introductory statistics text-books are written either in a highly mathematical style for an int...
An introduction to mathematical and statistical methods that are most useful to biologists, this cou...
If a sample of measurements comes from a population that is normally distributed, we can use several...
Biological response is characterized by variation: different organisms do not react in exactly the s...
This computational science module covers the basics of logarithms and exponents (i.e., magnitude sca...
About the book: Thirty leading international figures celebrate 50 years of achievement in biometry ...
There is widespread misuse of statistics in research, particularly in the life sciences (Weissgerber...
Knowledge in statistics is essential to draw solid conclusions from data. This chapter covers the ba...
Technological advancements in biology and microscopy have empowered a transition from bioimaging as ...
and technical replicates. The quality of an experiment design is commonly assessed by calculating it...
It is assumed that you have been introduced to the ideas of parametric descriptions of statistical d...
This open access textbook provides the background needed to correctly use, interpret and understand ...
In spite of the title, this is really a textbook for a one‐semester, introductory statistics course ...
There is an increasing need for students in the biological sciences to build a strong foundation in ...
Statistics should be considered as a tool by the animal experimenter in much the same way that a che...
Most introductory statistics text-books are written either in a highly mathematical style for an int...
An introduction to mathematical and statistical methods that are most useful to biologists, this cou...
If a sample of measurements comes from a population that is normally distributed, we can use several...
Biological response is characterized by variation: different organisms do not react in exactly the s...
This computational science module covers the basics of logarithms and exponents (i.e., magnitude sca...
About the book: Thirty leading international figures celebrate 50 years of achievement in biometry ...
There is widespread misuse of statistics in research, particularly in the life sciences (Weissgerber...
Knowledge in statistics is essential to draw solid conclusions from data. This chapter covers the ba...
Technological advancements in biology and microscopy have empowered a transition from bioimaging as ...
and technical replicates. The quality of an experiment design is commonly assessed by calculating it...