Understanding Statistical Error: A Primer for Biologists
Understanding Statistical Error: A Primer for Biologists
Editor/Author
Gierlinski, Marek
Publication Year: 2016
Publisher: Wiley
Single-User Purchase Price:
$60.00

Unlimited-User Purchase Price:
$90.00
ISBN: 978-1-119-10691-3
Category: Mathematics & Statistics - Statistics
Image Count:
68
Book Status: Available
Table of Contents
This accessible introductory textbook provides a straightforward, practical explanation of how statistical analysis and error measurements should be applied in biological research.
Table of Contents
- Introduction
- Why do we need to evaluate errors?
- Probability distributions
- Random variables
- What is a probability distribution?
- Mean, median, variance and standard deviation
- Gaussian distribution
- Central limit theorem
- Log-normal distribution
- Binomial distribution
- Poisson distribution
- Student's t-distribution
- Measurement errors
- Where do errors come from?
- Simple model of random measurement errors
- Intrinsic variability
- Sampling error
- Simple measurement errors
- Statistical estimators
- Population and sample
- What is a statistical estimator?
- Estimator bias
- Commonly used statistical estimators
- Standard error
- Standard error of the weighted mean
- Error in the error
- Degrees of freedom
- Confidence intervals
- Sampling distribution
- Confidence interval: what does it really mean?
- Why 95%?
- Confidence interval of the mean
- Standard error versus confidence interval
- Confidence interval of the median
- Confidence interval of the correlation coefficient
- Confidence interval of a proportion
- Confidence interval for count data
- Bootstrapping
- Replicates
- Error bars
- Designing a good plot
- Error bars in plots
- When can you get away without error bars?
- Quoting numbers and errors
- Summary
- Propagation of errors
- What is propagation of errors?
- Single variable
- Multiple variables
- Correlated variables
- To use error propagation or not?
- Example: distance between two dots
- Derivation of the error propagation formula for one variable
- Derivation of the error propagation formula for multiple variables
- Errors in simple linear regression
- Linear relation between two variables
- Straight line fit
- Confidence intervals of linear fit parameters
- Linear fit prediction errors
- Regression through the origin
- General curve fitting
- Derivation of errors on fit parameters
- Worked example
- The experiment
- Results
- Discussion
- The final paragraph
- Solutions to exercises
- Appendix A
- Bibliography