Statistics: information Flashcards
What is the alpha (type I) error also known as?
Specificity
What are alpha (type I) errors directly related to (statistically)?
P value
What are beta (type II) errors also known as?
Sensitivity
What is the equation for calculating power (in simple terms)?
1-beta error
What power value do we typically want an experiment to have?
Between 0.8 and 0.9
What does power relate to (statistically)?
Sample size and effect size. If sample size is large enough, even a tiny effect size may be statistically significant (but not necessarily clinically or functionally significant)
When may precision and accuracy become uncoupled?
Systematic error
When is mean vs median usually used?
Mean - when data are normally distributed with no major outliers
Median - when data are skewed or non-normally distributed
If the median of data is used, what should be used to measure spread?
Interquartile range
If the mean is used, what should be used to measure spread?
Standard deviation - spread of direct data
Standard error - where the real mean may be based on the population
X% confidence intervals - the range containing the population mean X% of the time based on the data collected
How can we test for normality?
Visually of q-q plots
Using tests such as the Shapiro-Wilk test
If data are normally distributed, what type of test is used?
Parametric
If data are not normally distributed, what type of test is used?
Non-parametric tests
What do non-parametric tests typically do?
Rank data and analyse whether a difference exists in the average rank between groups
Why is ANOVA preferable to multiple t tests?
Reduced risk of type I errors which would occur due to multiple comparisons
What does ANOVA tell you? What does this mean?
That a difference exists between any of the groups tested, but not where. One must then use post-hoc tests to compare means and identify where the difference is (these will include corrections)
What does the Tukey test do?
Compares
What does the Tukey test do?
Compares the differences in means between all groups
What does the Dunnett correction do? When may this be used?
Compares the mean of each group to a control value - could use when samples are taken periodically and you want to test when they become significant (known boundary)
What does the Bonferroni correction do? How?
It adjusts the p value for multiple testing - p is changed to be equal to alpha divided by the number of tests performed
What are the 5 main assumptions of T tests?
Data are normal
Groups are independent (unpaired)/ samples are independent (paired)
Equal variance
Measurements are continuous
No significant outliers
What are the 4 main assumptions in ANOVAs?
Data are normal
Variance is equal
Samples are independent
Observations within each sample are random
What are the 4 assumptions of Pearson’s test?
Continuous variables
Paired values for each observation
No outliers for either variable
Data are linear
What information is required to calculate the number of replicates required to detect a known true difference?
The variation and size of difference expected, the accepted alpha/beta threshold - use past literature
