Statistics Flashcards
t test
For comparison of two means.
Assume the data is parametric.
Sample size >=3.
Paired t test
Comparison of two means where the data is derived from repeated measures.
Assumes parametric data.
N>=3
Mann-Whitney
The non-parametric equivalent of the t test.
Linear regression
f
SEM
Standard error of the mean.
Rather than being descriptive like S.D. , SEM gives an appreciation of how close your sample mean is to the population mean.
SD
Describes the variance/spread of your sample.
95% CI
There is a 95% chance that the population mean lies within the range.
P value
Used to decide whether a particular data point was significantly different from the control value. Under the null-hypothesis there is less than 5% probability that the control and treated data are random samples from the same distribution.
ANOVA one way
Analysis of variance.
Used to compare multiple means with only one independent variable.
Assumes the data are parametric and n>3.
ANOVA two way
Comparison of multiple means where there are two independent variables.
Assumes same as ANOVA one way.
Tukey’s post hoc
A
Dunnet’s post hoc
f
Kruskal-Wallis test
f
Wilcoxon test
f
Friedman’s test
f
Pearsons
This is for linear “least squares” regression. Pearon’s ”r” value is the correlation co-efficient derived by the product moment method. A value close to 0 represents a lack of correlation, whereas a value of +1 or -1 represents a perfect positive or negative linear correlation. The ”r2” value is the square of this “r” value and represents the “co-efficient of determination”. It ranges between 0 and 1 with 1 representing a perfect linear correlation between two variables.
Spearman
f
Logrank test
The logrank test is a non-parametric test for statistical significance testing of data that is not normally distributed.
