Thesis Stats Set

Linear Mixed Model

A statistical model that incorporates both fixed and random effects, used for analyzing data with multiple levels of variation, often applied in situations where measurements are taken across different groups or time points.

Data Transformation

A method used to prepare data for analysis by altering its format or structure, often to meet statistical assumptions or improve interpretability. Transformation chosen had model with lowest AIC

SGR

(Specific Growth Rate) is a measure of the growth rate of an organism or population, typically expressed as the increase in biomass per unit of biomass per unit of time.

Fishers Exact Test

A statistical test used to determine if there are nonrandom associations between two categorical variables in a contingency table, particularly useful when sample sizes are small. It calculates the exact probability of observing the data given the null hypothesis of independence. used with binomial survival data

Pairwise Fisher’s Test

uses fishers exact test instead of chi-squared tests to evaluate null hypothesis between no more than 2 groups. Used as a post hoc

ANCOVA

Analysis of covariance is used to test the main and interaction effects of categorical variables on a continuous dependent variable, controlling for the effects of selected other continuous variables, which co-vary with the dependent. The control variables are called the "covariates." I used it for comparing SDs at time0 and timef

F-Test

a statistical test that compares variances. It is used to determine if the variances of two samples, or if the ratios of variances among multiple samples, are significantly different. used as post hoc for ancova if data was normal.

Levene’s Test

same function as F-test, but performs better (less type I errors) when data strays from normality assumptions

Pearson’s Correlation 

popular statistical analysis to measure how strong a relationship is between two variables

AIC

An estimator of prediction error. Given a collection of models for the data, AIC estimates the quality of each model, relative to each of the other models. Thus, AIC provides a means for model selection.

Chi-squared test vs. Fishers Exact Test

Fisher’s test is good for small sample sizes. Some argument it provides a “correct” but estimated answer to hypothesis. However, Fischers works for tests beyond 2×2 tables and results for my studies were not borderline, so concluded a good stat for limited data 

Probability Density Curve

Function that can be interpreted as providing a relative likelihood that the value of the random variable would be equal to that sample. Area under the curve is = 1. Y-axis is variable used to find x. Not very useful in understaning graph and PDFs are often plotted without y-axis