Statistics Flashcards
when would you use a Chi squared test?
- number of individuals in two or more categories have been counted
- you want to know if there is a significant difference between observed and expected results
when would you use Spearman’s Rank Correlation?
- measurements have been taken
- you want to know if there is an association/correlation between different measurements from the SAME sample
when would you use a t-test?
- measurements have been taken
- you want to compare the means of two sets of data
paired vs unpaired t-test
paired: two measurements are collected from the SAME individual
unpaired: two measurements are collected from DIFFERENT individuals
six assumptions made to use an unpaired t-test
- groups are independent
- same variable has been measured for an unbiased sample
- variable is continuous
- continuous variable is normally distributed for each group
- each group has approximately equal variances (similar SD)
- sample sizes for each group are roughly equal
five assumptions made to use a paired t-test
- two groups of with a specific relationship with each other (e.g. same individuals used in each sample)
- same variable has been measured for both unbiased samples
- variable is continuous
- continuous variable is normally distributed
- each group has similar variance/SD
two assumptions made to use Spearman’s Rank Correlation
- there is a set of items with data for BOTH variables for each item
- both variables are ordinal (can be ranked)
assumption made to use the Chi squared test
- sample size must be big enough so that all “expected values” are greater than 5
what probability should be used to find the critical value (if not stated)?
p=0.05 (95%)
degrees of freedom (one sample)
DF = N - 1
(N = sample number)
degrees of freedom (two samples)
DF = N1 + N2 - 2
what does the comparison of CV and t value mean? (with conclusion)
if t > CV, reject H0
if t < CV, accept H0
reject H0, we are 95% confident that something has caused the difference and it is not just down to chance
what does the comparison of CV and Χ² value mean? (with conclusion)
if X² > CV, then reject H0, there is a significant difference between observed and expected frequencies
if X² < CV, then accept H0, there is no significant difference between observed and expected frequencies
reject H0, there is less than a 5% probability that our results are due to chance
how do you find the CV for Spearman’s Rank Correlation?
use n (number of sample) to find CV in a table
(DO NOT USE DF)
what working should be shown on the data table for Spearman’s Rank Correlation?
- rank for BOTH variables
- difference between the ranks (and d²)