types of statistical analysis Flashcards
Descriptive analysis
sample of scores inform of frequency using mean, SD etc.
inferential statistics
conclude population based on samples and measures probably of getting results by chance.
-alternative and null
what does probability and specific methods
draw inferences- like samples draw inferences on population.
-sets interferences scientific use to draw inferences on data.
how is probability expressed
As a p(sig) value from 0 to 1-less likely occur by chance
smaller p the likely reject null and accept alternative.
theory 1
prob less 0.05 reject null accept alternative(because larger than 5 percent rate given as precaution can say.)
theory 2
p(E)=n(e)/n(s)
(number outcomes in events)/ number outcome sample size.
hypothesis testing rule
In statistics look at what data look like if not statistically significant .Before reject null must check if p larger 0.05.
One tailed or two tailed
most statistics have two directional results
One tailed
direction of results- The alternative hyp has one end reject null with 5 percent error rate
Two-tailed
direction of results- rate split between 2.5 and 2.5 percent each.
Graphs show how reaction time
-simple RT- single stimulus and faster respones.
choice RT-multiple choices- slower and more varied answers.-mean difference larger as more choice.
therefore always want more samples to create higher chance of correctly rejecting the null (as know mean overlap=sig is correctly alternative or null)
comparing means from both RT
Large regional overlap- there is a mean difference but difference is small.(small difference little sig difference between two groups)
small regional overlap- there is a mean difference but difference is large.
what effects this regional gaps
small regional gaps implies small mean= no sig
- SD is small.-(significates significance.)-shown by how tall
SD large–no sig diff between data points
large regional gaps-SD is large.
mean difference.)
large overlapping
(sample size?)
