Exam 2 - PSYC275

generic formula for MoE

(t / z) * (standard error)

MoE formula for one sample

t ( s / √ n)

MoE formula for two independent samples

t ( √ s₁² / n_{1 +}  s₂² / n₂ ) 

MoE formula for 2 dependent samples

t (s_d / √n) 

formula for z - score

x - μ / σ

what should an APA style paragraph 

1) measurements scales (nominal.. ordinal.. interval.. ratio) 

2) sample size 

3) the spread (standard deviation.. range.. mean + CI) 

4) r value (CI for correlation.. is hypothesis accepted.. t(x) = x.. p < x.. is it a + or - relationship)

positive relationship

x increases.. y increases

negative relationship

x increases.. y decreases

nominal

categories and no ranking

ordinal

rank but no distinction between ranks

interval

rank and equal distance between ranks.. can go below 0

ratio

rank and equal distance between ranks.. cannot go below 0

μ

population mean

s

standard deviation

σ

population standard deviation 

n / N

• sample size 

• population size 

∑

add all values

s² / σ²

sample / population variance

M

sample mean

SE

standard error

z

z-score

p

p - value

df

degrees of freedom (n-1)

MoE

margin of error

r

strength + direction of relationships

H₀

null hypothesis  (x effect) 

H₁

alternative hypothesis (there is an effect / difference)

no relationship in a scatterplot

dots are random

positive linear in a scatterplot

dots rise from left to right

negative linear in a scatterplot

dots fall left to right

outliers

any points that don’t fit the pattern

reliability

how consistent a measure is

validity

how well a measure reflects what its suppose to

paired design

same participants → similar related scores (change within people)

• ex. before VS after treatment

Cohen’s d independent group

M₁ + M₂ / S_pooled 

independent study

finds difference between participants

type I error

reject H₀ when true

• ex. approving a drug that doesn’t work

type II error

failure to reject H_o when false

• ex. rejecting a drug that works 

if p is less than 0.5 : 

reject hypothesis

if p is more than 0.5 :

accept hypothesis