T TESTS ( DIFFERENCES)
Design
Repeated
need less p
ie. morning vs evening
same particpants
Independant
different participants
ie. sex differences
Variables
Dependant
Independent
outcome
manipulation
Assumptions
data type
ratio
parametric
interval
independent observations
data
Normally distributed
VIOLATES ASSUMPTIONS
NON PARAMETRIC
SKEW
Negitively
Positively
low s overrep
high s overrep
tail +ive
tail -ve
homogeneity of varience
consistent diff between groups
no significant difference
variance of data to be similar in all groups
LEVENES TEST
Independent
Research Q
HYPOTHESIS
Do M & F differ in enjoyment of TV
F and M will report different enjoyment of three TV Shows
EastEnders, Football and news
TWO TAILED
Variables
independant
dependant
SEX
Enjoyment
ANALYSIS OUTPUT
HOMOGENIETY
WHERE?
INDEPENDANT SAMPLES TEST TABLE
LEVENES #
Not signifigant
(p.>.050) ASSUMPTION MET
READ numbers of the Equal variences assumed
Signifigant
Read numbers of equal variences not assumed
(p< or equal to <.050) ASSUMPTION VIOLATED
F=0.4, p= .535 #
HOW TO REPORT
T TEST STATISTIC
t, df, sig
t(10) =2.5, p=.031 #
t(df)= t statistic, p value
There is a sig differnce
Group Statistics
females =sig higher
Descriptive stats per group
males sig lower
(M=6.8, SD=1.5)
(M= 4.2, SD=2.1)
GRAPHING
BAR GRAPH
ERROR BARS
(+-)1SD
REPEATED
Research question
Does increased time to learn words improve memory performance?
Variables
Indpendant
Dependant
Time to learn
2 levels
4 minutes
2 minutes
words recalled (15)
Hypothesis
The longer time to learn the better remembered
ONE TAILED
ANALYSIS
PAIRED SAMPLES STATISTICS
t (DF) = T statistic, signifigance
IE> t(5)= 7.9, p =.001
descriptive stats
higher mean = significant increase in memory performance (t test stat) with increasing time to learn the list of words. #
interpret the means
with 2 minutes recall time (m=7, SD=1.5), 4 minutes = (M=13, SD=1.6)
CREATE A BAR GRAPH WITH ERROR BARS
repeated test
assumption that independence of observations
THIS NOT POSSIBLE IN REPEATED MEASURES
cant avoid as same participants- no individual differences
random variance reduced
DIFFERENT ASSUMPTION - SPHERICITY
ONE SAMPLE
COMPARES from single sample to REFERENCE
ANALYSIS
ie average height in uk is 164cm - is our sample above below or average
EG sample mean = 37 test value= 50
look at one sample stats table for the mean to compare to TEST VALUE in other table
one sample t test table for test value
then use this for t value df, and sig
t(9)=5.6, p<.001
height of sample smaller than the average