Download Levels of significance

Inferential
Statistics
Why are they used?
1)Statistical tests are used by Psychologists(and maths
boffins) to prove or disprove a Hypothesis.
2) Statistical tests are used to determine whether data
shows significance(if there is a relation or effect in
the experiment).
3) Statistical tests see if the NULL Hypothesis is
true(that results are due to chance/random).
So the test is there to find out if the result was
found by chance.
In fact we want to be 95% sure our results were not due to
chance. So we do a statistical test to find out.
What does p ≤ 0.05 level of significance mean?
This means that this is a 95% probability that the change in
the DV is as a result of the IV and a less than 5% probability
that this is due to random chance. The findings are
therefore statistically significant. Thus we can reject the
null hypothesis and accept the experimental/alternative
hypothesis.
What You Need to Know for
The Exam….

Know the purpose of using Inferential Statistics.

Know what test you would use and why.

Know how to conduct the test.

Whether or not the results are significant?
Choosing the Correct
Statistical Test
To decide what test you will use you need the following information:
Difference/Correlation/Association: (This you will gather from the
information given in the statement provided to you on the test.
Type of Participant Design: Independent Measures, Matched Pairs,
Repeated Measures
Type of Data: NOI
They may refer to the terms parametric and non parametric on your
exam.
Difference/Correlation:
Hypothesis

Hypothesis: predicts the outcome of the study

A one-tailed hypothesis (directional) predicts the expected
direction of results.

A two-tailed hypothesis (non-directional) which does not
predict the expected direction of the results.

There also needs to be a null hypothesis. This hypothesis
suggests that are results are down to chance and not your
IV.

They must be operationalised: to make the variables
measurable
What type of hypothesis am I
describing?
1. There will be a significant difference in test score
performance, measured by % on a 10 question Maths Test
between children who are born between October and April
than children who are born between May and September.
2. Children who are born between October and April will
perform significantly better in test score performance,
measured by % on a 10 question Maths Test than children
who are born between May and September.
3. There will be no significant difference in test score
performance, measured by % on a 10 question Maths Test
between children who are born between October and April
than children who are born between May and September.
Any difference will be down to chance.
Type of Participant Design: Independent
Measures, Matched Pairs, Repeated
Measures
How your participants are used.
Which One is Which
Bandura, Ross and Ross (1961) tested 74 preschoolers. They were put
into groups: a control group, single sex groups who saw a violent model
of either same sex or a different sex and single-sex groups who saw a
non-violent model of either the same sex or a different sex. Children who
saw a model who was violent were more likely to prelicate violent acts,
especially if the model was the same sex as them
A researcher wanted to test the effectiveness of two different treatments
for Schizophrenia. They divided the participants into two groups and
each group received one treatment. The participants were allocated
according to age, gender and how long they had has the disorder.
Kiecolt-Glaser (1984) took blood samples from 75 first year medical
students a) one month before their final examinations (relatively low
stress), and (b) during the examinations (high stress). She found that they
had reduced immune systems during times of stress.
Type of Data: NOI
Nominal: categories
Ordinal: ranking
Interval: data measure using units

A set of surgical records classifies patients as ‘chronic’,
‘acute’, or ‘not yet classified.’ What level of
measurement is being used?

The students organised themselves in order of what
month of the year that they were born. They started
with January and ended with December.

Students wrote a test and the results were presented in
%.
Chi Squared or (x ²)
Difference or an association between two variables
Independent Measures
Nominal data
Underline: the Design, The
Nominal data and how we know
that it is a test of difference.
156 boys and 204 girls were asked whether they liked
vanilla slices. Is there any evidence that there is a sex
difference in preference for vanilla slices?
Boys
Girls
Total
Like
94
175
269
Did not like
62
29
91
Total
156
204
360
Step 1: Label the cells (excluding totals)
Boys
Girls
Total
Like
94
175
269
Did not like
62
29
91
Total
156
204
360
Step 2: Work out the E values for each cell
E= Total of Row x Total of Column
Total
Boys
Girls
Like
94
a
175
b
269
Did not like
62
c
29
d
91
Total
156
204
Cell
Working
A
(269 x 156)÷ 360
B
C
D
Total
360
E value
Step 3: Work out X2 Value (Chi square)
X2= (Total of Cell O – E)2
E
Cel
l
Working
E value
A
(269 x 156) ÷ 360
116.57…
B
(269 x 204) ÷ 360
152.43…
C
(91x 156) ÷ 360
39.43…
D
(91 x 204) ÷ 360
51.57…
Cel
l
Working
X2 value
A
(94 - 116.57) 2 ÷ 116.57
4.42
B
C
D
Step 4: Work out the Total X2 Value
Add all the individual X2 values.
X2 value
4.42
3.34
12.92
9.88
Total =
Step 5: Work out the ‘c’ value
df= (Total number of rows -1) x ( Total number of columns –
1)
•df is the number which runs along the left side of the table
of critical values
•In this case our df=
•In some tables df appears as V.
Step 6: Using a table of critical values, find if the data is significant
•To be significant X2 value must be equal to or
exceed that found in the table.
df
•Use 0.05 degree of accuracy
1
P = 0.05
P = 0.01
P = 0.001
3.84
6.64
10.83
2
5.99
9.21
13.82
3
7.82
11.35
16.27
4
9.49
13.28
18.47
5
11.07
15.09
20.52
6
12.59
16.81
22.46
7
14.07
18.48
24.32
8
15.51
20.09
26.13
9
16.92
21.67
27.88
10
18.31
23.21
29.59
11
19.68
24.73
31.26
12
21.03
26.22
32.91
13
22.36
27.69
34.53
14
23.69
29.14
36.12
15
25.00
30.58
37.70
16
26.30
32.00
39.25
17
27.59
33.41
40.79
18
28.87
34.81
42.31
19
30.14
36.19
43.82
20
31.41
37.57
45.32
Are the Results Significant?
x ² (30.56)
Critical Value is (3.84)
What does this mean?
Homework
The results of an observation carried out in a record store are as follows. Is there a
significant association between gender and choice of music?
Male
Female
Total
Rock and pop
50
30
80
Classical
20
60
80
Total
70
90
160