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PSYCHOLOGY
COURSEWORK
THE RESULTS
RATIONALE/PURPOSE
•
The results section is where you
report the results that you have
found from your experiment.
•
You must report exactly what
you found, however you must
not explain why you found it
here, this goes in the
discussion.
ASSESSMENT CRITERIA
HL Criterion E - 2 marks
Results are clearly stated and accurate
and reflect the hypotheses and
research. Appropriate descriptive
statistics are applied to the data and
their use is explained. The graph of
results is accurate, clear and directly
relevant to the study. Results are
presented in both words and tabular
form.
HL Criterion F – 3 marks
An appropriate inferential statistics test
has been chosen and explicitly
justified. Results of the inferential
statistical test are accurately stated.
The null hypothesis has been accepted
or rejected appropriately according to
the results of the statistical test. A
statement of statistical significance is
appropriate and clear.
THE ESSENTIALS
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The essential elements of your
results section are as follows:
Descriptive statistics (justification
of and explanation of)
The results table (of descriptive
statistics)
Graph (of descriptive statistics)
Inferential statistics (justification of
and interpretation of)
DESCRIPTIVE STATISTICS
•
Your project must contain two
forms of descriptive statistics
1) measures of central tendency
- (i.e. mean/ median/ mode)
• 2) measure of dispersion
- (i.e. standard deviation)
•
MEASURES OF CENTRAL
TENDENCY
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This includes the mean, median
and mode.
You must first of all justify why
you have chosen to use the
mean, median or mode, i.e.
what are the strengths and
weaknesses of them? Which is
the most appropriate? Why?
MEASURES OF CENTRAL
TENDENCY

Then, you must include a table
of the calculated values of
mean, median or mode.

Do NOT include your workings
out here, they go in the
appendix (see ‘additional
important resources’). You can
use a calculator.
MEASURES OF CENTRAL
TENDENCY
Then, you must explain what the
calculated values show. This must
be detailed, i.e. Are the values
larger for condition A or B? Are
the m/m/m values the same in
condition A and the same in
condition B? Why/not? Are there
any obvious outliers in the results
table which may have distorted
the mean? Etc.
MEASURE OF DISPERSION

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The appropriate measure of
dispersion for interval/ratio data is
the standard deviation. This shows
how spread out the data are from the
mean.
You must first justify why you have
chosen this. Hint! Look in the Course
Companion p398 for the conditions
under which the SD is used.
MEASURE OF DISPERSION

Then, you must include the
calculated value of the standard
deviation for conditions A and B
in a table.

Do NOT include your workings
out here, they go in the
appendix (see ‘additional
important resources’) You can
use a calculator.
MEASURE OF DISPERSION

Then, you must explain what
the calculated value shows.

This must be detailed, i.e. Which
SD is larger? What does this
mean?
THE RESULTS TABLE
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You must include a table of results. Not raw
data, this goes in the appendices.
To do this, it is easier if you label your
conditions with an identifiable label, whilst also
naming your conditions ‘A’ and ‘B’. Condition
A must be the expected bigger result and
condition B the expected smaller result.
i.e. if you expect aggression to increase in a
warm classroom, and decrease in a cold
classroom, you would expect warm classroom
to have a bigger aggression score and so this
would be condition A.
Warm classroom, condition A
GRAPH

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You must display your results in
an appropriate graph. Only one
graph is required.
You must interpret your graph,
i.e. What does it show? Are the
scores higher in one condition?
How much are they higher by?
Are there any outliers? Etc.
INFERENTIAL STATISTICS
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The appropriate measure of statistical
significance depends on:
1) Test of difference or correlation
2) Level of data
3) Whether the data is related (repeated
measures) or unrelated (independent
groups)
It will either be a related t-test or an
unrelated t-test depending on whether
you have used repeated measures or
independent groups respectively.
INFERENTIAL STATISTICS

You must first justify why you have chosen
your statistical test.

You need to explain the conditions under which
the test is used (Hint! This is explained on the
previous slide!). Also explain that although the
criteria for a parametric test are not met (data
is normally distributed), these tests are very
robust.

Working out of the t-test must be present in the
appendices
INFERENTIAL STATISTICS
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You must now explain the level of
significance that has been used.
The p<0.05 level is used as it is the
conventional level of significance
that is accepted by psychologists.
P<0.05 means that there is a 95%
chance that the results occur due to
an effect of the IV on the DV, and a
5% chance that the results occur due
to random variability.
The ‘p’ stands for ‘probability’
INFERENTIAL STATISTICS

You must then interpret your stats
test results using a ‘numerical
statement of results’. This should
include:
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Calculated t value
Critical value
No. of Participants (N)
Directional/ non-directional hyp
Level of significance
Whether the null hypothesis is retained or rejected
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See the next slide or the VTLE
results section for help with this
NUMERICAL STATEMENT
OF RESULTS EXAMPLE
The calculated value from the
related/unrelated t-test was __. This is less
than/ more than the critical value of __ for a
directional/ non-directional (1 tailed/ 2
tailed) hypothesis when N = __. This shows
that the risk that this difference occurred by
chance is more than/ less than 0.05 or 5%.
The result is therefore significant/ nonsignificant and the null hypothesis can be
rejected/ retained. (t=_,N=_, CV _, p<0.05).
POINTS TO REMEMBER!
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Explain and interpret your results in
detail
Be consistent in calling your
conditions ‘A’ and ‘B’
Adopt a consistent approach
throughout the section
Don’t include any workings out.
These must appear in the appendix
(see ‘additional important
resources’)