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Exam question
15 minutes to look over plan. 30 minutes to answer
question
Describe and evaluate the gender schema
theory of gender development
(8 marks + 16 marks)
Research methods
Recap: Levels of measurement
• most appropriate descriptive statistic to
calculate
• which graph to use
• which inferential test to use
Levels of measurement relate to quantitative
data.
Levels of measurement:
fill in the blank spaces
• ______ data: when the data is measured on a_____,
like someone’s height or the number of items
remembered in a memory test.
• _______data: the data is in some kind of ______
(order), for instance the _____that horses finish in a
race
• ______ data: data that is in ________; if it is in one
_______, it cannot be in another.
Levels of measurement:
fill in the blank spaces
• Interval data: when the data is measured on a scale,
like someone’s height or the number of items
remembered in a memory test.
• Ordinal data: the data is in some kind of rank
(order), for instance the order that horses finish in a
race
• Nominal data: data that is in categories; if it is in one
category, it cannot be in another.
Identify whether the data in each statement
is nominal, ordinal or interval.
1.
2.
3.
4.
5.
6.
7.
A psychologist counts the number of males and females who are shopping
on a Saturday morning in Churchill Square.
A researcher measures how quickly participants can run 50 metres.
A researcher measures the temperature at which people feel most
aggressive.
In a company participants were asked to indicate on a scale of 1-7 how much
they felt in control of their working environment.
A researcher asks five year olds what their favourite flavours of ice cream
are.
A psychologist measures the attachment style of children: secure or
insecure.
A researcher asks participants to put ten photographs of faces in order from
most to least attractive.
1. A psychologist counts the number of males and
females who are shopping on a Saturday morning in
Churchill Square. nominal
2. A researcher measures how quickly participants can
run 50 metres. interval
3. A researcher measures the temperature at which
people feel most aggressive. interval
4. In a company participants were asked to indicate on a
scale of 1-7 how much they felt in control of their
working environment. Ordinal
5. A researcher asks five year olds what their favourite
flavours of ice cream are. Nominal
6. A psychologist measures the attachment style of
children: secure or insecure. Nominal
7. A researcher asks participants to put ten photographs
of faces in order from most to least attractive. ordinal
Moving on to:
• Why we use inferential statistics
• Hypothesis
• Probability
• Levels of significance.
Why not just use descriptive stats?
• Descriptive statistics give us convenient and
easily understood summaries of the data but
we can’t draw any firm conclusions from
them, they are just an overview.
• In order to draw firmer conclusions and to
accept or reject hypotheses, inferential
statistics are needed.
What is a hypothesis?
Two hypothesis are formulated at the beginning of
a study:
• The alternative hypothesis (H1)
– Predicts that there will be a significant difference
– Directional or non directional
• The null hypothesis (HO)
– predicts that there will not be a significant difference
What is a null hypothesis and why do we
need one?
•
The null hypothesis predicts that any difference between two or
more sets of data will have occurred through chance alone
•
If it is rejected then we must retain the alternative hypothesis
and vica versa.
•
If the null hypothesis is rejected we say our results are
statistically significant.
•
If it is accepted we say they are NOT significant.
•
We focus on the null hypothesis because it eliminates bias from
the research by forcing the researcher to consider the view that
any difference found between the two sets of data has occurred
through chance alone
A team of psychologists was interested in studying the effects of alcohol on peoples'
reaction times. Earlier research suggested that an increase in reaction time was due to
the alcohol rather than peoples' expectations of alcohol. The psychologists recruited
two groups of volunteers (an independent groups design) from a local university. Each
participant's reaction time was measured by using a computer game.
The participants were then given a drink. The first group received a drink containing a
large measure of strong alcohol; the second group received an identical drink without
alcohol, but with a strong alcoholic smell. Finally, all participants were required to play
the computer game again to assess their reaction time. Once they had completed the
task, they were then thanked for their time and allowed to leave.
What is the IV?
whether the participants have had an alcoholic drink or one that is not alcoholic but
smells as if it is
What is the DV?
reaction times on a computer game
Null hypothesis:
There will be no difference between the university students‘ reaction times on a
computer game between those who have had an alcoholic drink or one that is not
alcoholic but smells as if it contains alcohol; any differences are due to chance factors.
A teacher in a small secondary school wanted to find out whether
there was any truth in her idea that students who used a computer
regularly for their homework achieved higher exam grades than those
who did not. She decided to interview a sample of 30 students taken
from across the school. She tape-recorded all the interviews. She later
obtained their end of year exam grades from their reports.
What is the IV?
whether the participants used a computer regularly for their
homework or didn’t use a computer regularly for their homework.
What is the DV?
Exam grade achieved
Null hypothesis:
There will be no difference between the exam grades achieved at the
end of year between those who regularly used a computer to
complete homework and those who did not regularly use a computer
to complete homework; any differences are due to chance factors.
What is statistical significance then?!
Inferential statistics is a test of significance because it
is designed to assess whether we reject or retain the
null hypothesis.
If the null hypothesis is retained, the result is not
significant; if it is rejected the result is significant.
Inferential statistical tests work by assessing the
probability of our results occurring due to chance
alone (rather than the IV)
We use it to determine if the probability of our results
being down to chance is low enough for our
alternative hypothesis to be accepted.
The inferential test ends with a probability value (p), which
can be anything between 0 and 1.
The value indicates the probability that the null hypothesis is
true.
Inferential statistics do not tell us that a null hypotheses can
certainly be rejected, only the probability that it can be
rejected.
In order for psychologists to judge that they can reject the null
hypotheses and retain the alternative hypotheses the
probability value must be very small.
Probability and Significance
Probability, or p, is expressed as a number
between 0 and 1.
0 means an event will not happen.
1 means that an event will definitely happen.
The P value will always be found to be between
0 and 1 due to the way in which it is calculated.
Activity
To give you an idea and to keep things easy complete the following
exercise using 0 – 100 rather than 0 - 1
On a scale of 0-100 rate the following statements for probability 0 =
Impossible and 100 = Certain (Remember the only thing certain is death
and the only thing impossible immortality!)
You winning the lottery
It raining in the next week
Dreaming of elephants this week
Having a day off ill this term
Becoming a famous entertainer
Becoming a parent in your lifetime
A cure for cancer being discovered in your lifetime
If you spin a coin it will come down heads
If you spin two coins they will both come down heads
Passing all you’re A levels
Because we used a scale between 0-100 your
answers are expressed as percentages.
Convert them into fractions and then decimals
e.g. 50% is ½ or 0.5
(move the decimal point two places to the left.
This converts the probability to a decimal
between 0 and 1)
The aim of inferential statistics is to discover if your results are statistically
significant.
A statistically significant result is one which is unlikely to have occurred
through chance.
Levels of significance
Researchers can use significance levels of 10%, 5%, 1% (or 0.1% in very
stringent conditions) - expressed as:
10%, 0.10, 1 in 10, p≤0.10.
5%, 0.05, 1 in 20, p≤0.05
1%, 0.01, 1 in 100, p≤0.01
If you use a 5% statistical significance level and this is achieved you are saying
that the probability of your results being a fluke and nothing to do with your
IV is less than 5%.
or you are 95% sure that your change in DV is because of your IV
We express our results in terms of the Null
Hypothesis, if a result is statistically significant
we can reject the null hypothesis.
If the result is not statistically significant we
must accept the null hypothesis.
Null Hypothesis: - Any difference between the
two conditions is due to chance.
Take a pack of cards…
I want to judge whether there is…
– ‘nothing funny’ going on with the cards (the null
hypothesis)
Or whether….
– “there is something funny going on “ – the
research hypothesis.
Significance level
What are the chances, if there was nothing going on?
I card
Probability is 50:50 that the card is red
i.e. 0.5
50 %
2
cards
3
cards
4
cards
5
cards
6
cards
22
Significance level
What are the chances, if there was nothing going on?
I card
Probability is 50:50 that the card is red
i.e. 0.5
50 %
2
cards
0.5 x 0.5 = 0.25
25 %
3
cards
0.5 x 0.5 x 0.5 = 0.125
About 12
%
4
cards
0.5 x 0.5 x 0.5 x 0.5 = 0.0625
About 6 %
5
cards
0.5 x 0.5 x 0.5 x 0.5 x 0.5 = 0.03125
About 3 %
6
cards
0.5 x 0.5 x 0.5 x 0.5 x 0.5 x 0.5 = 0.015625
About 1 %
5 % level
23
At what point do we judge that something funny is going
on when the picked cards are all red?
• Probably on the 4th card.
• The probability of the first 4 cards picked being red is
6%.
• So the probability of the null hypothesis being correct
is less that 6%.
• This finding supports the alternative hypothesis: that
the first 4 cards picked at random are NOT due to
chance.
Activity: complete task 8
Next lesson
• Type 1 and Type 2 error
• Choosing an appropriate statistical test