INTRODUCING INFERENTIAL TESTS
NULL HYPOTHESIS (H₀) – statement of no effect (no difference or no
correlation).
ALTERNATIVE HYPOTHESIS (H₁) – a statement that there is an effect
between two variables.
DIRECTIONAL HYPOTHESIS – a statement that predicts the direction
of the relationship between two variables.
NON-DIRECTIONAL HYPOTHESIS – a statement that predicts a
difference between two variables but doesn’t suggest what
difference.
PROBABILITY
Inferential tests are used to work out whether a difference is or is
not significant.
These tests allow you to work out, at a given PROBABILITY, whether
a pattern in the data could have arisen by CHANCE or whether the
effect occurred because there is a real difference/correlation.
CHANCE = refers to something with no cause.
You can’t be 100% certain that an observed effect was not due to
chance but you can state how certain you are.
Usually psychologists use a probability of 95%.
This expresses the degree of uncertainty.
It means there is a 5% chance (probability) that the results would
occur even if there was no real difference/correlation between the
two variables.
This probability of 5% is recorded as:
P = 0.05 (P means probability)
Sometimes psychologists want to be more certain, so may use a
stricter probability, such as p<0.01 or p<0.001.
The chosen value of ‘p’ is called the SIGNIFICANCE LEVEL.
USING INFERENTIAL TESTS
Inferential tests help us to draw inferences about populations based
on the samples tested.
These tests allow us to infer that a pattern in the data is likely (or
not) to be due to chance.
OBSERVED + CRITICAL VALUES
Each inferential test involves taking the data collected in a study +
doing some calculations to produce a single number called the TEST
STATISTIC.
NULL HYPOTHESIS (H₀) – statement of no effect (no difference or no
correlation).
ALTERNATIVE HYPOTHESIS (H₁) – a statement that there is an effect
between two variables.
DIRECTIONAL HYPOTHESIS – a statement that predicts the direction
of the relationship between two variables.
NON-DIRECTIONAL HYPOTHESIS – a statement that predicts a
difference between two variables but doesn’t suggest what
difference.
PROBABILITY
Inferential tests are used to work out whether a difference is or is
not significant.
These tests allow you to work out, at a given PROBABILITY, whether
a pattern in the data could have arisen by CHANCE or whether the
effect occurred because there is a real difference/correlation.
CHANCE = refers to something with no cause.
You can’t be 100% certain that an observed effect was not due to
chance but you can state how certain you are.
Usually psychologists use a probability of 95%.
This expresses the degree of uncertainty.
It means there is a 5% chance (probability) that the results would
occur even if there was no real difference/correlation between the
two variables.
This probability of 5% is recorded as:
P = 0.05 (P means probability)
Sometimes psychologists want to be more certain, so may use a
stricter probability, such as p<0.01 or p<0.001.
The chosen value of ‘p’ is called the SIGNIFICANCE LEVEL.
USING INFERENTIAL TESTS
Inferential tests help us to draw inferences about populations based
on the samples tested.
These tests allow us to infer that a pattern in the data is likely (or
not) to be due to chance.
OBSERVED + CRITICAL VALUES
Each inferential test involves taking the data collected in a study +
doing some calculations to produce a single number called the TEST
STATISTIC.
