There either is or is not an effect and we need to decide, based on our statistics, which
one is more likely to be true.
o
Ex. Aggression modelling experiment
Null hypothesis H
0
– the population mean of the model group is equal to the
population mean of the nomodel group
Research hypothesis H
1
– the population mean of the model group is not equal to
the population mean of the nomodel group
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The null hypothesis is used in inferential statistics because it is a very precise statement – the
population means are exactly equal
o
This precision permits us to know the probability of the outcome of the study occurring if
the null hypothesis is true in the population
o
Such precision is not possible with the research hypothesis, so we infer that the research
hypothesis is likely true in the population only by rejecting the null hypothesis
o
Null hypothesis is rejected when there is a very low probability that the obtained results
could be due to random error
This is what is meant by statistical significance:
A significant result is one that has a very low probability of occurring if there is no
effect in the population (e.g. group means are equal)
Significance indicates that there is a low probability that the difference
between the obtained sample means (or the nonzero correlation) was
due to random error.
PROBABILITY AND SAMPLING DISTRIBUTIONS

Probability
is the likelihood of the occurrence of some event or outcome.

Probability in statistical inference is used in much the same way
o
We want to specify the probability that an event (in this case, a difference between
means in the sample) will occur if there is no difference in the population
PROBABILITY: THE CASE OF MIND READING

Ex. Friend claims to have mind reading or ESP, you decide to test by flipping coins 10 times
o
Goal is to determine whether answers reflect random error (guessing) or whether
something more than random error is occurring
o
Null hypothesis is that only random error is operating
o
Research hypothesis sis that the number of correct answers shows more than random or
chance guessing

The probability required for significance is called the
Alpha Level
o
Most common
alpha level
probability used is 0.05
Outcome is considered significant when there is a 0.05 or less probability of
obtaining the results if the
null hypothesis
is actually true.
If it is very unlikely that random error is responsible for the obtained results, the
null hypothesis is rejected.
SAMPLING DISTRIBUTIONS

A probability distribution called Binomial distribution

Such distributions are called
null hypothesis sampling distributions
or simply
sampling
distributions

Sampling distribution
is based on the assumption that the null hypothesis is true;
o
in the mind reading example, the null hypothesis is that the person is only guessing and
should therefore get 50% correct.