The document discusses the null hypothesis for an independent-samples t-test. The null hypothesis states that there is no effect or relationship between the independent and dependent variables. It provides a template for writing the null hypothesis: "There is no significant difference in [dependent variable] between [level 1 of independent variable] and [level 2 of independent variable]." Two examples applying this template are given, comparing ACT scores between students who eat different foods and comparing IQ scores between teenagers listening to different music types.
3. With hypothesis testing we are setting up a null-hypothesis
– the probability that there is no effect or
relationship –
4. With hypothesis testing we are setting up a null-hypothesis
– the probability that there is no effect or
relationship – and then we collect evidence that leads
us to either accept or reject that null hypothesis.
5. As you may recall, an independent-sample t-test
attempts to compare an independent sample with
another independent sample.
6. Here is a template for writing a independent sample t-test
null hypothesis.
7. There is no significant difference in [insert the
Dependent Variable] between [insert Level 1 of the
Independent Variable] and [insert Level 2 of the
Independent Variable]
9. Let’s say we want to know if teenagers who eat
asparagus (sample size = 30) get better ACT scores than
teenagers who eat broccoli (sample size = 25) .
16. Here is the hypothesis:
There IS a statistical difference in IQ scores
between teenagers who listen to elevator music
on their iPods and those who listen to screaming
rock.
17. Here is the null-hypothesis:
There IS NO statistical difference in IQ scores
between teenagers who listen to elevator music
on their iPods and those who listen to screaming
rock.
18. Here is the Template Again
There is no significant difference in [insert the
Dependent Variable] between [insert Level 1 of the
Independent Variable] and [insert Level 2 of the
Independent Variable]