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Psychologists conduct probability and significance testing to see if their results show real differences or correlations or if they are due to:
a) chance
b) the independent variable
c) controlled conditions
a.
Psychologists conduct probability and significance testing to see if their results show real differences or correlations, or if they are due to chance.
How is the 5% probability level expressed?
a) p > 0.05
b) p < 0.05
c) p < 0.5
b.
The 5% probability level is expressed as p < 0.05.
Which one of the following questions is not used to determine the critical value?
a) What is the N value?
b) What is the independent variable?
c) Is the test one-tailed or two-tailed?
d) What is the level of significance?
b.
'What is the independent variable?' is not used to determine the critical value.
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Psychologists conduct probability and significance testing to see if their results show real differences or correlations or if they are due to:
a) chance
b) the independent variable
c) controlled conditions
a.
Psychologists conduct probability and significance testing to see if their results show real differences or correlations, or if they are due to chance.
How is the 5% probability level expressed?
a) p > 0.05
b) p < 0.05
c) p < 0.5
b.
The 5% probability level is expressed as p < 0.05.
Which one of the following questions is not used to determine the critical value?
a) What is the N value?
b) What is the independent variable?
c) Is the test one-tailed or two-tailed?
d) What is the level of significance?
b.
'What is the independent variable?' is not used to determine the critical value.
What is a Type I Error?
A Type I Error occurs when the null hypothesis is rejected when it should have been accepted.
The researcher claims that the results are significant when in fact they are not (also known as a false positive).
A Type II Error occurs when the hypothesis is when it should have been .
A Type II Error occurs when the null hypothesis is accepted when it should have been rejected.
The researcher claims that the results are not significant when in fact they are (also known as a false negative).