Fill in the blank with the word that completes the sentence.
1. In an experiment, the independent variable is and its effect on the dependent variable is .
2. In a , participants are not randomly allocated to groups.
3. In an experiment, variables that are not controlled are known as variables.
4. When one group of participants thinks that they are receiving a treatment, but they are not, this is known as a .
5. Because of the high level of control, we can say with a high level of confidence that it was in fact the independent variable that affected the dependent variable. This means that experiments often have a high level of .
6. Because experiments have a procedure, they are replicable. This means that experiments potentially have a high level of .
7. An experiment can be to a target population if the participants have been allocated to conditions.
8. When there are two or more distinct groups, researchers are using an design. When there is one group of participants that experience both conditions of the experiment, the researchers are using a design.
9. When participants improve on a task because they have been asked to do it repeatedly, we can say that has taken place.
10. When carrying out a repeated measures design, one important control is to make sure that not all participants begin with the same condition. This is a control known as .
11. An experiment that is done so that neither the people who are doing the experiment nor the people who are the subjects of the experiment know which of the groups being studied is the control group and which is the test group is called a control.
12. The high level of control in experiments often means that the results may not be applied to behaviour outside of the laboratory; this means that the study has low .
13. When participants figure out what the researcher is looking for and tries to help out, this is known as .
14. When participants try to give the "right" answer or behave in a certain way in order to preserve or increase their self-image, this is known as .
15. If the calculation of inferential statistics is significant, we the null hypothesis. If the calcuations are not significant, we the null hypothesis.
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