Ch. 11 Research Design & Execution

Question 1

Positive controls

Answer 1

any control that ensures a change in dependent variable when it is expected.

e.g. in designing an assay to detect HIV, administering the test to a group of samples known to have HIV would constitute a positive control.

Question 2

Negative controls

Answer 2

any control that ensures no change in the dependent variable happens when no change is expected.

e.g. in designing an assay to detect HIV, administering the test to a group of samples known to NOT have HIV would constitute a negative control.

Question 3

What are two ways we can assess causality in a basic science research experiment?

Answer 3

1. utilizing controls (or standards) to demonstrate the outcome does NOT occur in the absence of the intervention
2. making sure the variables/results show an “if-then” relationship.

Question 4

Type I Error

Answer 4

The incorrect rejection of a true null hypothesis. Also known as a “false positive”

Question 5

Type II Error

Answer 5

The failure to reject a false null hypothesis. Also known as a “false negative”

Question 6

Accuracy

Answer 6

Also called validity, this is the ability of an instrument to measure a true value.

e.g. a person that weighs 170 should should get a reading of 170.

Alternatively, a scale that is accurate but imprecise would give a reading between 150 and 190 (in the middle of the two).

Question 7

Precision

Answer 7

Also called reliability, this is the ability of an instrument to read consistently, or within a narrow range.

e.g. a scale weighing a person that is 170 might show 130 every time would be precise but not accurate.

Question 8

Confounding variables

Answer 8

“third party” variables (often hidden or unobserved) that influence the dependent variable and are not the independent variables.