7.40 Much has been made of the concept of experimenter bias, which refers to the fact that even the most conscientious experimenters tend to collect data that come out in the desired direction (they see what they want to see). Suppose we use students as experimenters. All the experi- menters are told that subjects will be given caffeine before the experiment, but one-half of the experimenters are told that we expect caffeine to lead to good performance and one-half are told that we expect it to lead to poor performance. The dependent variable is the number of simple arithmetic problems the subjects can solve in 2 minutes. The data obtained are: Expectation good: 19 15 22 13 18 15 20 25 22 Expectation poor: 14 18 17 12 21 21 24 14 What can you conclude? 7.41 Calculate 95% confidence limits on m1 – m2 and d for the data in Exercise 7.40.

7.40 Much has been made of the concept of experimenter bias, which refers to the fact that even the most conscientious experimenters tend to collect data that come out in the desired direction (they...

7.40 Much has been made of the concept of experimenter bias, which refers to the fact that even the most conscientious experimenters tend to collect data that come out in the desired direction (they see what they want to see). Suppose we use students as experimenters. All the experi- menters are told that subjects will be given caffeine before the experiment, but one-half of the experimenters are told that we expect caffeine to lead to good performance and one-half are told that we expect it to lead to poor performance. The dependent variable is the number of simple arithmetic problems the subjects can solve in 2 minutes. The data obtained are:

Expectation good: 19 15 22 13 18 15 20 25 22

Expectation poor: 14 18 17 12 21 21 24 14

What can you conclude?

7.41 Calculate 95% confidence limits on m1 – m2 and d for the data in Exercise 7.40.

Jun 08, 2022