Question

Previous studies have shown that playing video games can increase visual perception abilities on tasks presented in the gaming zone of the screen (within 5 degrees of the center). A graduate student is interested in whether playing video games increases peripheral visual perception abilities or decreases attention to peripheral regions because of focus on the gaming zone. For her study, she selects a random sample of 64 adults. The subjects complete a difficult spatial perception task to determine baseline levels of their abilities. After playing an action video game (a first-person combat simulation) for 1 hour a day over 10 days, they complete the difficult perception task for a second time.

Before playing the action video game, the mean score in their accuracy on the spatial task was 0.42. After playing the action video game, the mean score was -0.08. The mean of the differences between each person’s pre- and post- scores was 0.5, with a standard deviation of the differences equal to 2.4.

The graduate student has no presupposed assumptions about whether playing video games increases peripheral visual perception abilities or decreases attention to peripheral regions because of focus on the gaming zone, so she formulates the null and alternative hypotheses as:

	H₀: μDD = 0
	H₁: μDD ≠ 0

She uses a repeated-measures t test. Because the sample size is large, if the null hypothesis is true as an equality, the test statistic follows a t-distribution with n – 1 = 64 – 1 = 63 degrees of freedom.

This is a one or two tailed test?

The critical score(s) (the value(s) for t that separate(s) the tail(s) from the main body of the distribution, forming the critical region) is/are ( ) ?   

To calculate the test statistic, you first need to calculate the estimated standard error under the assumption that the null hypothesis is true. The estimated standard error is (    ) ?

The test statistic is t = ( )?

The t statistic lies or does not lie in the critical region for a two-tailed hypothesis test?

Therefore, the null hypothesis is rejected or not rejected?

The graduate student can or can not conclude that playing video games alters peripheral visual perception?

The graduate student repeats her study with another random sample of the same size. This time, instead of the treatment being playing the combat simulation video game, the treatment is playing a soccer video game. Suppose the results are very similar. After playing a soccer video game, the mean score was still 0.5 lower, but this time the standard deviation of the difference was 1.8 (vs. the original standard deviation of 2.4). This means..... playing a soccer video game OR playing the combat simulation game has the more consistent treatment effect?

This difference in the standard deviation also means that a 95% confidence interval of the mean difference would be narrower or wider for the original study, when the treatment was playing the combat simulation video game, than the 95% confidence interval of the mean difference for the second study, when the treatment was playing a soccer video game.

Finally, this difference in the standard deviation means that when the graduate student conducts a hypothesis test testing whether the mean difference is zero for the second study, she will be more or less likely to reject the null hypothesis than she was for the hypothesis test you completed previously for the original study?

Answer 1