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 postscores 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: Ho. HD =0 Hg: HD +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 degree of freedom - This is a test. From the table we find that the critical score(s) for the level of significance a - .01 is In order to calculate the test statistic t, you will need to calculate the estimated standard error first, which is v The calculated test statistic is therefore t=
Inverse Normal Distribution
The method used for finding the corresponding z-critical value in a normal distribution using the known probability is said to be an inverse normal distribution. The inverse normal distribution is a continuous probability distribution with a family of two parameters.
Mean, Median, Mode
It is a descriptive summary of a data set. It can be defined by using some of the measures. The central tendencies do not provide information regarding individual data from the dataset. However, they give a summary of the data set. The central tendency or measure of central tendency is a central or typical value for a probability distribution.
Z-Scores
A z-score is a unit of measurement used in statistics to describe the position of a raw score in terms of its distance from the mean, measured with reference to standard deviation from the mean. Z-scores are useful in statistics because they allow comparison between two scores that belong to different normal distributions.
![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 postscores 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:
Ho: HD = 0
%3D
Hg: HD +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 at-
distribution with degree of freedom =
This is a
test.
From the table we find that the critical score(s) for the level of significance a - .01 is
In order to calculate the test statistic t, you will need to calculate the estimated standard error first, which is
v The
calculated test statistic is therefore t =](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F3f31aa3f-c5fc-4e35-ab29-c3f7a99bd25c%2Fd679fefc-5702-4aea-bb0f-716888ea1a7a%2F5wfsovf_processed.png&w=3840&q=75)
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