A Type II error occurs in hypothesis testing when the null hypothesis ($H_0$) is false, but it is not rejected. This is also known as a 'false negative'.
In this study:
Let's analyze each potential conclusion in the context of Type II error:
Based on the analysis, the scenario where the study concludes no relationship exists between video games and the teaching method, despite a real relationship actually existing, is the Type II error.
Therefore, the statement representing a Type II error is: Deciding the two types of video games are not related to play way method of teaching and they really are.
| LIST-I | LIST-II | |
| A. One-Tailed Test | I. | Null hypothesis is rejected if the sample value is significantly higher or lower than the hypothesized value of the population parameter |
| B. Paired difference Test | II. | A hypothesis test of the difference between the sample means of two independent samples |
| C. Two-Tailed Test | III. | A sample value significantly above the hypothesized population value will lead to rejection of the null hypothesis |
| D. Upper-Tailed Test | IV. | Concerned only with whether the observed value deviates from the hypothesized value in one direction |