A teacher administers an exam. The exam seemed relatively easy ...

[Medesa]

A teacher administers an exam. The exam seemed relatively easy for the students, and the majority of the scores are at the high end of the scale, although several students received low scores. In statistical terms this represents what?
 
  (Select all that apply.)
  a. Positive skew
  b. Negative skew
  c. Asymmetrical distribution
  d. Symmetrical distribution
  e. A normal curve
  f. A non-normal curve

Question 2

Which of the following are true about a type II error? (Select all that apply.)
 
  a. It is more likely to occur when p <.01 rather than when p <.05.
  b. It is extremely likely to occur when p <.001.
  c. It occurs when the null hypothesis is true but rejected.
  d. It is a possibility only when there are statistically nonsignificant results in a study.
  e. It is a possibility only when there are statistically significant results in a study.

[Meganchabluk]

Answer to Question 1

ANS: B, C, F
Any curve that is not symmetrical is referred to as skewed or asymmetrical. Skewness may be exhibited in the curve in a variety of ways. A curve may be positively skewed, which means that the largest portion of data is below the mean. A curve can also be negatively skewed, which means that the largest portion of data is above the mean. A normal curve is symmetric and has no skew.

Answer to Question 2

ANS: A, B, D
The probability of retaining the null hypothesis when it is in fact false is a type II error. In nursing research, beta is frequently set to 0.20, meaning that the researcher will allow for a 20 or lower chance of making a type II error, when the alpha is set at .05. If the alpha decreases (becomes more stringent) (.025, .01, and so forth), decreasing the possibility of type I error, the consequence is that the beta rises, making type II error much more likely. When a statistical test in a research study shows that a result is not statistically significant, the discerning reader will evaluate the sample size and the level of significance, in order to determine the possibility that a type II error occurred. It is not possible to decrease both types of error simultaneously without a corresponding increase in sample size.