Question 1

A sample is a subset of the population.

Accepted Answer

A sample is indeed a subset of the population, selected to represent the population in a study or analysis.

Question 2

The median is preferred to the mean when there are a few extreme scores.

Accepted Answer

The median is less affected by extreme scores or outliers than the mean, making it a more representative measure of central tendency in such cases.

Question 3

A type 2 error occurs when we falsely reject the null hypothesis when it is actually false.

Accepted Answer

A type 2 error occurs when we fail to reject the null hypothesis when it is actually false, not when we falsely reject it.

Question 4

If the mean score is 200 and the standard deviation is 50,then a score of 50 is one standard deviation below the mean.

Accepted Answer

A score of 50 is three standard deviations below the mean, since the mean is 200 and the standard deviation is 50 (200 - 50 = 150 for one standard deviation, 200 - 3*50 = 50 for three standard deviations).

Question 5

In a multifactor analysis of variance,how the variables affect one another is called:
A) main effects
B) interaction effects
C) experimental effects
D) variance effects
E) a type II error

Accepted Answer

Interaction effects describe how variables in a multifactor analysis of variance affect one another, indicating how the effect of one factor depends on the level of another factor.

Question 6

Statistical power increases with sample size.

Accepted Answer

Statistical power, which is the probability of correctly rejecting a false null hypothesis, increases as the sample size increases because larger samples provide more information about the population, reducing the standard error and making it easier to detect a true effect if one exists.

Question 7

The power of a statistical test determines how likely it is that the null hypothesis will be rejected.

Accepted Answer

The power of a statistical test is the probability that it correctly rejects a false null hypothesis, meaning it measures the test's ability to detect an effect if there is one.

Question 8

A one-tailed p value is always bigger than a two-tailed p.

Accepted Answer

A one-tailed p-value is not always bigger than a two-tailed p-value; it is typically half the size of a two-tailed p-value if the test statistic falls in the direction specified by the one-tailed test, assuming the test statistic distribution is symmetric.

Question 9

In a histogram,frequency of scores is on the abscissa.

Accepted Answer

In a histogram, the frequency of scores is typically represented on the ordinate (y-axis), while the variable or score categories are represented on the abscissa (x-axis).

Question 10

If an obtained score has a z-value of two or greater,then this score is greater than about 95% of all scores.

Accepted Answer

A z-score of 2 or greater indicates that the score is at least 2 standard deviations above the mean, which corresponds to being greater than approximately 95% of all scores in a normally distributed dataset.

Question 11

Statistical tests that increase type 1 errors tend to decrease type 2 errors.

Accepted Answer

Increasing the likelihood of a Type 1 error (falsely rejecting the null hypothesis when it is true) generally involves using a higher significance level, which makes the test more sensitive to detecting an effect if there is one, thus decreasing the likelihood of a Type 2 error (failing to reject the null hypothesis when it is false).

Question 12

In a normal distribution,the mean,median,and mode have the same value.

Accepted Answer

In a normal distribution, it is symmetric about the mean, which means the mean, median, and mode are all located at the same point on the distribution curve.

Question 13

A type 1 error is rejection of the null hypothesis when it is actually false.

Accepted Answer

A type 1 error occurs when the null hypothesis is rejected even though it is actually true.

Question 14

About 68% of all scores lie between -2 and +2 standard deviations in a normal distribution.

Accepted Answer

Approximately 95% of all scores lie between -2 and +2 standard deviations in a normal distribution.

Question 15

The Greek letter sigma ($\sigma$)stands for the sample standard deviation.

Accepted Answer

The Greek letter sigma (σ) stands for the population standard deviation, not the sample standard deviation. The sample standard deviation is usually denoted by "s".

Question 16

The standard error of the mean decreases as sample size increases.

Accepted Answer

The standard error of the mean decreases as the sample size increases because it is inversely proportional to the square root of the sample size, leading to more precise estimates of the population mean.

Question 17

The null hypothesis can be rejected if the alpha value is less than or equal to .05.

Accepted Answer

The null hypothesis can be rejected if the p-value is less than or equal to the alpha level (commonly set at .05), indicating that the observed data would be highly unlikely under the null hypothesis.

Question 18

Parametric statistical tests assume that the level of measurement is at least an interval scale.

Accepted Answer

Parametric statistical tests assume that data are measured on an interval scale or a ratio scale, which are both considered higher levels of measurement that allow for the use of arithmetic operations.

Question 19

A z-score of +1 is one standard deviation above the mean.

Accepted Answer

A z-score of +1 indicates a value that is one standard deviation above the mean in a normal distribution.

Question 20

The standard deviation is the sum of the squared deviations from the mean,divided by the number of scores.

Accepted Answer

The standard deviation is the square root of the variance, which is the sum of the squared deviations from the mean divided by the number of scores (for a population) or by the number of scores minus one (for a sample).

Quiz 15: Appendices a and B Descriptive and Inferential Statistics

A sample is a subset of the population.

The median is preferred to the mean when there are a few extreme scores.

A type 2 error occurs when we falsely reject the null hypothesis when it is actually false.

If the mean score is 200 and the standard deviation is 50,then a score of 50 is one standard deviation below the mean.

In a multifactor analysis of variance,how the variables affect one another is called:

Statistical power increases with sample size.

The power of a statistical test determines how likely it is that the null hypothesis will be rejected.

A one-tailed p value is always bigger than a two-tailed p.

In a histogram,frequency of scores is on the abscissa.

If an obtained score has a z-value of two or greater,then this score is greater than about 95% of all scores.

Statistical tests that increase type 1 errors tend to decrease type 2 errors.

In a normal distribution,the mean,median,and mode have the same value.

A type 1 error is rejection of the null hypothesis when it is actually false.

About 68% of all scores lie between -2 and +2 standard deviations in a normal distribution.

The Greek letter sigma ( $\sigma$ )stands for the sample standard deviation.

The standard error of the mean decreases as sample size increases.

The null hypothesis can be rejected if the alpha value is less than or equal to .05.

Parametric statistical tests assume that the level of measurement is at least an interval scale.

A z-score of +1 is one standard deviation above the mean.

The standard deviation is the sum of the squared deviations from the mean,divided by the number of scores.

Quiz 15: Appendices a and B Descriptive and Inferential Statistics

A sample is a subset of the population.

The median is preferred to the mean when there are a few extreme scores.

A type 2 error occurs when we falsely reject the null hypothesis when it is actually false.

If the mean score is 200 and the standard deviation is 50,then a score of 50 is one standard deviation below the mean.

In a multifactor analysis of variance,how the variables affect one another is called:

Statistical power increases with sample size.

The power of a statistical test determines how likely it is that the null hypothesis will be rejected.

A one-tailed p value is always bigger than a two-tailed p.

In a histogram,frequency of scores is on the abscissa.

If an obtained score has a z-value of two or greater,then this score is greater than about 95% of all scores.

Statistical tests that increase type 1 errors tend to decrease type 2 errors.

In a normal distribution,the mean,median,and mode have the same value.

A type 1 error is rejection of the null hypothesis when it is actually false.

About 68% of all scores lie between -2 and +2 standard deviations in a normal distribution.

The Greek letter sigma ( σ\sigmaσ )stands for the sample standard deviation.

The standard error of the mean decreases as sample size increases.

The null hypothesis can be rejected if the alpha value is less than or equal to .05.

Parametric statistical tests assume that the level of measurement is at least an interval scale.

A z-score of +1 is one standard deviation above the mean.

The standard deviation is the sum of the squared deviations from the mean,divided by the number of scores.

The Greek letter sigma ( $\sigma$ )stands for the sample standard deviation.