Question 1

Without some correction,the percentage of agreement between two observers will tend to overestimate the true level of inter-rater reliability.

Accepted Answer

This statement is true because without correction, chance agreement between observers is included in the calculation of inter-rater reliability, leading to an overestimation of agreement.

Question 2

In general,a sample with large variance is more likely to produce a significant result than a sample with small variance.

Accepted Answer

A large variance in a sample often indicates more spread in the data, which can make it harder to detect a true effect or difference, thus potentially reducing the likelihood of finding a significant result.

Question 3

One concern with measuring split-half reliability is that many different correlations are possible depending on how you decide to split the test items in half.

Accepted Answer

This is true. Depending on how the test items are split in half, different correlations can result which may impact the overall reliability estimate. Therefore, it's important to consider alternative methods of testing reliability such as Cronbach's alpha, which does not rely on splitting the test items in half.

Question 4

The goal of a hypothesis test is to demonstrate that the patterns observed in the sample data represent real patterns in the population and are not simply due to chance or sampling error.

Accepted Answer

The goal of hypothesis testing is indeed to determine if the patterns observed in a sample are truly representative of the population and not just due to chance or sampling variability.

Question 5

The goal of descriptive statistics is to simplify,summarize,and organize data.

Accepted Answer

Descriptive statistics involves methods of organizing, summarizing and presenting data in a meaningful way.

Question 6

The mode is the best way to measure central tendency for data from a nominal scale of measurement.

Accepted Answer

The mode is the most frequently occurring value in a data set and is appropriate for nominal data where values cannot be ordered or ranked. Mean and median are not appropriate for nominal data.

Question 7

A Type I error means that the hypothesis test has failed to detect a real treatment effect.

Accepted Answer

A Type I error means that the hypothesis test has falsely rejected a true null hypothesis and concluded that there is a treatment effect when there really isn't one. Therefore, it does not mean that the hypothesis test has failed to detect a real treatment effect.

Question 8

A distribution of scores and a mean of 55 and a standard deviation of 4.The variance for this distribution is 16.

Accepted Answer

The variance of a distribution is equal to the square of the standard deviation. Therefore, if the standard deviation is 4, the variance is 16.

Question 9

It is always possible that patterns observed in sample data do not accurately represent patterns in the population.

Accepted Answer

This is due to the fact that sample data is just a small representation of the entire population and there could be variability and sampling error. Therefore, we always have to be cautious when generalizing findings from sample data to the entire population.

Question 10

The median is the most commonly used measure of central tendency.

Accepted Answer

The mean is actually the most commonly used measure of central tendency. The median is often used as an alternative when the data is skewed or has outliers.

Question 11

In a distribution with a mean of M = 76 and a standard deviation of SD = 7,a score of 91 would be considered an extreme value.

Accepted Answer

An extreme value in a normal distribution is typically defined as a score that falls beyond two standard deviations from the mean. In this case, two standard deviations above the mean would be 90 (76 + 2*7), so a score of 91 would be considered an extreme value.

Question 12

Cohen's kappa is used to correct for chance agreements when computing inter-rater reliability.

Accepted Answer

This is a correct statement. Cohen's kappa is a statistical measure used to calculate inter-rater reliability while controlling for chance agreements between two or more raters.

Question 13

A summary value,usually numerical,that describes a sample is called a parameter.

Accepted Answer

A parameter describes a population, not a sample. A summary value that describes a sample is called a statistic.

Question 14

A researcher records the average age for a group of 25 preschool children selected to participate in a research study.The average age is an example of a statistic.

Accepted Answer

Since the researcher is calculating the average age for a specific group of children, the resulting value is a statistic.

Question 15

Without some correction,such as the Spearman-Brown formula,a correlation measuring split-half reliability will tend to overestimate the reliability for the full test.

Accepted Answer

The Spearman-Brown formula is used to correct for the underestimation of reliability when using split-half methods, by predicting the reliability of the full test based on the split-half reliability.

Question 16

A negative correlation means that as the X values decrease,the Y values also tend to decrease.

Accepted Answer

A negative correlation means that as the X values increase, the Y values tend to decrease, and vice versa.

Question 17

In a distribution with a mean of M = 36 and a standard deviation of SD = 8,a score of 40 would be considered an extreme value.

Accepted Answer

A score of 40 is just 1 standard deviation above the mean, which is not considered extreme. Extreme values would be those that are more than 2 or 3 standard deviations from the mean.

Question 18

A researcher reports a significant correlation using an alpha level of .01.The probability that the researcher is making a Type I error is p < .01.

Accepted Answer

The answer of A researcher reports a significant correlation using...

Question 19

When a research report demonstrates a significant treatment effect at the .05 level,you can be more confident that the effect is real than if the researcher had reported a significant effect with an alpha level of only .01.

Accepted Answer

A significant effect at the .01 level indicates a stronger level of statistical significance compared to the .05 level, meaning there is a lower probability that the observed effect is due to chance, thus increasing confidence in the reality of the effect.

Question 20

In general,a correlation obtained from a large sample is more likely to be significant than a correlation obtained from a small sample.

Accepted Answer

This is true because a larger sample size reduces the chance of obtaining a correlation by chance or random error, resulting in a more accurate estimate of the true correlation in the population.

Quiz 15: Statistical Evaluation of Data