Question 1

A researcher reports that results of a study were not statistically significant. How is this to be interpreted?

Accepted Answer

If the results of the study are not statistically significant, the researcher was unable to show there was a mathematical difference between the groups. The null hypothesis, which states there is no difference between groups, would therefore be supported. The null hypothesis cannot be rejected in this case.
Although it may be True that the intervention was not strong enough to make a difference, it does not relate to the statistical significance.
It may be True that the researcher's logic or conceptualization in setting up the study was faulty, but cannot be read into the statement regarding statistical significance.
The topic may still be a very worthwhile area of study. The lack of statistically significant results does not mean that the topic is not a clinically significant topic.

Question 2

There is a greater risk of making which error with a directional hypothesis?

Accepted Answer

In a one-tailed test of significance, the hypothesis is directional. One-tailed statistical tests are uniformly more powerful than two-tailed tests, decreasing the possibility of a Type II error (saying there is no difference when there really is). This means the likelihood of a Type I error (saying there is a difference when there really is not) increases.
Concluding that there is no difference between groups when there is an inverse relationship is a Type II error.
Concluding that there is no difference between groups when there is an inverse relationship describes a Type II error.
Rejecting the null hypothesis when the measurement error is moderate would be True of both directional and nondirectional hypotheses.

Question 3

Level of significance, sample size, power, and effect size are the four components of:

Accepted Answer

Cohen identified four parameters of a power analysis: the level of significance, sample size, power, and effect size.
The four components do not constitute decision theory.
Exploratory analysis is a preliminary step in the analysis of data.
Inference is the conclusion or judgment based on evidence.

Question 4

Under what condition would the mean, median, and mode be equal?

Accepted Answer

In the normal curve, the mode, median, and mean are equal.
Equal range and standard deviation would not mean that the mode, median, and mean are equal. In the normal curve, the mode, median, and mean are equal.
With a multimodal distribution, the mean, median, and mode would not be equal. In the
normal curve, the mode, median, and mean are equal.
A small variance would not mean that the mode, median, and mean are equal. In the normal curve, the mode, median, and mean are equal.

Question 5

What proportion of the standardized scores of a sample lies between the Z-scores of -1.96 and +1.96?

Accepted Answer

Z-scores are a common standardized score used to express deviations from the mean in terms of standard deviation units. Figure 12-1 demonstrates that standardized scores lying between the Z-score of -1.96 and +1.96 are distributed over 95.5% of the normal curve.
34.0% of cases will be 1 score above or below the mean.
Approximately 47.7% of cases will be 1.96 above OR below the mean.
68.3% of cases will lie between the Z-scores of -1.0 and +1.0.

Question 6

A Type I error could occur for which of the following reasons?

Accepted Answer

There is a greater risk of Type I error with a 0.05 level of significance than with a 0.01 level of significance. As the level of significance becomes more extreme, the risk of a Type I error decreases.
The greater the difference between groups the less likelihood of a Type I error.
A Type I error is probably less likely with a large sample.
Normal distribution is not going to cause a Type I error.

Question 7

Which of the following interpretations is acceptable as worded?

Accepted Answer

Researchers can never prove things using inferential reasoning; they can never be certain their reasoning is correct. Correlations do not indicate causality; they simply express a relationship. Because of the limitations of research and the diversity of humans, the ability to generalize findings to "all" members of a population is not possible.
Findings can never be applied to all humans.
Correlation does not equate with causation.
The study cannot prove that something is the case; it can only support the likelihood.

Question 8

Which of the following is true about Type I errors?

Accepted Answer

With a Type I error, study results indicate there is a significant difference, when in reality there is not.
Researchers should always be concerned with both Type I and Type II errors. With a Type I error, study results indicate there is a significant difference, when in reality there is not.
A Type I error is less likely to happen with smaller and smaller levels of significance. With a Type I error, study results indicate there is a significant difference, when in reality there is not. C. With a Type I error, study results indicate there is a significant difference, when in reality there is not.

Question 9

The mean is represented by which score in the following frequency distribution?

Accepted Answer

The mean is the sum of the scores divided by the number of scores being summed. In this example, the sum of scores equals 70, and the number of scores being summed equals 7. Seventy divided by 7 equals 10.

Question 10

The likelihood that a statistical value obtained through analysis of the data is likely to occur in any two samples selected from the same population is called:

Accepted Answer

Probability is used to explain the extent of a relationship, the probability of an event occurring in a given situation, or the probability of accurately predicting an event.
Degrees of freedom is the freedom of a score's value to vary given the existing situation.
Induction is a type of reasoning.
Interval estimation is the researcher's best guess as to the range of scores for the study population.

Question 11

In the following frequency distribution of data, the score 12 is which measure of central tendency?

Accepted Answer

The mode is the numerical value or score that occurs with greatest frequency. In this example, the score 12 occurs three times in the data set.
Frequency is how many times a certain score is recorded in the data. The mode is the numerical value or score that occurs with greatest frequency.
The mean is the sum of the scores divided by the number of scores being summed. The mode is the numerical value or score that occurs with greatest frequency.
The median is the score at the exact center of the ungrouped frequency distribution. The mode is the numerical value or score that occurs with greatest frequency.

Question 12

The level of significance usually set in nursing studies is at either:

Accepted Answer

The level of significance selected for most nursing studies is .05. In some studies, the more rigorous level of significance of .01 may be chosen. .5 or .1 values are too high. The level of significance selected for most nursing studies is .05. In some studies, the more rigorous level of significance of .01 may be chosen.
.03 or .003 values are not generally accepted levels of significance. The level of significance selected for most nursing studies is .05. In some studies, the more rigorous level of significance of .01 may be chosen.
.005 or .001 values would be too rigorous. The level of significance selected for most nursing studies is .05. In some studies, the more rigorous level of significance of .01 may be chosen.

Question 13

Descriptive statistics should be reported in every study to:

Accepted Answer

The researcher needs to obtain as complete a picture of the sample as possible.
Frequencies of descriptive variables related to the sample are usually obtained first.
Validity is not determined by descriptive statistics.
Descriptive statistics would not indicate reliability.
Descriptive statistics are not "powerful analysis" measures.

Question 14

A researcher notes that 3 of 30 subjects had extreme anxiety scores when compared with the other subjects. These three subjects would be treated as:

Accepted Answer

Subjects with extreme values that seem unlike the rest of the sample are called outliers.
Deviants and outliers are not the same.
Unexpected findings can occur with or without outliers.
Subjects can be grouped into categories or not, the process may highlight outliers, but would not define them.

Question 15

Which of the following questions relates to generalization?

Accepted Answer

Generalization is the application of information to a general situation (in this case other groups or settings) that has been acquired from a specific instance (research study).
The issue of significance is determined differently than generalizability.
Control relates to the research methodology.
This question has to do with controls involved in the study and the methodology that was used.

Question 16

Results of an ANOVA analysis of three specialty nursing groups indicate there is a significant difference between groups on the practice of spiritual care. To determine where the difference occurs, the researcher would need to run which statistical analyses?

Accepted Answer

Some statistical analyses, such as chi-square and analyses of variance (ANOVA), are used to test for differences among groups in studies including more than two groups. These tests do not indicate which groups are different. Post hoc analyses are used to identify the specific groups that are different.
Confirmatory analysis is performed to confirm expectations regarding the data.
Predictive research seeks to forecast situations in the future based on current knowledge.
Relational analysis determines a connection between the variables.

Question 17

Type I errors are more likely to occur when the level of significance is less than:

Accepted Answer

There is a greater risk of a Type I error with a 0.05 level of significance than with a 0.01 level of significance.
There is a greater risk of a Type I error with a 0.05 level of significance than with a 0.01 level of significance.
This level of significance is more extreme than 0.01. There is a greater risk of a Type I error with a .05 level of significance than with a 0.01 level of significance.
There is a greater risk of a Type I error with a 0.05 level of significance than with a 0.01 level of significance.

Question 18

A statistically significant finding means that:

Accepted Answer

Statistical significance indicates the likelihood that results of a statistical analysis are real and not a result of chance. The calculated probability from the statistical analysis is compared with alpha to determine whether findings are statistically (mathematically) significant or not.
Statistical significance does not necessarily mean clinically significant. Statistical significance indicates the likelihood that results of a statistical analysis are real and not a result of chance.
Clinicians must evaluate findings for relevance to their own practice.
There is no guarantee that results will be the same from one study to the next, especially if it is early in the exploration of the topic.

Question 19

Which of the following levels of significance would decrease the chance of a Type II error?

Accepted Answer

There is a greater risk of Type II error with more extreme levels of significance and less of a risk with more conservative levels of significance.
There would be less chance of a Type II error with 0.05 than with 0.01 or 0.001, but 0.10 is even more liberal. There is a greater risk of Type II error with more extreme levels of significance and less of a risk with more conservative levels of significance.
There would be less chance of a Type II error with 0.01 than with 0.001, but 0.10 is even more liberal. There is a greater risk of Type II error with more extreme levels of significance and less of a risk with more conservative levels of significance.
This is the most restrictive answer and therefore the greatest risk of a Type II error. There is a greater risk of Type II error with more extreme levels of significance and less of a risk with more conservative levels of significance.

Question 20

Which of the following is true about the level of significance? The level of significance:

Accepted Answer

A Type I error occurs when the null hypothesis is rejected, though it is actually True. The level of significance is the cutoff point selected by the researcher before data collection that indicates the probability of a True significant difference between groups.
It is the likelihood of correct findings, but cannot ensure that they actually are correct.
A "p value" is calculated by the computer, but this is compared to the level of significance determined acceptable by the researcher.
It actually has to do with making a Type I error. A Type I error occurs when the null hypothesis is rejected, though it is actually True.

Quiz 11: Understanding Statistics in Research