Chapter 11 Practice Questions

Which of the following describes the tails of the normal curve? A. All the above B. They are representative samples that may not belong to the same population. C. They are the extreme statistical values on the peripheral ends of the normal curve. D. They are defined by the level of significance selected by the researcher.

A. All the above Rationale: All the responses are correct

Which of the following is the purpose of exploratory data analysis? Select all that apply. A. Identify outliers B. Correct all errors C. Check the data for accuracy D. Obtain a better understanding of the data E. Determine the nature of variation in the data

A. Identify outliers D. Obtain a better understanding of the data E. Determine the nature of variation in the data Rationale: Analysis involves interpreting variations, outliers, and gaining understanding of the data. Checking for errors and accuracy are data-cleaning activities.

Which of the following is true of a one-tailed test of significance? A. Indicates that extreme scores on only one tail are considered significant B. Increases the risk of a type II error C. Is weaker than two-tailed tests D. Is referred to as no directional

A. Indicates that extreme scores on only one tail are considered significant Rationale: In a one-tailed test, the statistical procedure tests for differences in only one tail. Thus only extreme scores in that tail are considered significantly different.

Which of the following best explains power? A. It is the probability that a statistical test will detect a significant difference that exists. B. It is the capacity of the computer to run complex statistical analyses. C. It is the degree to which the null hypothesis is false. D. It is the amount of variance allowed in the measured scores.

A. It is the probability that a statistical test will detect a significant difference that exists. Rationale: Power is the capacity of a statistical analysis to identify real differences (or relationships) in the data. The variance for scores in a study is calculated with a mathematical equation and indicates the spread or dispersion of the scores. The standard deviation (SD) is the square root of the variance. Just as the mean is the average value, the SD is the average difference (deviation) value. Computation is a mechanical process usually performed by a computer. The Statistical Package for the Social Sciences (SPSS Statistic 20) is a software program for analyzing data and running statistical tests. The effect size is the degree to which the null hypothesis is false.

The risk of a type II error increases with which of the following? Select all that apply. A. Low levels of power B. Type I error C. Small effect sizes D. Small samples

A. Low levels of power C. Small effect sizes D. Small samples Rationale: Options A, C, D are type II errors

A researcher wants to conduct a study examining the relationship between gender and heart disease. Which of the following methods would be most appropriate? A. Analysis of variance (ANOVA) B. Chi-square C. Pearson's r D. Regression analysis

B. Chi-square Rationale: Chi-square is used to examine relationships between categorical data. Analysis of variance (ANOVA) is a parametric statistical technique used to examine differences among three or more groups. Pearson's r is a correlation coefficient designating the magnitude of relationship between two interval- or ratio-level variables. Regression analysis is used to predict the value of one variable when the value of one or more other variables is known.

During data cleaning, the researcher will perform which of the following? Select all that apply. A. Organize according to responses B. Correct all errors C. Identify missing data points and supply the data D. Sort according to demographics E. Check the data for accuracy

B. Correct all errors C. Identify missing data points and supply the data E. Check the data for accuracy Rationale: Data cleaning involves checking for accuracy, errors, or missing data. Organizing and sorting are components of analysis

In any study in which the data are numerical, data analysis begins with which of the following? A. Predictive statistics B. Descriptive statistics C. Hypothesis-testing statistics D. Correlational statistics

B. Descriptive statistics Rationale: All quantitative studies begins analysis with descriptive statisitcs

A researcher wanted to study the elements or variables associated with fear. Which of the following would be an appropriate statistical measure? A. Chi-square B. Factor analysis C. t-test D. Pearson's r

B. Factor analysis Rationale: Factor analysis is used to determine the relationships among large numbers of variables associated with a complex phenomenon. Chi-square test of independence examines the frequencies of observed values and compares them with the frequencies that would be expected if the data categories were independent of each other. Pearson's r is a correlation coefficient designating the magnitude of relationship between two interval- or ratio-level variables. The t-test is used to examine group differences when the variables are measured at the interval or ratio levels.

Which of the following does the normal curve indicate? A. Distribution of the values of a single sample B. Theoretical frequency distribution of all possible values in a population C. Real distribution of the values of a population D. Illustration of scores from several samples

B. Theoretical frequency distribution of all possible values in a population Rationale: The normal curve is a theoretical frequency distribution of all possible values in a population; however, no real distribution exactly fits the normal curve.

The researcher understands that exploratory analysis is used for all except which of the following? A. Become familiar with the data B. Examine measures of central tendency and dispersion for each variable C. Generalize to a larger population D. Identify outliers

C. Generalize to a larger population Rationale: Exploratory analysis is not used for this purpose. This requires confirmatory analysis using inferential statistics.

Using decision theory, if the level of significance was set at 0.05, which of the following probability levels from statistical analyses would indicate the greatest significant difference? A. 0.01 B. 0.001 C. None of the above D. 0.04

C. None of the above Rationale: According to decision theory, results are expressed dichotomously. Results are either significantly different or not significantly different. There are no "degrees" of significant difference.

When interpreting research outcomes, the type of results that agree with those predicted by the researcher and support the logical links developed by the researcher among the framework, purpose, study questions, hypotheses, variables, and measurement tools is known as? A. Unexpected results B. Nonsignificant results C. Significant results D. Significant and unpredicted results

C. Significant results Rationale: Significant results agree with those predicted by the researcher and support the logical links developed by the researcher among the framework, purpose, study questions, hypotheses, variables, and measurement tools. Nonsignificant (or inconclusive) results, often referred to as "negative" results, may be a true reflection of reality. In that case, the reasoning of the researcher or the theory used by the researcher to develop the hypothesis is in error. Significant and unpredicted results are the opposite of those predicted by the researcher and indicate that flaws are present in the logic of the researcher and theory being tested. Unexpected results usually are relationships found between variables that were not hypothesized and not predicted from the study framework.

A researcher wants to compare the results of two tests completed on the same group. Which of the following methods would be most appropriate? A. t-test B. Chi-square C. Z-score D. Analysis of variance

C. Z-score Rationale: Z-scores are used to standardize scores of different tests to make comparisons. Analysis of variance (ANOVA) is a parametric statistical technique used to examine differences among three or more groups. Chi-square is used to examine relationships between categorical data. The t-test is used to examine group differences when the variables are measured at the interval or ratio levels.

Which of the following describes the purpose of the Chi-square test of independence? A. Has a high risk of a type II error B. Is a very weak statistical test C. Determines whether two variables are independent or related D. All the above

D. All the above Rationale: All the options are correct

For what reason is it important to describe the sample? A. Determine if the sample is representative of the target population B. Allow readers to determine if the sample is similar to persons in their clinical setting C. Determine if groups being compared are equivalent D. All the above

D. All the above Rationale: These options are important reasons for describing the sample

Which of the following is not a characteristic of ANOVA? A. F statistic used to report results B. Tests for differences between means C. Often requires post hoc tests to identify locations of differences D. Can be used only with two groups

D. Can be used only with two groups Rationale: This is not a characteristic of analysis of variance (ANOVA). ANOVA can be used with three or more groups.

Which of the following is related to inference? A. Logical movement from a general truth to a specific instance B. Researcher's guess about the outcomes of the study C. Theoretical application of studying findings D. Conclusion or judgement based on evidence

D. Conclusion or judgement based on evidence Rationale: An inference is made from the study findings obtained from a specific sample and applied to a more general population using the results from statistical analyses.

Which of the following is not a descriptive statistic? A. Frequency distribution B. Mean C. Standard deviation D. Correlational analysis

D. Correlational analysis Rationale: Correlational analysis is not a descriptive statistic, but it is an inferential statistic. Inferential statistics are designed to address objectives, questions, and hypotheses in studies to allow inference from the study sample to the target population. Descriptive statistics are summary statistics that allow the researcher to organize data in ways that give meaning and facilitate insight. Frequency distribution describes the occurrence of scores or categories in a study. The mean is the sum of the scores divided by the number of scores being summed. Standard deviation is the square root of the variance.

Types of results from inferential statistical analyses include all except which of the following? A. Unpredicted B. Not significant C. Significant D. Findings

D. Findings Rationale: The researcher, not the statistical procedures, must reach findings.

What do measures of dispersion indicate? A. The central tendency of the sample B. Differences among samples C. Individual differences of the members of the sample D. Homogeneity, which indicates wider dispersion

D. Homogeneity, which indicates wider dispersion Rationale: Measures of central tendency, or variability, are measures of individual differences of the members of the sample.

The most common purpose of a Pearson's correlation is to examine which of the following? A. Relationships among groups. B. Differences between groups C. Differences between variables D. Relationships among variables

D. Relationships among variables Rationale: A Pearson's correlation usually examines relationships among variables.

To judge statistical suitability while critiquing a study, the nurse researcher needs to know all except which of the following? A. Level of measurement B. Whether the groups are dependent or independent C. Number of groups D. Reliability of the measures

D. Reliability of the measures Rationale: This information is not necessary to judge statistical suitability

For what purpose is the t-test used? A. To describe relationships between two variables B. To test the power of a statistical procedure C. To examine differences among three or more groups D. To test for a significant difference between the means of two samples

D. To test for a significant difference between the means of two samples Rationale: The t-test is used to test for a significant difference between the means of two samples. Correlational analyses are conducted to describe relationships between two variables. When differences are examined among three groups, post hoc analyses are conducted. Power is the probability that a statistical test will detect a significant difference that exists. The risk of a type II error can be determined using power analysis.

Which of the following leads to a type I error? A. When wrong statistical procedures are used B. When data are not measured at the interval level C. When results are not significant D. When results indicate a significant difference when there is no difference

D. When results indicate a significant difference when there is no difference Rationale: A type I error indicates a significant difference when there is no difference