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| Is used to examine all of the data descriptively |
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| Subjects or data points with extreme values (values that lie far from other plotted points on a graph) |
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| Used to confirm expectations regarding dara that are expressed as hypotheses, questions, or objectives. |
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| A deductive method used to explain the extent of a relationship, the probability that an event will occur in a given situation, or the probability that an event can accurately be predicted. |
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| An inductive theory that assumes that all of the groups in a study (e.g. experimental, control) used to test a particular hypothesis are components of the same population relative to the variables under study. |
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| Level of statistical significance |
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| The probability level at which the results of statistical analysis are judged to indicate a statistically significant difference between the groups. |
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| Level of statistical significance |
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| The probability level at which the results of statistical analysis are judged to indicate a statistically significant difference between the groups. |
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| A conclusion or judgement based on evidence. Statistical inferences are made cautiously and with great care. |
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| The application of information that has been acquired from a specific instance to a general situation. Generalization requires making an inference. Both require the use of inductive reasoning. |
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| The application of information that has been acquired from a specific instance to a general situation. Generalization requires making an inference. Both require the use of inductive reasoning. |
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| An expression of statistical thory. A theoretical frequency distribution of all possible values in a population; however, no real distribution exacly fits the normal curve. |
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| Two-tailed test of significance |
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| The analysis of a nondirectional hypothesis. |
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| one-tailed test of significance |
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| The hypothesis is directional, and extreme statistical values that occur on a single tail of the curve are of interest. |
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| Occurs when the null hypothesis is rejected when it is true (e.g. when the results indicate that there is a significant difference, when, in reality, there is not). |
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| Occurs when the null hypothesis is regarded as true, when it is, in fact, false. For example, a statistical analyses may indicate that no significant differences between groups, but in reality the groups are different. |
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| The probability that a statistical test will detect a significant difference that exists. The risk of a type II error can be determined by a power analysis. |
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| Four parameters of a power analysis |
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| The level of significance sample size, power, and effect size. |
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| The degree to which the phenomenon is present in the population, or the degree to which the null hypothesis is false. |
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| Ungrouped frequency distribution |
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| A table is develiped to display all numerical values obtained for a particular variable. |
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| Also called summary statistics. For some descriptive studies, researchers limit data analyses to descriptive statistics. |
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| Usually the first method used to organize the dara for examination. There are two types of frequency distribution. Grouped and ungrouped. |
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| Grouped frequency distributions |
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Definition
| Used when continuous variables, such as age, are being examined. Many measures are taken during datacollection. They are measured on a continuous scale. Any method of grouping results in loss of information. |
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| Indicates the percentage of subjects in a sample whose scores fall into a specific group and the number of scores in that group. |
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| Measure of central tendency |
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| Frequently referred to as an "average," which is a lay term not commonly used in statistics because it is vague. These are the most concise statements of the nature of the data. |
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| The numerical value or score that occurs with greatest frequency; does not necesarily indicate the center of the data set. |
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| The score at the exact center of the ungrouped frequency distribution-the 50th percentile. |
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| The most commonly used measure of central tendency. The sum of the scores divided by the number of scores being summed. May not be a member of the data set. |
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| The simplest measure of dispersion. |
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| Obtained by subtracting the lowest score from the highest score. |
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| Calculated with a mathematical equation. The numerical value obtained from the calculation depends on the measurement scale used. |
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| The square root of the variance. Just as the mean is the average value, this is the average difference (deviation) value. |
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| Numbers that make sense only within the framework of measurements used within a specific study are transformed into numbers (standardized scores) that have a more general meaning. |
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| Expresses deviations from the mean (difference scores) in terms of standard deviation units. |
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| Expresses deviations from the mean (difference scores) in terms of standard deviation units. |
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| Has two scales: horizontal and vertical. Each scale is referred to as an axis. The vertical scale is called the y axis; the horizontal scale is called the x axis. Can be used to illustrated the dispersion of values on a variable. |
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| Chi-square test of independence |
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Definition
| Determines whether two variables are independent; the test can be used with nominal or ordinal data. The procedures examines the frequencies of observed values and compares them with the frequencies that would be expected if the dara categories were independent of each other. |
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| Pearson product-moment correlation |
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Definition
| A parametric test used to determine relationships among variables. |
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| Measures the extent of relationship between two variables. Data are collected from a single sample, and measures of the two variables to be examined must be available for each subject in the data set. |
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| Means that the analysis gives no indication of the direction of the relationship. |
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| A high score on one variable is correlated with a low score on the other variable. |
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| A high score on one variable is correlated with a high score on one variable is correlated with a high score on the other variable. |
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| Some of the variation in values is explained by the relationship between the two variables. The amount of explained varience is indicated by r2 and is expressed as a percentage. |
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| Part of the variation is the result of things other than the relationship. |
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| Examines the interrelationships among large numbers of variables and disentangles those relationships to identify clusters of variables that are most closely linked. |
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| Closely related variables are grouped together into these. |
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| Used to predict the value of one variable when the value of one or more other variables is known. |
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| The variable to be predicted in a regression analysis. |
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| If there is more than one independent variable, the analysis is referred to as. . . |
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| Purpose of regression analysis is to develop this. . .it will best reflect the values on a scatterplot. |
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| Coefficient of multiple determination |
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Definition
| When more than one independent variable is being used to predict values of the dependent variable, r2 is sometimes referred to as this. . . |
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| one of the most common analyses used to test for significant differences between two samples. |
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| Analysis of variance (ANOVA) |
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Definition
| Tests for differences between means. More flexible than other analyses, ecause it can be used to examine data from two or more groups. |
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| Individual scores in the group with vary from the group mean. This is called what? |
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| Variation of the group means around the grand mean, reffered to as this. . . |
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| Within-group variance and between-group variance combined. |
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| The test for ANOVA is always? |
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| Analysis of covariance (ANCOVA) |
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| Allows the researcher to examine the effect of a treatment apart from the effect if one or more potentially confounding variables. |
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Definition
| The selection of one subject is totally unrelated to the selction of other subjects. |
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| Subjects or observations selected for data collection are related in some way to the selection of other subjects or observations. |
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| These results agree with those predicted by the researcher and support the logical links developed by the researcher between the framework, questions, variables, and measurement tools. |
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| Inconclusive, often referred to as "negative" results, may be a true reflection of reality. In that case, the reasoning of the researcher or the thort used by the researcher to develop the hypothe sis is in error. |
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| Significant and unpredicted results |
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Definition
| The opposite of those predicted by the researcher and indicate that flaws are present in the logic of both the researcher and the thory being tested. If the results are valid, however, they constitute an important addition to the body of knowledge. |
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| Probably the most common outcome of studies. One variable may uphold predicted characteristics whereas another does not; or two dependent measures of the same variable may show opposite results. |
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| Usually are relationships found between variables that were not hypothesized and not predicted from the framework being used. |
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| A synthesis of the findings. The researcher uses logical reasoning, creates a meaningful whole from pieces of information obtained through data analysis and findings from previous studies, remains receptive to subtle clues in the data and considers alternative explanations of the data. |
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| Results are translated and interpreted. Consequence of evaluating evidence. |
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| Meanings of conclusions from scientific research for the body of nursing knowledge, theory, and practice. Based on conclusion, but are more specific, and they provide suggestions for implementing the findings. |
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| Related to the practical importance of the findings. There is no common agreement in nursing about how to evaluate the findings for this. |
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| Empirical generalizations |
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| BAsed on accumulated evidence from many studies and are important for the verification of theoretical statements or the development of a new theory. |
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| Often linked to "criticize" a term that is often viewed as negative. |
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| Intellectual research critique |
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| A careful, complete, examination of a study to judge its strengts, weaknesses, logical links, meaning, and significance. |
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| What does a high-quality study focus on? |
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| A significant problem, demonstrating sound methodology, producing credible findings, and providing a basis for additional studies conducted by other researchers. |
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| The first step in the research critique process. Involves understanding the terms and concepts in the report and identifying the elements or steps of the research process, such as the problem, purpose, etc. |
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| Requires knowledge of what each step of the research process should be like, and then the ideal is compared to the real. |
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| Involves a critique of the logical links connecting one study element with another. |
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| During this phase of a research critique, the meaning and significance of the study findings are examined. |
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| The study purpose, significance, and interpretations must be articulated in such detail and richness that the reader has the sense of personally experiencing the event and clearly understanding the significance of the findings. |
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| Methodological congruence |
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| Requires knowledge of the methodological approach the researcher used and whether that approach was consistent with the philosophical basis of the study. |
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Definition
| A fourth dimension of methodological congruence is the rigorous development of a decision trail. |
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| Failure of the researcher to record the nature of the decisions made, the data on which they were based, and the decision trail and rules for arriving at conclusions. Other researchers with a similar background and philosohical background are not able to arrive at similar conclusions after applying the decision rules to the data. |
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| Failure to include enough participant quites to support the findings. The interpretative statements developed to not correspond with the findings. |
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| Failure to provide quotes that are sufficiently rich or detailed to allow judgements to be made. This flaw also has been described as not achieving saturation or redundency in the data. |
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| Failure to provide specific examples of the phenomenon being investigated. |
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| Analytical and interpretative preciseness |
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| Requires that the researcher involve others in the interpretative proces and present a meaningful picture of the phenimenon. |
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| Philosophical and theoretical correctness |
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| Requires that the findings developed from the study be clearly expressed, logically consistent, and compatible with the knowledge base of nursing. |
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| This value is reflected in the reader's ability to recognize the phenomenon described in the study, its applicability to nursing practice, and its influence on future research. Includes intuitive recognition, relationship to the existing body of knowledge, and applicability. |
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| Is decision theory inductive or deductive? |
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| What type of reasoning does probability theory use? |
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