Statistics Review: Interpretation and Application

Question 2: What are the different levels of data discussed in the module, and how are they distinguished?

Answer: The module discusses three levels of data: Nominal, Ordinal, and Interval/ratio2 .

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Nominal data is categorical, meaning it consists of labels or names with no inherent order (e.g., gender, race, political affiliation)2 .

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Ordinal data involves rank order, where categories have a meaningful sequence, but the distance between categories is unknown (e.g., rankings like private, corporal, sergeant, lieutenant or ratings like very poor, poor, fair, good, excellent)2 .

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Interval/ratio data also involves ordered categories, but crucially, the distance between categories is some accepted unit of measurement2 .

Question 3: What are the primary functions of descriptive statistics, and what are some of the terms associated with the language of statistics mentioned in the module?

Answer: The primary functions of descriptive statistics are to organize, summarize, and simplify data2 . The module also introduces some key terms in the language of statistics, including Dependent variable, Independent variable, Predictor variable, Univariate analysis, and Multivariate analysis2 . However, the module does not provide specific definitions for each of these terms.

Question 4: What are the common measures of central tendency and measures of dispersion discussed in the module?

Answer: The common measures of central tendency mentioned are the Mean, Median, and Mode3 . These are ways to describe the typical or central value of a dataset. The common measures of dispersion discussed are the Range, Standard deviation, and Variance3 . These measures describe the spread or variability of the data.

Question 5: Briefly explain the concept of the Normal Distribution as presented in the module.

Answer: The module briefly introduces the Normal Distribution visually, indicating that in a normal distribution, the Mean, Median, and Mode are all equal and located at the center of the distribution3 . It also shows the spread of the data in terms of Standard Deviations (SD) away from the mean, indicating areas containing approximately 1 SD and 2 SD on either side of the mean3 .

Question 6: What is the purpose of inferential statistics, and what does it involve?

Answer: The purpose of inferential statistics is to draw conclusions about a population from sample(s)3 . It also involves the process of testing the plausibility of hypotheses about a population, including tests of relationships and differences3 .

Question 7: Explain the process of hypothesis testing as outlined in the module, including the concept of the "null" hypothesis.

Answer: Hypothesis testing involves using a sample to decide whether a hypothesis is believable3 . A key part of this process is considering the "null" hypothesis3 . The goal is to use the data to decide whether to reject the null hypothesis (suggesting that maybe something happened or there is an effect) or to fail to reject the null hypothesis (suggesting that nothing apparent happened or there is no significant effect)4 . This decision is often based on a level of probability4 .

Question 8: What are some of the statistical tests mentioned in the module for examining differences between means and differences in proportions?

Answer: For examining differences between means, the module mentions the T-test and Analysis of variance (ANOVA), as well as Repeated measures ANOVA and ANCOVA4 . For examining differences in proportions, the module mentions the Chi-square test4 .

Question 9: What statistical methods are mentioned for examining relationships between/among variables, particularly linear relationships?

Answer: For examining if there is a relationship between/among variables, especially linear relationships, the module mentions Pearson Correlation, Regression, and Beta values4 .

Question 10: Describe the purpose and design of the study mentioned that evaluated the effectiveness of pulmonary rehabilitation for COPD patients.

Answer: The purpose of this study was to evaluate the effectiveness of a pulmonary rehabilitation to improve psychosocial adjustment to COPD and decrease use of Health care services4 . The study compared adjustment scores and use of HC services for 13 subjects who had not had a formal pulmonary rehab program (recruited from an internal medicine practice) and 17 subjects who had completed a formal rehab program (recruited from a pulmonology practice)4 .

Question 11: Describe the design of the study that evaluated a special intervention to decrease dietary fat intake, reduce smoking, and increase exercise in women after coronary artery bypass surgery.

Answer: In this study, 138 women who had coronary artery bypass surgery were randomly assigned into either a "special intervention" group or a "usual care" group5 . Risk factors and lifestyle behaviors were measured at baseline and 1 year after surgery5 .

Question 12: What was the research question or hypothesis being tested in the study about the effect of planned nursing instruction on patient's compliance with a self-medication regimen?

Answer: The hypothesis being tested in this study was that a higher proportion of subjects in the experimental group will be compliant than will subjects in the control group5 . Subjects were randomly assigned to either the experimental or control group5 . The data collected is presented in a table showing the number of compliant and noncompliant subjects in each group6 . A Chi-square test would likely be used to analyze this data to compare the proportions of compliant subjects in the two groups.

Question 13: What was the aim of the study involving the relationship between fruit ingested and energy level in high school athletes, and what statistical measure was used to assess this relationship?

Answer: The study aimed to determine if there was a relationship between the amount of fruit ingested and energy level in high school athletes6 . Both variables were measured using a scale, and the results section provides Pearson correlation coefficients (r) to indicate the strength and direction of the linear relationship, along with corresponding p-values6 . For example, it shows results like "r = .70, p = .04" and "r = .30, p = .10"6 .

Question 14: What statistical technique was used to examine the influence of multiple family, parent, child, and teacher characteristics on Teacher Rating of Performance? What does the R² value indicate in this context?

Answer: Multiple regression was used to examine the relationship between the various characteristic variables (family SES and child stress; parent attitude and expectations; child attitude, school self-concept, adaptive competency, externalizing behavior; and teacher expectations) and Teacher Rating of Performance7 . The results indicate that parent expectations, child adaptive competency, externalizing behavior, and teacher expectations accounted for a significant amount of the variance in Teacher Rating of Performance7 . The R² value of .599 means that these variables collectively accounted for 59.9% of the variance in Teacher Rating of Performance7 .

Question 15: What important note is included at the end of the module excerpt regarding a statistics assessment?

Answer: The wrap-up section of the module includes a note stating to disregard the audio statement about the Stats assessment being linked to the PowerPoint7 . It clarifies that a new quiz has been created in Canvas, and grades will be automatically provided after completion by the specified date in the course outline7 .