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N580 Final Exam 2025/2026 – 90 Verified Questions & Answers | Statistics, Hypothesis Testing, Regression, ANOVA, t-tests

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This comprehensive exam prep document includes 90 expertly verified questions and answers for the N580 Final Exam (Advanced Nursing Research) for the 2025/2026 academic year. It covers essential topics such as parametric vs. non-parametric tests, inferential and descriptive statistics, levels of measurement, correlation, regression, t-tests, and ANOVA. This resource is ideal for MSN, BSN, DNP, and healthcare research students, as well as those enrolled in evidence-based practice, nursing informatics, and biostatistics courses. It is especially useful for students preparing for cumulative exams, research-intensive coursework, or advanced practice nursing certifications. Keywords: nursing research, inferential statistics, descriptive statistics, hypothesis testing, parametric tests, non-parametric tests, regression, ANOVA, t-test, correlation, levels of measurement, effect size, confidence interval, standard deviation, sampling error, chi-square test, research methods, quantitative analysis, RANOVA

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N580 Final 2025/2026 Exam Questions
and Verified Answers | Already Graded
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statistics vs. parameters - 🧠 ANSWER ✔✔analysis on a sample vs. analysis on the

entire population


overview to data analysis - 🧠 ANSWER ✔✔quantitative: descriptive and

inferential

descriptive: simply describe a characteristic of a population/sample or a

phenomenon

inferential: hope to generalize from a sample to a population (based on

probability)--we use parametric and non-parametric statistics


parametric tests and non-parametric tests - 🧠 ANSWER ✔✔every statistical test

has assumptions that must be met

parametric tests have more stringent assumptions--two of the most critical

assumptions: normal distribution of the data and level of measurement (must be

interval-like in nature)

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,non-parametric tests don't have such limitations

we like parametric tests b/c they are more powerful and more likely to find a

difference if there is one

one chosen will depend on your data


analysis - 🧠 ANSWER ✔✔clearly the problem is the driving force--the

sophistication of analysis will never compensate for an insignificant problem

always remember the research question or hypothesis always drives the analysis

look at the hypothesis or question--should be able to begin to think about the type

of analysis that would be appropriate


when you are beginning to think about statistical tests... - 🧠 ANSWER ✔✔you

must look at what drives the tests-->the research question and the hypothesis--what

are the variables and how are they measured? what is the level of measurement?


if the question focuses on describing some phenomena - 🧠 ANSWER ✔✔N & %

(if data are nominal or categorical) or descriptive statistics (if measures are

interval-like in nature--mean, standard deviation, range)

if the research question or hypothesis is interested in a relationship between two

variables - 🧠 ANSWER ✔✔correlation



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,Pearson's r (parametric test) or Spearman Rho/Kendall's Tau (non-parametric test)

if the research question or hypothesis is interested in a difference between two

independent groups - 🧠 ANSWER ✔✔the independent t test (parametric) or the

Mann Whitney U (if data weren't normally distributed)

if the research question or hypothesis is interested in a difference between two or

more independent groups - 🧠 ANSWER ✔✔ANOVA (parametric) or the Kruskal

Wallis (if data aren't normally distributed or if measure is ordinal)

if the research question or hypothesis is interested in differences in two groups that

are dependent (repeated measures) - 🧠 ANSWER ✔✔the paired t test (parametric)

or Wilcoxon (non-parametric)

if the research question or hypothesis is interested in the difference in two or more

groups that are dependent - 🧠 ANSWER ✔✔RANOVA (parametric) or Friedman

(non-parametric)


how can you choose? - 🧠 ANSWER ✔✔what is the research question or hypothesis

asking?

are groups independent or dependent?

what is the level of measurement of the variables?



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, are the assumptions of the statistical test met, particularly that of normal

distribution?

knowledge of statistics is necessary to all who read or conduct research - 🧠

ANSWER ✔✔research: making observations or measurements on people, things,

or events to answer a research question

statistics: a set of procedures for describing those measurements--how do we

quantify and report these measurements?


data - 🧠 ANSWER ✔✔the raw material of research


variable - 🧠 ANSWER ✔✔something that varies or takes on different values


we are always interested in variability and explaining variation


variables are also classified as... - 🧠 ANSWER ✔✔discrete: finite number of value

(almost like you can count)--obtained by counting

continuous: infinite number of value between any two points--obtained by

measuring

statistical methods are sometimes described by the number of variables in the

analysis - 🧠 ANSWER ✔✔univariate: average cholesterol


bivariate: average cholesterol (exercise group and sedentary group)

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