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HLT-362V Applied Statistics for Health Care
HLT-362V Applied Statistics for Health Care is a required course in Grand Canyon University’s RN-to-BSN program that teaches nursing students how to use descriptive and inferential statistics to improve patient outcomes, evaluate research, and make data-driven clinical decisions. The course covers everything from calculating means and standard deviations in Excel to reading a peer-reviewed study and deciding whether its findings actually prove what the authors claim.
If you are a working nurse juggling clinicals, a job, and family while trying to pass this course, this guide is the single resource you need: it maps every graded assignment, links to a detailed guide and worked example for each one, and explains how the assignments connect so the course makes sense as a whole.
What Is HLT-362V Applied Statistics for Health Care?
HLT-362V is a statistics course designed specifically for health care professionals in GCU’s College of Nursing and Health Care Professions. It sits in the RN-to-BSN curriculum and assumes no prior statistics background; you learn by doing, with each assignment building on the one before it.
The course runs across five topics (roughly five weeks) and includes a mix of Excel-based calculation worksheets, APA-formatted writing assignments, and research article analyses. There is one benchmark assignment (Summary and Descriptive Statistics) that carries extra weight and ties to a program competency.
Unlike a pure math class, HLT-362V frames every concept in terms of nursing practice. You are not learning statistics for its own sake; you are learning it so you can evaluate evidence, detect health disparities, and support quality improvement at the bedside and in leadership.
What Are the HLT-362V Assignments?
HLT-362V includes six core graded assignments spread across the course topics. Each one teaches a different layer of statistical reasoning, from conceptual understanding to hands-on computation to critical appraisal of published research.
Topic 1: Application of Statistics in Health Care
The first assignment is a 750–1,000-word APA paper explaining why statistics matter in health care across four domains: quality, patient safety, health promotion, and leadership. It sets the conceptual foundation for everything that follows. You are not calculating anything yet; you are building the argument for why a nurse needs statistical literacy.
Our guide: Application of Statistics in Health Care: Guide + Example — includes a fully worked APA paper with peer-reviewed references (2023–2024).
Topic 2: Summary and Descriptive Statistics (Benchmark)
The benchmark assignment gives you the National Cancer Institute data on cancer incidence rates by race/ethnicity and asks you to calculate six descriptive statistics — mean, median, mode, variance, standard deviation, and range — using Excel formulas for each group. You then write a 150–250-word analysis interpreting the group differences and their health-outcomes implications.
This is the most heavily weighted assignment in the course and the one where students lose the most points, usually by typing answers instead of leaving live formulas.
Our guide: Summary and Descriptive Statistics: Guide + Example — includes a worked .xlsx with live formulas and a model analysis paragraph.
Topic 2: Population and Sampling Distribution Excel Worksheet
This worksheet teaches the difference between how individual values vary (population distribution) and how sample means vary (sampling distribution). You calculate Z-scores with STANDARDIZE, find normal-distribution probabilities with NORMDIST, and compute the standard error of the mean.
The key concept: sample means cluster more tightly around the population mean than individual values do, and the standard error shrinks as sample size grows. Students who miss this distinction lose points on both the worksheet and later assignments.
Our guide: Population and Sampling Distribution: Guide + Example — includes a worked .xlsx covering Z-scores, probabilities, and standard error.
Topics 2–3: Article Analysis 1 and Article Analysis 2
The two article analysis assignments ask you to locate two peer-reviewed quantitative research articles per assignment and complete an analysis template for each study — identifying the purpose, design, sample, variables, instruments, statistical tests, findings, and limitations. Article Analysis 2 uses the same template with two new articles.
These assignments test whether you can read quantitative research critically. The most common errors are choosing a qualitative study by mistake, naming the wrong statistical test, and copying the abstract instead of analyzing in your own words.
Our guides:
- Article Analysis 1: Guide + Example — worked example analyzing two 2024 nurse-burnout studies.
- Article Analysis 2: Guide + Example — worked example analyzing two 2023 medication-safety studies.
Correlation and Causation
The final core assignment is a 750–1,000-word APA paper that asks you to find a real-world example where correlation was mistaken for causation in health, analyze the error, explain how misinformation spread, and propose a study design (typically an RCT) that would have resolved the question.
This is the most integrative assignment in the course — it requires you to understand confounding, study design, and the limits of observational data, drawing together everything you have learned.
Our guide: Correlation and Causation: Guide + Example — worked example using the vitamin D and COVID-19 case.
How Do the HLT-362V Assignments Build on Each Other?
The assignments in HLT-362V follow a deliberate progression from conceptual understanding to practical application to critical evaluation. Seeing this structure helps you study more efficiently and write stronger papers.
Layer 1 — Why statistics matter. The Application of Statistics paper (Topic 1) establishes the conceptual foundation. You explain why health care needs data.
Layer 2 — How to compute statistics. The Summary and Descriptive Statistics benchmark and the Population and Sampling Distribution worksheet (Topic 2) put you in Excel computing the actual numbers: means, standard deviations, Z-scores, probabilities, and the standard error. These are the building blocks.
Layer 3 — How to read statistics. Article Analysis 1 and 2 (Topics 2–3) shift you from producer to consumer. You read published research and identify which statistical methods were used and what the results mean.
Layer 4 — How to evaluate statistics. The Correlation and Causation paper asks you to judge whether a statistical finding actually proves what it claims. This is the highest-order skill in the course and the one most directly relevant to evidence-based nursing practice.
Each layer depends on the one before it, which is why students who skip ahead often struggle; the Article Analyses are hard to complete if you do not know what a t-test or regression is, and the Correlation and Causation paper is hard to write if you have not practiced identifying study designs in the Article Analyses.
What Statistical Concepts Does HLT-362V Cover?
HLT-362V covers a focused set of statistical concepts, each tied to a specific assignment. Understanding which concept maps to which assignment helps you study the right material at the right time.
Descriptive statistics — mean, median, mode, variance, standard deviation, and range. Covered in the Summary and Descriptive Statistics benchmark.
Normal distribution and Z-scores — the bell curve, standardized scores, and cumulative probabilities. Covered in the Population and Sampling Distribution worksheet.
Sampling distributions and the standard error — how sample means behave and why larger samples produce more reliable estimates. Also covered in the Population and Sampling Distribution worksheet.
Research design — cross-sectional, cohort, experimental, and randomized controlled trials. Introduced in the Article Analyses and deepened in the Correlation and Causation paper.
Correlation and causation — the difference between association and cause-and-effect, confounding variables, and the role of RCTs. Covered in the Correlation and Causation paper.
Inferential statistics — t-tests, ANOVA, chi-square, and regression (primarily encountered in the research articles you analyze, not computed directly).
Tips for Succeeding in HLT-362V
Students who do well in HLT-362V share a few common habits. These are worth adopting from the start.
- Use Excel formulas, never type answers. The benchmark rubric specifically grades whether you used live formulas. A hardcoded number earns zero for that criterion even if the value is correct.
- Read the methods section first. When selecting articles for the Article Analyses, start with the methods — it tells you the design, sample size, and statistical tests in one place.
- Name specifics, not generalities. In every assignment, the rubric rewards specificity: “Pearson correlation and multiple linear regression” scores higher than “statistical analysis.”
- Follow APA 7 to the letter. Title page, double spacing, hanging-indent references, and in-text citations are mechanical points you should never lose.
- Connect statistics to practice. The strongest papers and analyses tie the numbers back to patient care, quality improvement, or health policy — because that is what the course is designed to teach.
HLT-362V Applied Statistics for Health Care FAQ
Is HLT-362V hard?
HLT-362V is challenging for students without a statistics background, but it is manageable because the course is designed for working nurses and builds concepts progressively. The Excel worksheets are formula-based, and the papers follow clear rubric structures that reward specificity.
What textbook does HLT-362V use?
HLT-362V has historically used Grove and Cipher’s Statistics for Nursing Research workbook, though GCU periodically updates course materials. The current curriculum pairs textbook readings with Excel-based assignments and APA writing tasks.
How many assignments are in HLT-362V?
HLT-362V includes six core graded assignments: the Application of Statistics paper, the Summary and Descriptive Statistics benchmark, the Population and Sampling Distribution worksheet, Article Analysis 1, Article Analysis 2, and the Correlation and Causation paper. Discussion questions are also graded weekly.
Do I need to know Excel for HLT-362V?
Yes, two of the six assignments require you to use Excel formulas; specifically AVERAGE, MEDIAN, MODE, VAR, STDEV, STANDARDIZE, NORMDIST, and SQRT. You do not need advanced Excel skills, but you must be comfortable entering and copying formulas.
What is the benchmark assignment in HLT-362V?
The benchmark is the Summary and Descriptive Statistics assignment, which carries extra weight and is tied to a program competency. You calculate six descriptive statistics for the National Cancer Institute data and write a short analysis interpreting group differences.
About the Author
This guide was prepared by the Gradevia academic team, specialists in nursing and health-sciences coursework support for students at GCU, WGU, Walden, and Liberty University. Our writers hold graduate degrees in nursing, public health, and applied statistics, and have produced hundreds of rubric-aligned HLT-362V resources. We focus on helping busy working nurses understand the method, not just the answer.
Article Update Log
- June 18, 2026 — Initial publication.
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