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Applied Probability & Statistics C955: Premier Formula Sheet and Practice

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Applied Probability & Statistics C955: Premier Formula Sheet and Practice Problems for Nursing Mastery 2025Your Essential Guide to Statistical Excellence and Exam Success 1 Introduction This premier guide is tailored for WGU C955 nursing students preparing for the 2025 Objective Assessment (OA) in Applied Probability and Statistics. It includes a comprehensive formula sheet, 30 advanced practice questions with clear, concise, and detailed rationales, and a clinical scenario, all focused on nursing applications. The guide equips students with strategies to excel in the OA and apply statistics in healthcare practice.

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Applied Probability & Statistics C955:
Premier Formula Sheet and Practice
Problems for Nursing Mastery 2025 Your
Essential Guide to Statistical Excellence and Exam Success



1 Introduction
This premier guide is tailored for WGU C955 nursing students preparing for the 2025 Objective
Assessment (OA) in Applied Probability and Statistics. It includes a comprehensive formula sheet,
30 advanced practice questions with clear, concise, and detailed rationales, and a clinical scenario,
all focused on nursing applications. The guide equips students with strategies to excel in the OA
and apply statistics in healthcare practice.


2 Formula Sheet

Concept Formula
∑
ix
Mean x̄ = ∑n
(x −x̄)2
Variance σ 2 =√ ni
Standard Deviation σ = σ2
Probability P (A) = favorable outcomes
total outcomes
Conditional Probability P (A|B) = P P(A∩B)
(B)
Expected Value (Binomial) E(X) = n · p
Z-score z = x−µ
σ ∑
(x −x̄)(y −ȳ)
Pearsons Correlation √
r = ∑ i 2 ∑i
(xi −x̄) (yi −ȳ)
2

Linear Regression y = β0 + β1 x
Confidence Interval (Mean) x̄ ± z · √σn


3 Practice Question Bank
3.1 Question 1
A clinic reports that 21% of patients experience side effects from a new treatment. If 250 patients
receive the treatment, how many are expected to experience side effects?
a) 50
b) 53
c) 56
d) 59
Answer: b) 53
Rationale: Expected value in a binomial distribution is E(X) = n · p, where n = 250 (patients) and
p = 0.21 (probability). Thus, 250 · 0.21 = 52.5, rounded to 53. The expected number is 53 patients.


1

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