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C784 | 100+ Objective Assessment Questions | Probability, Regression, Equations | WGU

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This document contains over 100 expert-verified multiple-choice questions and answers from the 2025/2026 Objective Assessment #1 for C784 – Applied Healthcare Statistics at WGU (Western Governors University). It serves as a high-yield study resource for nursing, health sciences, and analytics students needing to master fundamental concepts in statistics and healthcare math. Topics include types of data (qualitative vs. quantitative), descriptive statistics (mean, median, mode, outliers, five-number summary), probability and probability rules (conditional probability, independent events, disjoint events), regression and correlation (regression line, least squares, scatterplots), and algebraic reasoning (fractions, exponents, operations, LCM/GCF, equations, unit conversions). It also features applied healthcare problems including dosage calculations, body fluid volumes, rates, and temperature conversions—essential skills for clinical and data-driven decision-making in healthcare. Each question is clearly labeled with the correct answer, and definitions of key concepts are provided throughout. This resource is perfect for WGU students preparing for their objective assessments, and for others in healthcare programs requiring statistics competency. Who this document is for: • WGU students in C784 – Applied Healthcare Statistics • Nursing and healthcare administration students • Allied health, health science, and public health majors • Learners preparing for nursing entrance exams or healthcare analytics roles • Students needing support in math, statistics, or quantitative reasoning for healthcare Keywords: C784, WGU, applied healthcare statistics, objective assessment, mean, median, mode, regression, correlation, probability, fractions, equations, GCF, LCM, order of operations, dot plot, box plot, scatterplot, slope, intercept, dosage calculation, temperature conversion, data analysis, healthcare math, unit conversion

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WGU C784 - Applied Healthcare
Statistics Objective Assessment #1 2025
Expert Verified | Ace the Test



Given the following set of numbers: 3.3, -2.3, -16, 25. What are the square

roots of the whole number?

A. +/- 2.3

B. +/- 3.3

C. +/- 4


D. +/- 5 - 🧠 ANSWER ✔✔D. +/- 5


Composite Number - 🧠 ANSWER ✔✔A number with more factors that just

one and itself.

,Equivalent Fractions - 🧠 ANSWER ✔✔Different fractions that represent the

same value.


X-Axis - 🧠 ANSWER ✔✔The horizontal line that passes through the origin

on a coordinate plane.


Qualitative Data - 🧠 ANSWER ✔✔Non-numeric information based on some

quality or characteristic.


No Correlation - 🧠 ANSWER ✔✔There is no apparent overall trend

between the two variables. If the correlation coefficient is 0, this only rules

out a linear trend. There could be a non-linear or curvilinear trend.


Extrapolate - 🧠 ANSWER ✔✔Using information from a data set to make

predictions about data outside of the original set.


Event - 🧠 ANSWER ✔✔An outcome, or set of outcomes, whose chance of

occurrence can be represented with a probability.

Given the following set of numbers: 10, 2.5, -4, -4.5, 5. What is the sum

when adding together only the whole numbers?

A. 5.5

B. 11

, C. 12.5


D. 15 - 🧠 ANSWER ✔✔D. 15


Operation - 🧠 ANSWER ✔✔In Mathematics, an operation is a procedure

which generates a new value from one or more operands, or Mathematical

values.


Conditional Proportion - 🧠 ANSWER ✔✔A proportion where one part of the

proportion is a variable, or unknown quantity.


Coefficients - 🧠 ANSWER ✔✔A number by which a number is multiplied.

This number is written in front of the variable(s).


Mean - 🧠 ANSWER ✔✔Average, calculated by adding a series of elements

in a data set together and dividing by the total number in the series.


Outlier - 🧠 ANSWER ✔✔An observation point that is statistically distant

from the other observations in the dataset.


Regression Line - 🧠 ANSWER ✔✔The line of best fit to show the

relationship between variables, the one that minimizes distance from each

data point to the line.




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