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WGU Applied-Probability-and-Statistics Exam Syllabus Topics:

SectionWeightObjectives
Inferential Statistics & Study Design20%- Observational studies vs experiments
- Sampling methods and bias
- Hypothesis testing framework and interpretation
- Confidence intervals for means/proportions
Descriptive Statistics25%- Types of data: categorical, discrete, continuous
- Graphical displays: histograms, boxplots, scatterplots
- Measures of center: mean, median, mode
- Measures of spread: range, IQR, variance, standard deviation
Basic Numeracy & Algebra15%- Exponents, roots, and basic formulas
- Arithmetic operations, fractions, decimals, percentages
- Linear equations, inequalities, graphing functions
Probability Concepts20%- Discrete and continuous probability distributions
- Probability rules, independent and dependent events
- Normal distribution and empirical rule
- Conditional probability and Venn diagrams
Correlation & Regression20%- Interpreting slope, intercept, and R-squared
- Correlation coefficient and interpretation
- Simple linear regression models
- Predictions and limitations of regression

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WGU Applied Probability and Statistics (FZO1 C955) Sample Questions (Q104-Q109):

NEW QUESTION # 104
Poisson used for:

Answer: D

Explanation:
The Poisson distribution is used to model counts of events occurring within a fixed interval of time, space, area, or volume, especially when the events are relatively rare and occur at a constant average rate. Examples include the number of calls received per hour, accidents per month, defects per batch, or arrivals at a service counter per minute. Its parameter # represents the average number of events per interval. Option B describes the binomial distribution, which models the number of successes in a fixed number of independent success
/failure trials. Option C is incorrect because Poisson outcomes are discrete counts, not continuous measurements. Option D is also incorrect because categorical data classify observations into groups, while Poisson data count event occurrences. The phrase "rare events per interval" is the defining clue for the Poisson model. Study Guide references/topics: Poisson distribution, rare-event counts, # parameter, discrete probability models.


NEW QUESTION # 105
Two dice rolled. Probability sum = 7?

Answer: B

Explanation:
When two standard six-sided dice are rolled, there are 6 × 6 = 36 equally likely ordered outcomes. To find the probability that the sum is 7, count all ordered pairs that produce 7. These are (1,6), (2,5), (3,4), (4,3), (5,2), and (6,1). There are 6 favorable outcomes. Therefore, the probability is 6/36, which simplifies to 1/6. Since the answer choices include both 6/36 and 1/6, the listed answer from the PDF uses the unsimplified equivalent form, 6/36. Option C, 5/36, omits one valid ordered pair. Option D, 1/12, is too small because it would represent only 3 favorable outcomes out of 36. This problem reinforces that dice outcomes are ordered when two dice are rolled, so (1,6) and (6,1) are counted separately. Study Guide references/topics: sample spaces, dice probability, favorable outcomes, theoretical probability.


NEW QUESTION # 106
There are 20 men in a room whose heights are reflected in inches as 68, 70, 73, 67, 71, 68, 76, 70, 73, 66, 68,
69, 71, 74, 73, 72, 65, 60, 70, and 78 inches respectively.
What is the median of these data?

Answer: A

Explanation:
The median is the middle value of an ordered data set. Because there are 20 observations, the number of data values is even, so the median is the average of the 10th and 11th values after the data are arranged from least to greatest. Ordering the heights gives 60, 65, 66, 67, 68, 68, 68, 69, 70, 70, 70, 71, 71, 72, 73, 73, 73, 74, 76,
78. The 10th value is 70, and the 11th value is also 70. The median is therefore (70 + 70) ÷ 2 = 70. This value divides the ordered heights into two equal halves: ten values are at or below 70, and ten values are at or above
70. The median is resistant to extreme values, so the low value 60 and the high value 78 do not distort it the way they could affect the mean. References/topics from the Study Guide: median, ordered data, measures of center, quantitative data.


NEW QUESTION # 107
Sample correlation r = 0 #

Answer: B

Explanation:
The correlation coefficient r measures the strength and direction of a linear relationship between two quantitative variables. Values close to 1 indicate strong positive linear association, values close to #1 indicate strong negative linear association, and values near 0 indicate no linear relationship. Therefore, r = 0 means there is no linear association detected by the correlation coefficient. It is important to interpret this precisely: r
= 0 does not guarantee there is no relationship of any kind. A nonlinear relationship may still exist, but correlation measures only linear pattern. Option B and option C are incorrect because strong relationships require r to be close to 1 or #1. Option D is incorrect because perfect correlation occurs at r = 1 or r = #1, not at 0. The correct interpretation is no linear relationship. Study Guide references/topics: correlation coefficient, linear association, scatterplots, correlation interpretation.


NEW QUESTION # 108
Expected value of binomial X ~ B(10, 0.3) = ?

Answer: A

Explanation:
For a binomial random variable, the expected value is E(X) = np, where n is the number of trials and p is the probability of success on each trial. In this problem, X ~ B(10, 0.3), so n = 10 and p = 0.3. Substituting into the formula gives E(X) = 10 × 0.3 = 3. This means that across many repetitions of the same binomial experiment, the average number of successes would be 3. Option B, 7, would correspond to the expected number of failures if the failure probability is 0.7. Option C gives only the number of trials, not the expected successes. Option D gives only the success probability, not the expected count. The expected value combines both trial count and success probability. Study Guide references/topics: binomial distribution, expected value, success probability, discrete random variables.


NEW QUESTION # 109
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