Other WGU Applied-Probability-and-Statistics Exam Key Questions

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

SectionObjectives
Statistical Inference- Estimation and Confidence Intervals
  • 1. Point estimates
    • 2. Confidence interval interpretation
      - Hypothesis Testing (Introductory Level)
      • 1. Null vs alternative hypothesis
        • 2. p-values interpretation
          Descriptive Statistics- Single Variable Data Analysis
          • 1. Measures of dispersion (variance, standard deviation, range)
            • 2. Measures of central tendency (mean, median, mode)
              • 3. Data visualization (histograms, box plots)
                - Two Variable Data Analysis
                • 1. Correlation
                  • 2. Outliers and relationships
                    • 3. Scatter plots interpretation
                      Probability Theory- Fundamental Probability Concepts
                      • 1. Conditional probability
                        • 2. Independent vs dependent events
                          • 3. Basic probability rules
                            - Probability Distributions
                            • 1. Normal distribution
                              • 2. Binomial distribution basics
                                Regression and Modeling- Linear Relationships
                                • 1. Simple linear regression
                                  • 2. Slope and intercept interpretation

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                                    WGU Applied Probability and Statistics (FZO1 C955) Sample Questions (Q82-Q87):

                                    NEW QUESTION # 82
                                    The dot plot illustrates the frequency of outdoor games played by students per week.

                                    Which statement is true?

                                    Answer: D

                                    Explanation:
                                    The dot plot shows a distribution centered near 3 days, with substantial frequencies at 2, 3, and 4 days and smaller frequencies at the extremes of 1 and 5 days. This shape is reasonably balanced around the center.
                                    When a distribution is approximately symmetric, the mean and median tend to be close because the lower and higher values balance each other. The median identifies the middle observation after the data are ordered, and the mean represents the balance point of the distribution. Since the tallest stack is near 3 days and the surrounding stacks on 2 and 4 days are comparable, the center of the data is approximately 3 days by both measures. There is no strong skew to pull the mean far above or below the median. Therefore, the best statement is that the mean is almost the same as the median. Options B and C would require clear skew or extreme imbalance, which the dot plot does not show. References/topics from the Study Guide: dot plots, mean, median, distribution shape, symmetry.


                                    NEW QUESTION # 83
                                    What is the mode of this dataset: 3, 5, 7, 7, 10?

                                    Answer: B

                                    Explanation:
                                    The mode is the value that occurs most frequently in a data set. In the set 3, 5, 7, 7, 10, the value 3 appears once, 5 appears once, 10 appears once, and 7 appears twice. Since 7 has the highest frequency, it is the mode.
                                    This question tests recognition of a measure of center that differs from the mean and median. The mean would require summing all values and dividing by the number of observations, while the median would identify the middle value after ordering the data. The data are already ordered, and the middle value is also 7, but the reason the correct answer is 7 here is specifically because it appears more often than any other value. Options A, B, and D each name values that occur only once, so none can be the mode. A dataset may have one mode, multiple modes, or no mode, but this dataset is unimodal. References/topics from the Study Guide: descriptive statistics, measures of center, frequency, mode.


                                    NEW QUESTION # 84
                                    What is the result of 2/5 + 1/3 # 1/4?

                                    Answer: B

                                    Explanation:
                                    To add and subtract fractions, first rewrite all fractions using a common denominator. The denominators are
                                    5, 3, and 4. Their least common denominator is 60. Convert each fraction: 2/5 = 24/60, 1/3 = 20/60, and 1/4 =
                                    15/60. Now combine the numerators while keeping the common denominator: 24/60 + 20/60 # 15/60 = (24 +
                                    20 # 15)/60 = 29/60. The fraction 29/60 is already in simplest form because 29 is prime and does not divide
                                    60. Option A, 13/60, and option B, 11/60, result from incorrect numerator operations. Option D, 19/60, also fails to preserve the correct addition before subtraction. The essential technical step is establishing a common denominator before performing arithmetic operations. References/topics from the Study Guide: fractions, least common denominator, fraction addition, fraction subtraction.


                                    NEW QUESTION # 85
                                    95% CI = 50 ± 2. SE = ?

                                    Answer: C

                                    Explanation:
                                    A confidence interval has the structure estimate ± margin of error. The margin of error is calculated as critical value × standard error. For a 95% confidence interval using the normal approximation, the critical value is approximately 1.96, often rounded to 2 in introductory settings. The interval is given as 50 ± 2, so the margin of error is 2. Using the approximate 95% critical value of 2, we solve 2 = 2 × SE, giving SE = 1. More exactly, using 1.96 gives SE = 2/1.96 # 1.02, which rounds to 1. Option B confuses the margin of error with the standard error. Option C is too large, and option D would produce a margin of error near 1 under a 95% critical value. The correct standard error is approximately 1. Study Guide references/topics: confidence intervals, standard error, critical value, margin of error.


                                    NEW QUESTION # 86
                                    Central limit theorem applies when:

                                    Answer: A

                                    Explanation:
                                    The central limit theorem applies when the sample size is sufficiently large and observations are independent.
                                    It states that the sampling distribution of the sample mean becomes approximately normal as sample size increases, even if the original population distribution is not normal. This makes option A correct. Option B is incorrect because the population does not have to be normal for the theorem to operate; large sample size is what permits the normal approximation. Option C is not the condition that defines the theorem. A population parameter may be unknown in inference, but that is not the trigger for the central limit theorem. Option D is incorrect because the classic central limit theorem for means concerns quantitative data, not purely categorical labels. The theorem is foundational because it justifies using normal-based confidence intervals and hypothesis tests for means when sample sizes are large. Study Guide references/topics: central limit theorem, sample size, sampling distribution, normal approximation.


                                    NEW QUESTION # 87
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