WGU Applied-Probability-and-Statistics Questions Pdf, Exam Applied-Probability-and-Statistics Forum

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

SectionObjectives
Probability- Fundamental probability concepts
  • 1. Events and sample spaces
    • 2. Conditional probability and independence
      - Probability rules
      • 1. Addition and multiplication rules
        • 2. Bayes’ theorem (introductory level)
          Descriptive Statistics- Data visualization
          • 1. Box plots and interpretation
            • 2. Histograms and frequency distributions
              - Data summarization
              • 1. Measures of central tendency (mean, median, mode)
                • 2. Measures of variability (range, variance, standard deviation)
                  Probability Distributions- Discrete distributions
                  • 1. Poisson distribution (introductory use cases)
                    • 2. Binomial distribution
                      - Continuous distributions
                      • 1. Standard normal and z-scores
                        • 2. Normal distribution
                          Regression and Correlation- Relationship analysis
                          • 1. Correlation coefficient interpretation
                            • 2. Simple linear regression basics
                              Statistical Inference- Estimation
                              • 1. Confidence intervals for means and proportions
                                - Hypothesis testing
                                • 1. t-tests and z-tests (basic application)
                                  • 2. Null and alternative hypotheses

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                                    WGU Applied Probability and Statistics (FZO1 C955) Sample Questions (Q127-Q132):

                                    NEW QUESTION # 127
                                    A road safety research group wants to enhance road safety by analyzing the stopping distance of a car at different speeds. The group has recorded their data in the following scatterplot.

                                    What is true about the outlier in the scatterplot?

                                    Answer: C

                                    Explanation:
                                    An outlier is a data point that does not follow the general pattern of the remaining data. In this scatterplot, most points show a clear increasing relationship: as speed increases, stopping distance also increases. The main cluster follows a smooth upward trend, with stopping distances gradually rising as speed increases. One point, however, is far above the rest of the pattern. That point is located at approximately 40 mph and 560 feet, making it unusually high compared with the expected stopping distance at that speed. This is why option D correctly identifies the outlier. Option A describes a low-speed point that fits the lower end of the trend.
                                    Option B describes a high-speed point near the upper end of the general pattern, not an unusual deviation.
                                    Option C describes a point around 30 mph and 190 feet, which lies within the main cluster of observations.
                                    The outlier is not merely an extreme x-value or y-value; it is unusual relative to the trend. References/topics from the Study Guide: scatterplots, outliers, bivariate data, association patterns.


                                    NEW QUESTION # 128
                                    Probability it does NOT rain = 1 # 0.25 = ?

                                    Answer: B

                                    Explanation:
                                    This question uses the complement rule of probability. If the probability that it rains is 0.25, then the probability that it does not rain is the complement of that event. The complement rule states that P(not A) = 1
                                    # P(A). Here, A represents the event "it rains," so P(not rain) = 1 # 0.25 = 0.75. This means there is a 75% probability that rain does not occur. Option B repeats the probability of rain rather than its complement.
                                    Option C would imply rain and no rain are equally likely, which is not supported by the given probability.
                                    Option D would mean no rain is certain, but a 0.25 probability of rain means rain is still possible. The key technical point is that an event and its complement must sum to 1. Study Guide references/topics: probability, complement rule, event probability, sample-space total.


                                    NEW QUESTION # 129
                                    A city council surveys residents and business owners about a proposed new public transportation system. The results of the survey are shown in the following 2 × 2 contingency table.

                                    Which statement is true?

                                    Answer: D

                                    Explanation:
                                    This question requires comparing conditional percentages from a two-way table. For residents, 150 out of 200 are in favor of the proposed transportation system. The resident support rate is therefore 150/200 = 0.75, or
                                    75%. For business owners, 30 out of 100 are in favor. The business owner support rate is 30/100 = 0.30, or
                                    30%. The difference is 75% # 30% = 45 percentage points, which is a large gap. Therefore, a resident is much more likely than a business owner to favor the new transportation system. Option A understates the magnitude of the difference by calling it slight. Options B and C reverse the direction of the comparison because residents have the higher support rate, not the lower one. The appropriate statistical tool here is conditional percentage because support is being compared within each respondent group. References/topics from the Study Guide: contingency tables, conditional percentages, two-variable categorical data, comparative proportions.


                                    NEW QUESTION # 130
                                    Uniform distribution 0-5: P(X < 3) = ?

                                    Answer: A

                                    Explanation:
                                    For a continuous uniform distribution on the interval from 0 to 5, probability is proportional to interval length.
                                    The total interval length is 5 # 0 = 5. The event X < 3 corresponds to the interval from 0 to 3, which has length 3. Therefore, P(X < 3) = 3/5 = 0.6. This works because the uniform distribution assigns constant density across the entire interval, so any subinterval's probability equals its length divided by the total length.
                                    Option B would correspond to half the interval, such as X < 2.5. Option C would correspond to length 2 out of
                                    5. Option D incorrectly treats the cutoff value 3 as if it were a percentage rather than an interval boundary.
                                    The correct answer is 0.6, meaning 60% of the uniform distribution lies below 3. Study Guide references
                                    /topics: uniform distribution, continuous probability, interval length, probability density.


                                    NEW QUESTION # 131
                                    Histogram vs bar chart:

                                    Answer: A


                                    NEW QUESTION # 132
                                    ......

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