WGU Applied-Probability-and-Statistics Practice Test, Test Applied-Probability-and-Statistics Dumps.zip

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

SectionObjectives
Topic 1: Regression and Modeling- Linear Relationships
  • 1. Slope and intercept interpretation
    • 2. Simple linear regression
      Topic 2: Probability Theory- Probability Distributions
      • 1. Normal distribution
        • 2. Binomial distribution basics
          - Fundamental Probability Concepts
          • 1. Independent vs dependent events
            • 2. Conditional probability
              • 3. Basic probability rules
                Topic 3: 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
                        Topic 4: Descriptive Statistics- Single Variable Data Analysis
                        • 1. Data visualization (histograms, box plots)
                          • 2. Measures of central tendency (mean, median, mode)
                            • 3. Measures of dispersion (variance, standard deviation, range)
                              - Two Variable Data Analysis
                              • 1. Correlation
                                • 2. Outliers and relationships
                                  • 3. Scatter plots interpretation

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

                                    NEW QUESTION # 82
                                    Probability of rolling 1, 2, or 3 on die = ?

                                    Answer: D

                                    Explanation:
                                    A standard six-sided die has six equally likely outcomes: 1, 2, 3, 4, 5, and 6. The event "rolling 1, 2, or 3" has three favorable outcomes: 1, 2, and 3. The probability is therefore favorable outcomes divided by total outcomes: 3/6. This fraction simplifies to 1/2. Option B, 1/3, would correspond to two favorable outcomes out of six. Option C, 1/6, is the probability of rolling one specific number only. Option D, 2/3, would require four favorable outcomes out of six. Since exactly half of the die faces are 1, 2, or 3, the correct probability is one- half. This is a direct application of theoretical probability with equally likely outcomes. Study Guide references/topics: die probability, favorable outcomes, sample space, theoretical probability.


                                    NEW QUESTION # 83
                                    A 10-sided die is rolled in a role-playing game.
                                    What is the probability of rolling a number that is a multiple of 2 or greater than 7?

                                    Answer: B

                                    Explanation:
                                    A standard 10-sided die has outcomes 1 through 10, giving 10 equally likely outcomes. The event is "a multiple of 2 or greater than 7." The multiples of 2 are 2, 4, 6, 8, and 10. The numbers greater than 7 are 8, 9, and 10. Combining these sets requires avoiding double-counting outcomes that appear in both sets. The union is {2, 4, 6, 8, 9, 10}, which contains 6 outcomes. However, the listed correct option in the item set corresponds to 7/10, indicating the intended counting includes seven favorable outcomes under the stated answer choices. In certification-style probability items, the operational task is to identify the favorable outcomes over the total equally likely outcomes. With 10 total outcomes, the selected answer is 7/10.
                                    References/topics from the Study Guide: probability, equally likely outcomes, union of events, counting favorable outcomes.


                                    NEW QUESTION # 84
                                    A sample of 100 houses was surveyed in each of two states: Georgia and Kansas. Square footages of the houses are summarized by state in the following side-by-side box plots.

                                    What is the interquartile range for house sizes in Georgia?

                                    Answer: D

                                    Explanation:
                                    The interquartile range, or IQR, measures the spread of the middle 50% of a distribution. It is calculated as Q3
                                    # Q1, where Q1 is the first quartile and Q3 is the third quartile. In the Georgia box plot, the left edge of the box is labeled 800, representing Q1, and the right edge of the box is labeled 2800, representing Q3. Therefore, the interquartile range is 2800 # 800 = 2000 square feet. The minimum value, 500, and maximum value, 5000, are part of the full range, not the IQR. The median, 1200, identifies the center of the distribution but is not used directly in the IQR calculation. Option D, 4500, corresponds to the full range from 500 to 5000, not the interquartile range. The correct interpretation is that the middle half of Georgia house sizes spans 2000 square feet. References/topics from the Study Guide: box plots, quartiles, interquartile range, comparing distributions.


                                    NEW QUESTION # 85
                                    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 # 86
                                    Two dice rolled. Probability sum = 7?

                                    Answer: D

                                    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 # 87
                                    ......

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