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

SectionObjectives
Probability- Fundamental probability concepts
  • 1. Conditional probability and independence
    • 2. Events and sample spaces
      - Probability rules
      • 1. Bayes’ theorem (introductory level)
        • 2. Addition and multiplication rules
          Descriptive Statistics- Data summarization
          • 1. Measures of variability (range, variance, standard deviation)
            • 2. Measures of central tendency (mean, median, mode)
              - Data visualization
              • 1. Box plots and interpretation
                • 2. Histograms and frequency distributions
                  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
                        Probability Distributions- Continuous distributions
                        • 1. Standard normal and z-scores
                          • 2. Normal distribution
                            - Discrete distributions
                            • 1. Poisson distribution (introductory use cases)
                              • 2. Binomial distribution
                                Regression and Correlation- Relationship analysis
                                • 1. Simple linear regression basics
                                  • 2. Correlation coefficient interpretation

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                                    WGU Applied-Probability-and-Statistics Questions Exam Study Tips And Information

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                                    WGU Applied Probability and Statistics (FZO1 C955) Sample Questions (Q69-Q74):

                                    NEW QUESTION # 69
                                    Standard error decreases when:

                                    Answer: B

                                    Explanation:
                                    The standard error of the mean is calculated as SE = s/#n, where s is the sample standard deviation and n is the sample size. Because n appears in the denominator under a square root, increasing the sample size decreases the standard error when the standard deviation is held constant. This reflects a central idea in sampling: larger samples tend to produce more stable and precise estimates of the population mean. Option C is incorrect because increasing the standard deviation increases the standard error, not decreases it. Option B is incomplete and does not identify what is decreasing. Option D is not the direct driver of standard error; confidence level affects the critical value and margin of error, but the standard error itself is determined by variability and sample size. The correct relationship is inverse: as sample size increases, standard error decreases. Study Guide references/topics: standard error, sample size, sampling variability, precision of estimates.


                                    NEW QUESTION # 70
                                    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 # 71
                                    A dataset: 2, 4, 6, 8, 10. Variance = ?

                                    Answer: D

                                    Explanation:
                                    Variance measures the average squared distance of data values from the mean. For the dataset 2, 4, 6, 8, 10, the mean is (2 + 4 + 6 + 8 + 10) ÷ 5 = 30 ÷ 5 = 6. The deviations from the mean are #4, #2, 0, 2, and 4.
                                    Squaring these deviations gives 16, 4, 0, 4, and 16. The sum of squared deviations is 40. Using the sample variance formula, divide by n # 1, where n = 5. Thus, sample variance = 40 ÷ 4 = 10. Option A is correct.
                                    Option C, 6.25, does not result from the standard sample variance computation for these values. The important distinction is whether a problem is using sample variance or population variance; the provided answer set and calculation use the sample variance formula. Study Guide references/topics: variance, mean, squared deviations, sample variance.


                                    NEW QUESTION # 72
                                    Binomial expected value = ?

                                    Answer: B

                                    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. The binomial model applies when there is a fixed number of independent trials, each trial has two outcomes, and the probability of success remains constant. The expected value represents the long-run average number of successes across repeated binomial experiments. For example, if a test has 20 independent questions and the probability of success on each is 0.75, the expected number correct is 20 × 0.75 = 15. Option B, n/p, and option C, p/n, do not represent the binomial mean. Option D, n + p, incorrectly adds the number of trials and success probability, which are not comparable units. The formula np captures both how many opportunities there are and how likely success is on each opportunity. Study Guide references/topics: binomial distribution, expected value, success probability, discrete random variables.


                                    NEW QUESTION # 73
                                    A researcher has collected information on students from a school. The researcher wants to display the ethnic groups represented in the school.
                                    Which pair of graphs both display data in this manner?

                                    Answer: B

                                    Explanation:
                                    Ethnic group is a categorical variable because it classifies students into named groups rather than measuring a numerical quantity. Categorical data are commonly displayed with bar graphs or pie charts. A bar graph shows the frequency or relative frequency of each category using separate bars, making it easy to compare group sizes. A pie chart shows how the whole student population is divided among categories, making it useful for displaying proportions or percentages. Therefore, the correct pair is bar graph and pie chart. A box plot is used for quantitative data and summarizes values using quartiles and a median, so it is not appropriate for ethnic categories. A line graph is typically used to show change over time or ordered numerical trends. A histogram is used for distributions of quantitative data grouped into intervals, not named categories. Since the goal is to display category membership, both selected graphs must support categorical frequency or percentage displays. References/topics from the Study Guide: categorical data displays, bar graphs, pie charts, relative frequency.


                                    NEW QUESTION # 74
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