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

SectionObjectives
Topic 1: Probability- Probability rules
  • 1. Addition and multiplication rules
    • 2. Bayes’ theorem (introductory level)
      - Fundamental probability concepts
      • 1. Conditional probability and independence
        • 2. Events and sample spaces
          Topic 2: 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)
                  Topic 3: Probability Distributions- Discrete distributions
                  • 1. Poisson distribution (introductory use cases)
                    • 2. Binomial distribution
                      - Continuous distributions
                      • 1. Standard normal and z-scores
                        • 2. Normal distribution
                          Topic 4: Statistical Inference- Estimation
                          • 1. Confidence intervals for means and proportions
                            - Hypothesis testing
                            • 1. Null and alternative hypotheses
                              • 2. t-tests and z-tests (basic application)
                                Topic 5: Regression and Correlation- Relationship analysis
                                • 1. Correlation coefficient interpretation
                                  • 2. Simple linear regression basics

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                                    Applied-Probability-and-Statistics Exam VCE: Applied Probability and Statistics (FZO1 C955) - Applied-Probability-and-Statistics Pass Guide & Applied-Probability-and-Statistics Study Guide

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                                    WGU Applied Probability and Statistics (FZO1 C955) Sample Questions (Q94-Q99):

                                    NEW QUESTION # 94
                                    Dataset: 5, 7, 7, 10. Standard deviation?

                                    Answer: C

                                    Explanation:
                                    The standard deviation measures the typical distance of data values from the mean. For the dataset 5, 7, 7, 10, the mean is (5 + 7 + 7 + 10) ÷ 4 = 29 ÷ 4 = 7.25. The deviations from the mean are #2.25, #0.25, #0.25, and
                                    2.75. Squaring these deviations gives 5.0625, 0.0625, 0.0625, and 7.5625. The sum of squared deviations is
                                    12.75. If treated as a sample, the variance is 12.75 ÷ 3 = 4.25, and the sample standard deviation is #4.25 #
                                    2.06. If rounded using the answer set provided, the closest available value is 2.16. The key conceptual point is that standard deviation cannot be 0 unless all values are identical, and it is not as large as 3 because the observations are relatively close to the mean. Study Guide references/topics: mean, variance, standard deviation, spread of data.


                                    NEW QUESTION # 95
                                    What is the product of 0.6 and 0.25?

                                    Answer: D

                                    Explanation:
                                    To multiply decimals, first multiply the numbers as whole numbers and then place the decimal point according to the total number of decimal places in the factors. The values are 0.6 and 0.25. Ignoring decimals temporarily, 6 × 25 = 150. The factor 0.6 has one decimal place, and 0.25 has two decimal places, for a total of three decimal places. Therefore, 150 becomes 0.150, which is equivalent to 0.15. A second way to verify the computation is to convert the decimals into fractions: 0.6 = 6/10 and 0.25 = 25/100. Multiplying gives (6 ×
                                    25)/(10 × 100) = 150/1000 = 0.15. This result is reasonable because one-fourth of 0.6 is 0.15. The other answer choices are too large for one-fourth of 0.6 or do not result from the correct decimal multiplication.
                                    References/topics from the Study Guide: decimal multiplication, fractions, equivalent forms, numerical operations.


                                    NEW QUESTION # 96
                                    Conditional probability P(A|B) = P(A and B)/P(B) #

                                    Answer: D

                                    Explanation:
                                    The formula for conditional probability is P(A|B) = P(A and B)/P(B), provided P(B) > 0. The notation P(A|B) is read as "the probability of A given B." The denominator P(B) restricts the sample space to cases in which B occurs, and the numerator P(A and B) counts the portion of that restricted group in which A also occurs.
                                    Therefore, the statement is true. Option B is incorrect because the formula is the standard definition of conditional probability. Option C is incorrect because if A and B are mutually exclusive, then P(A and B) = 0, which creates a special case rather than the general definition. Option D is invalid because conditional probability is undefined when P(B) = 0. The condition must have positive probability. Study Guide references
                                    /topics: conditional probability, joint probability, event intersection, probability rules.


                                    NEW QUESTION # 97
                                    A marketing analyst is studying the relationship between customer age groups, teens, adults, and seniors, and their preferred shopping methods, online and in-store.
                                    Which numerical measure is most appropriate for this study?

                                    Answer: D

                                    Explanation:
                                    This study involves two categorical variables: customer age group and preferred shopping method. Age group is categorical because customers are classified into groups such as teens, adults, and seniors. Shopping method is also categorical because customers are classified as preferring either online or in-store shopping.
                                    When two categorical variables are analyzed together, conditional percentages are the most appropriate numerical summary because they describe how the distribution of one categorical variable changes within levels of another categorical variable. For example, the analyst could compute the percentage of teens who prefer online shopping, the percentage of adults who prefer online shopping, and the percentage of seniors who prefer online shopping. A five-number summary is used for quantitative data, not categorical data. Mean difference requires numerical measurements. A correlation coefficient measures the strength and direction of a linear relationship between two quantitative variables, so it is not appropriate here. References/topics from the Study Guide: two-variable categorical data, conditional percentages, categorical association, numerical summaries.


                                    NEW QUESTION # 98
                                    In a game, a coin is tossed, and a spinner with 8 equal spaces numbered 1 through 8 is spun.
                                    What is the probability of getting heads on the coin and a number less than 3 on the spinner?

                                    Answer: A


                                    NEW QUESTION # 99
                                    ......

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