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

SectionObjectives
Topic 1: Descriptive Statistics- Data visualization
  • 1. Histograms and frequency distributions
    • 2. Box plots and interpretation
      - Data summarization
      • 1. Measures of central tendency (mean, median, mode)
        • 2. Measures of variability (range, variance, standard deviation)
          Topic 2: Probability Distributions- Continuous distributions
          • 1. Standard normal and z-scores
            • 2. Normal distribution
              - Discrete distributions
              • 1. Binomial distribution
                • 2. Poisson distribution (introductory use cases)
                  Topic 3: Regression and Correlation- Relationship analysis
                  • 1. Correlation coefficient interpretation
                    • 2. Simple linear regression basics
                      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: Probability- Fundamental probability concepts
                            • 1. Conditional probability and independence
                              • 2. Events and sample spaces
                                - Probability rules
                                • 1. Addition and multiplication rules
                                  • 2. Bayes’ theorem (introductory level)

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                                    WGU Applied Probability and Statistics (FZO1 C955) Sample Questions (Q22-Q27):

                                    NEW QUESTION # 22
                                    A commuter has a .4 probability of taking the bus to work, a .4 probability of driving a car, and a .2 probability of cycling. The probability of being late is .15 when taking the bus, .05 when driving a car, and .1 when cycling.
                                    What is the probability of taking the bus and being on time, or driving a car and being on time?

                                    Answer: C

                                    Explanation:
                                    This item requires multiplying conditional probabilities and then adding mutually exclusive outcomes.
                                    "Taking the bus and being on time" means the commuter takes the bus and is not late. Since the probability of being late by bus is .15, the probability of being on time by bus is 1 # .15 = .85. Therefore, P(bus and on time)
                                    = .4 × .85 = .34. For driving, the probability of being late is .05, so the probability of being on time is 1 # .05
                                    = .95. Therefore, P(car and on time) = .4 × .95 = .38. Because a commuter cannot both take the bus and drive a car on the same trip, the events are mutually exclusive. Add the two joint probabilities: .34 + .38 = .72. The cycling information is not used because the question asks only about bus-on-time or car-on-time outcomes.
                                    References/topics from the Study Guide: probability rules, complements, conditional probability, mutually exclusive events.


                                    NEW QUESTION # 23
                                    There are 12 cell phone charging cords available at a store for purchase. The length of each charging cord in inches is reflected as 3, 3, 4, 6, 6, 6, 6, 7, 10, 10, 11, and 12, respectively.
                                    What are the mean of these data?

                                    Answer: B

                                    Explanation:
                                    The mean is the arithmetic average of a data set. To find it, add all values and divide by the number of values.
                                    The cord lengths are 3, 3, 4, 6, 6, 6, 6, 7, 10, 10, 11, and 12. Their sum is 84. Since there are 12 charging cords, divide 84 by 12 to obtain 7. Therefore, the mean cord length is 7 inches. This value represents the balance point of the distribution, not necessarily a value that must occur most often. In this data set, 6 appears most frequently, so 6 is the mode, but the question asks for the mean. Option B, 8, and option C, 9, are too large because several values are below 7. Option D, 6, identifies the most common value rather than the average. References/topics from the Study Guide: mean, measures of center, quantitative data, arithmetic average.


                                    NEW QUESTION # 24
                                    Confidence interval = sample mean ± ?

                                    Answer: C

                                    Explanation:
                                    A confidence interval for a population mean is generally constructed as sample mean ± margin of error. The margin of error equals a critical value multiplied by the standard error. Therefore, the structure is sample mean ± critical value × SE. The critical value depends on the confidence level and distribution used, such as a z critical value when the population standard deviation is known or a t critical value when it is unknown. The standard error measures the sampling variability of the sample mean, often computed as s/#n when using sample standard deviation. Option B is incorrect because variance times sample size is not a margin of error.
                                    Option C is incomplete because standard deviation alone measures spread among data values, not uncertainty of the sample mean. Option D is incorrect because the median is a measure of center and is not the typical component of a mean-based confidence interval. Study Guide references/topics: confidence intervals, standard error, critical value, margin of error.


                                    NEW QUESTION # 25
                                    Review the following inequality:
                                    y < x # 1/2
                                    Which shaded portion in the graphs corresponds to this inequality?



                                    Answer: D

                                    Explanation:
                                    The inequality y < x # 1/2 has boundary line y = x # 1/2. This line has slope 1 and y-intercept #1/2, so it crosses the y-axis slightly below the origin and rises one unit for every one unit moved to the right. Because the inequality is strict, using " < " rather than "#," the boundary line must be dashed, showing that points on the line are not included in the solution set. The solution region must be shaded below the line because y is less than the expression x # 1/2. A useful verification method is the test point (0, 0). Substituting gives 0 < 0 #
                                    1/2, or 0 < #1/2, which is false. Therefore, the region containing the origin should not be shaded. The fourth graph has the dashed boundary with intercept #1/2 and shades the region below the line while excluding the origin. References/topics from the Study Guide: graphing linear inequalities, slope-intercept form, dashed boundaries, test-point method.


                                    NEW QUESTION # 26
                                    In hypothesis testing, rejecting H# when true = ?

                                    Answer: C

                                    Explanation:
                                    A Type I error occurs when the null hypothesis, H#, is true but the test decision rejects it. In plain statistical language, this is a false positive: the analysis concludes that there is evidence of an effect, difference, or relationship when in reality the null condition is true. The probability of making a Type I error is denoted by
                                    #, the significance level, commonly set at 0.05. A Type II error is different; it occurs when the null hypothesis is false but the test fails to reject it. That is a false negative. Option C is incorrect because rejecting a true null is not a correct decision. Option D describes not rejecting or accepting the null, not the stated event. The critical phrase is "rejecting H# when true," which directly defines a Type I error. Study Guide references
                                    /topics: hypothesis testing, null hypothesis, Type I error, significance level.


                                    NEW QUESTION # 27
                                    ......

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