WGU Applied-Probability-and-Statistics Simulationsfragen - Applied-Probability-and-Statistics Exam

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

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

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                                    WGU Applied Probability and Statistics (FZO1 C955) Applied-Probability-and-Statistics Prüfungsfragen mit Lösungen (Q72-Q77):

                                    72. Frage
                                    Histogram vs bar chart:

                                    Antwort: D


                                    73. Frage
                                    A single ball is drawn from an opaque bag that contains red, blue, and green balls. The probability of drawing a red ball is .3, and the probability of drawing a blue ball is .6.
                                    What is the probability of drawing a green ball?

                                    Antwort: D

                                    Begründung:
                                    The probabilities of all possible outcomes in a sample space must sum to 1. In this experiment, the bag contains only red, blue, and green balls, so these three outcomes exhaust the sample space. The probability of drawing a red ball is 0.3, and the probability of drawing a blue ball is 0.6. Their combined probability is 0.3 +
                                    0.6 = 0.9. The remaining probability must belong to drawing a green ball. Therefore, P(green) = 1 # 0.9 = 0.1.
                                    This can also be viewed as a complement problem: green is the complement of drawing either red or blue when those are the only other colors available. Option B repeats the red probability, option C would make the total probability exceed 1, and option D is the combined probability of red or blue rather than green.
                                    References/topics from the Study Guide: probability sum rule, complements, sample space, mutually exclusive outcomes.


                                    74. Frage
                                    Review the following inequality:
                                    y < x # 1/2
                                    Which shaded portion in the graphs corresponds to this inequality?



                                    Antwort: D

                                    Begründung:
                                    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.


                                    75. Frage
                                    Regression intercept represents:

                                    Antwort: A

                                    Begründung:
                                    In a linear regression equation, usually written as # = b# + b#x, the intercept b# represents the predicted value of Y when X equals 0. It is the point where the regression line crosses the vertical axis. For example, if a model is # = 12 + 3x, the intercept 12 means the predicted response is 12 when x = 0. The slope, b#, is different; it represents the predicted change in Y for each one-unit increase in X. Correlation measures the strength and direction of a linear association, not the intercept. The mean is a measure of center for a variable and is not the same as a regression intercept. In applied settings, the intercept is meaningful only when X = 0 is within a realistic or relevant range of the data. Study Guide references/topics: linear regression, intercept interpretation, slope-intercept form, response prediction.


                                    76. Frage
                                    Determine x:
                                    4 + x = 6 # x

                                    Antwort: C

                                    Begründung:
                                    The equation 4 + x = 6 # x is a linear equation in one variable. To solve it, collect variable terms on one side and constant terms on the other. Add x to both sides to eliminate the negative x on the right: 4 + 2x = 6. Then subtract 4 from both sides: 2x = 2. Finally, divide both sides by 2, giving x = 1. This value can be verified directly in the original equation. Substituting x = 1 gives 4 + 1 = 5 on the left and 6 # 1 = 5 on the right, so both sides are equal. Option A gives 4 = 6, which is false. Option C gives 6 = 4, also false. Option D gives 9 =
                                    1, which is not valid. The correct solution is the value that balances both sides of the equation. References
                                    /topics from the Study Guide: basic algebra, solving linear equations, inverse operations, substitution checks.


                                    77. Frage
                                    ......

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