Pass Guaranteed Quiz WGU Applied-Probability-and-Statistics - Applied Probability and Statistics (FZO1 C955) Pass-Sure Exam Preparation

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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: Probability Distributions- Continuous distributions
      • 1. Normal distribution
        • 2. Standard normal and z-scores
          - Discrete distributions
          • 1. Binomial distribution
            • 2. Poisson distribution (introductory use cases)
              Topic 3: 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 4: 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
                            Topic 5: Descriptive Statistics- Data summarization
                            • 1. Measures of central tendency (mean, median, mode)
                              • 2. Measures of variability (range, variance, standard deviation)
                                - Data visualization
                                • 1. Histograms and frequency distributions
                                  • 2. Box plots and interpretation

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                                    2026 Applied-Probability-and-Statistics Exam Preparation | Pass-Sure Applied-Probability-and-Statistics: Applied Probability and Statistics (FZO1 C955) 100% Pass

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                                    WGU Applied Probability and Statistics (FZO1 C955) Sample Questions (Q151-Q156):

                                    NEW QUESTION # 151
                                    Probability of rolling an odd number on a die:

                                    Answer: C

                                    Explanation:
                                    A standard six-sided die has six equally likely outcomes: 1, 2, 3, 4, 5, and 6. The odd outcomes are 1, 3, and
                                    5. Thus, there are 3 favorable outcomes out of 6 possible outcomes. The probability is 3/6, which simplifies to
                                    1/2. This means an odd number is just as likely as an even number on a fair die. Option B, 1/3, would represent 2 favorable outcomes out of 6, which is not correct. Option C, 1/6, is the probability of rolling one specific number, such as only a 1. Option D, 2/3, would require 4 favorable outcomes out of 6. Since exactly half the faces are odd, the probability is one-half. Study Guide references/topics: theoretical probability, equally likely outcomes, sample space, favorable outcomes.


                                    NEW QUESTION # 152
                                    A school surveyed student participation in extracurricular activities. The survey found:
                                    * The drama club had 50% of students participate.
                                    * The science club had 30% of students participate.
                                    * Both clubs had 15% of students participate.
                                    What is the probability that a student participated in the drama club, given that they attended the science club?

                                    Answer: A

                                    Explanation:
                                    This question asks for a conditional probability. The phrase "given that they attended the science club" means the science club group becomes the restricted reference group. The required probability is P(drama club | science club), which is calculated as P(drama and science) divided by P(science). The problem states that 15% of students participated in both clubs, so P(drama and science) = 0.15. It also states that 30% participated in the science club, so P(science) = 0.30. Therefore, P(drama | science) = 0.15 ÷ 0.30 = 0.50. This means that among students who attended the science club, half also participated in drama club. Option A gives the joint probability, not the conditional probability. Option B gives only the science club participation rate. Option C does not match the conditional probability calculation. References/topics from the Study Guide: conditional probability, joint probability, probability ratios, two-event probability.


                                    NEW QUESTION # 153
                                    Determine z in the equation:
                                    1/(6z) = 2/9

                                    Answer: D

                                    Explanation:
                                    The equation 1/(6z) = 2/9 is a proportion because it sets two fractions equal to each other. To solve it, use cross multiplication. Multiply the numerator of the first fraction by the denominator of the second fraction, and multiply the denominator of the first fraction by the numerator of the second fraction: 1 × 9 = 2 × 6z. This gives 9 = 12z. To isolate z, divide both sides by 12: z = 9/12. This fraction can also be simplified to 3/4, but the answer choices list the unsimplified equivalent form 9/12. The other options do not satisfy the original equation. For example, if z = 2/54, then 6z is very small and the left side becomes much larger than 2/9. If z =
                                    12/9 or 18/2, the denominator becomes too large, making the left side too small. References/topics from the Study Guide: proportions, solving equations, cross multiplication, equivalent fractions.


                                    NEW QUESTION # 154
                                    A fitness center owner notices that gym attendance increases as the number of daylight hours increases. The owner calculates a correlation coefficient between daylight hours and gym attendance of r = 0.72.
                                    Based on this information, what can be concluded?

                                    Answer: A

                                    Explanation:
                                    The correlation coefficient r measures the direction and strength of a linear association between two quantitative variables. Since r = 0.72 is positive, the relationship is positive: as daylight hours increase, gym attendance tends to increase. The value 0.72 also indicates a moderately strong to strong linear association because it is closer to 1 than to 0. However, correlation alone does not establish causation. Even though daylight hours and gym attendance move together, other variables could influence attendance, such as weather, seasonal routines, work schedules, or fitness promotions. Therefore, the valid conclusion is that there is a positive association, not a proven causal relationship. Options A and B are incorrect because they describe a negative relationship, which conflicts with the positive correlation coefficient. Option D overstates the evidence by claiming causation. References/topics from the Study Guide: correlation coefficient, positive association, linear relationship, correlation versus causation.


                                    NEW QUESTION # 155
                                    Rare event count per interval modeled by:

                                    Answer: A

                                    Explanation:
                                    The Poisson distribution is used to model the number of events occurring in a fixed interval of time, space, area, or volume when the events occur independently at a constant average rate. It is especially common for rare event counts, such as calls arriving at a help desk per hour, accidents at an intersection per month, defects per production batch, or website errors per day. The defining parameter of the Poisson distribution is #, the average number of events per interval. A binomial distribution instead models the number of successes in a fixed number of independent trials with a constant probability of success. A normal distribution models continuous, bell-shaped measurements. A uniform distribution assigns equal probability across outcomes or intervals. Because the prompt specifically says "rare event count per interval," the technical match is the Poisson distribution. Study Guide references/topics: Poisson distribution, event counts, rate parameter #, discrete probability distributions.


                                    NEW QUESTION # 156
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