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

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

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                                    WGU Applied Probability and Statistics (FZO1 C955) Sample Questions (Q74-Q79):

                                    NEW QUESTION # 74
                                    Regression intercept represents:

                                    Answer: C

                                    Explanation:
                                    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.


                                    NEW QUESTION # 75
                                    A golf course is attempting to correlate golfing handicap with math SAT scores among local high school golfers. Ignoring potential confounding variables such as socioeconomic status, the golf course creates the following scatterplot.

                                    What is the estimated value of r, the correlation coefficient, between these variables?

                                    Answer: C

                                    Explanation:
                                    The correlation coefficient r measures the direction and strength of a linear relationship between two quantitative variables. In the scatterplot, the points are widely dispersed, so the relationship is weak rather than strong. The fitted trend line slopes slightly downward, indicating a negative association: as golf handicap increases, math SAT score tends to decrease slightly. Because the pattern is weak and negative, r should be close to 0 but less than 0. The best match is #0.10. Option A, #0.63, would represent a moderately strong negative linear relationship, which would require the points to cluster more tightly around a downward- sloping line. Option C, 0.10, has the right weak magnitude but the wrong direction because it is positive.
                                    Option D, 0.63, is both too strong and positive. The visual evidence supports only a very slight negative linear association. References/topics from the Study Guide: scatterplots, correlation coefficient, positive and negative association, strength of linear relationship.


                                    NEW QUESTION # 76
                                    Probability of rolling an odd number on a die:

                                    Answer: A

                                    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 # 77
                                    Probability of drawing red or black card = ?

                                    Answer: C

                                    Explanation:
                                    In a standard deck of playing cards, every card is either red or black. Red cards consist of hearts and diamonds, and black cards consist of clubs and spades. There are 26 red cards and 26 black cards, for a total of 52 cards. The event "red or black" includes all possible cards in the deck. Therefore, the probability is 52 favorable outcomes out of 52 total outcomes, which equals 1. A probability of 1 means the event is certain.
                                    Option B, 1/2, would be the probability of drawing a red card alone or a black card alone, not red or black.
                                    Option C would mean the event is impossible, which is false. Option D would correspond to one suit out of four, such as hearts only. The word "or" combines both color categories, covering the entire sample space.
                                    Study Guide references/topics: sample space, certainty, addition rule, card probability.


                                    NEW QUESTION # 78
                                    A home inspector finds 3% of the homes in a community infected with termites.
                                    How should the home inspector's findings be interpreted?

                                    Answer: B

                                    Explanation:
                                    A probability or percentage describes how often an event is expected to occur in the long run. Here, 3% of homes are infected with termites. As a probability, this is 0.03, meaning about 3 out of every 100 homes would be expected to have termites. This is a small probability, so the event should be interpreted as unlikely.
                                    It is not impossible, because impossible would require a probability of 0%. It is also not likely, because likely events generally have probabilities substantially greater than 50%. Finally, it is not "as likely as unlikely," because that language corresponds to a probability near 50%, where occurrence and nonoccurrence are approximately balanced. Since 3% is close to zero but not equal to zero, the technically correct interpretation is that termite infection is unlikely for a randomly selected home in the community. References/topics from the Study Guide: probability interpretation, percentages, unlikely events, complementary probability.


                                    NEW QUESTION # 79
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