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

SectionObjectives
Descriptive Statistics- Two Variable Data Analysis
  • 1. Scatter plots interpretation
    • 2. Correlation
      • 3. Outliers and relationships
        - Single Variable Data Analysis
        • 1. Data visualization (histograms, box plots)
          • 2. Measures of central tendency (mean, median, mode)
            • 3. Measures of dispersion (variance, standard deviation, range)
              Probability Theory- Fundamental Probability Concepts
              • 1. Independent vs dependent events
                • 2. Basic probability rules
                  • 3. Conditional probability
                    - Probability Distributions
                    • 1. Binomial distribution basics
                      • 2. Normal distribution
                        Regression and Modeling- Linear Relationships
                        • 1. Simple linear regression
                          • 2. Slope and intercept interpretation
                            Statistical Inference- Hypothesis Testing (Introductory Level)
                            • 1. Null vs alternative hypothesis
                              • 2. p-values interpretation
                                - Estimation and Confidence Intervals
                                • 1. Point estimates
                                  • 2. Confidence interval interpretation

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                                    WGU Applied Probability and Statistics (FZO1 C955) Sample Questions (Q26-Q31):

                                    NEW QUESTION # 26
                                    Rare event count per interval modeled by:

                                    Answer: D

                                    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 # 27
                                    Which measure of central tendency is least affected by outliers?

                                    Answer: B

                                    Explanation:
                                    The median is the measure of central tendency least affected by outliers because it depends only on the ordered position of values, not on the numerical magnitude of extreme observations. To find the median, the data are arranged from least to greatest and the middle value is identified, or the average of the two middle values is taken when the sample size is even. If an extremely large or extremely small value is added to a data set, the mean can shift substantially because every value contributes to the arithmetic average. The median, however, usually remains stable unless the extreme value changes the middle position. The mode is also not directly affected by magnitude, but it may be absent or non-unique and is often less informative for numerical data. Range is not a measure of central tendency and is highly sensitive to outliers because it uses the minimum and maximum. Study Guide references/topics: descriptive statistics, measures of center, median, resistance to outliers.


                                    NEW QUESTION # 28
                                    What is the product of 0.6 and 0.25?

                                    Answer: C

                                    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 # 29
                                    A sample of 100 houses was surveyed in each of two states: Georgia and Kansas. Square footages of the houses are summarized by state in the following side-by-side box plots.

                                    What is the interquartile range for house sizes in Georgia?

                                    Answer: B

                                    Explanation:
                                    The interquartile range, or IQR, measures the spread of the middle 50% of a distribution. It is calculated as Q3
                                    # Q1, where Q1 is the first quartile and Q3 is the third quartile. In the Georgia box plot, the left edge of the box is labeled 800, representing Q1, and the right edge of the box is labeled 2800, representing Q3. Therefore, the interquartile range is 2800 # 800 = 2000 square feet. The minimum value, 500, and maximum value, 5000, are part of the full range, not the IQR. The median, 1200, identifies the center of the distribution but is not used directly in the IQR calculation. Option D, 4500, corresponds to the full range from 500 to 5000, not the interquartile range. The correct interpretation is that the middle half of Georgia house sizes spans 2000 square feet. References/topics from the Study Guide: box plots, quartiles, interquartile range, comparing distributions.


                                    NEW QUESTION # 30
                                    A child's parents want to analyze the relationship between the daily high temperature and ice cream sales at their child's ice cream stand. They create the following scatterplot.

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

                                    Answer: A

                                    Explanation:
                                    The correlation coefficient r measures both the direction and strength of a linear relationship between two quantitative variables. In this scatterplot, the points rise from lower left to upper right, showing a positive association between temperature and daily ice cream sales. As temperature increases, sales also tend to increase. The points are fairly close to an upward-sloping linear pattern, so the relationship is strong rather than weak. A value of r near 1 indicates a strong positive linear association, while a value near #1 indicates a strong negative association. Since the association is clearly positive, the negative options, #0.93 and #0.39, are not appropriate. Since the points show a strong trend rather than a loose or weak trend, 0.39 is too small.
                                    The best estimate is 0.93. This is consistent with the visual pattern: temperature explains a substantial amount of the linear movement in ice cream sales. References/topics from the Study Guide: scatterplots, correlation coefficient, positive association, strength of linear relationship.


                                    NEW QUESTION # 31
                                    ......

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