Applied-Probability-and-Statistics Test Dates - Applied-Probability-and-Statistics Reliable Exam Book

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

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

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                                    WGU Applied Probability and Statistics (FZO1 C955) Sample Questions (Q91-Q96):

                                    NEW QUESTION # 91
                                    There are 20 men in a room whose heights are reflected in inches as 68, 70, 73, 67, 71, 68, 76, 70, 73, 66, 68,
                                    69, 71, 74, 73, 72, 65, 60, 70, and 78 inches respectively.
                                    What is the median of these data?

                                    Answer: C

                                    Explanation:
                                    The median is the middle value of an ordered data set. Because there are 20 observations, the number of data values is even, so the median is the average of the 10th and 11th values after the data are arranged from least to greatest. Ordering the heights gives 60, 65, 66, 67, 68, 68, 68, 69, 70, 70, 70, 71, 71, 72, 73, 73, 73, 74, 76,
                                    78. The 10th value is 70, and the 11th value is also 70. The median is therefore (70 + 70) ÷ 2 = 70. This value divides the ordered heights into two equal halves: ten values are at or below 70, and ten values are at or above
                                    70. The median is resistant to extreme values, so the low value 60 and the high value 78 do not distort it the way they could affect the mean. References/topics from the Study Guide: median, ordered data, measures of center, quantitative data.


                                    NEW QUESTION # 92
                                    What is the mode of this dataset: 3, 5, 7, 7, 10?

                                    Answer: D

                                    Explanation:
                                    The mode is the value that occurs most frequently in a data set. In the set 3, 5, 7, 7, 10, the value 3 appears once, 5 appears once, 10 appears once, and 7 appears twice. Since 7 has the highest frequency, it is the mode.
                                    This question tests recognition of a measure of center that differs from the mean and median. The mean would require summing all values and dividing by the number of observations, while the median would identify the middle value after ordering the data. The data are already ordered, and the middle value is also 7, but the reason the correct answer is 7 here is specifically because it appears more often than any other value. Options A, B, and D each name values that occur only once, so none can be the mode. A dataset may have one mode, multiple modes, or no mode, but this dataset is unimodal. References/topics from the Study Guide: descriptive statistics, measures of center, frequency, mode.


                                    NEW QUESTION # 93
                                    Probability of rolling 1, 2, or 3 on die = ?

                                    Answer: D

                                    Explanation:
                                    A standard six-sided die has six equally likely outcomes: 1, 2, 3, 4, 5, and 6. The event "rolling 1, 2, or 3" has three favorable outcomes: 1, 2, and 3. The probability is therefore favorable outcomes divided by total outcomes: 3/6. This fraction simplifies to 1/2. Option B, 1/3, would correspond to two favorable outcomes out of six. Option C, 1/6, is the probability of rolling one specific number only. Option D, 2/3, would require four favorable outcomes out of six. Since exactly half of the die faces are 1, 2, or 3, the correct probability is one- half. This is a direct application of theoretical probability with equally likely outcomes. Study Guide references/topics: die probability, favorable outcomes, sample space, theoretical probability.


                                    NEW QUESTION # 94
                                    Best chart for categorical data?

                                    Answer: D

                                    Explanation:
                                    A bar chart is the best display for categorical data because it shows the frequency or relative frequency of each category using separate bars. Categorical variables classify observations into groups, such as favorite color, type of transportation, political affiliation, or product category. A bar chart allows the viewer to compare category counts directly by bar height. A histogram is not appropriate because it is used for quantitative data grouped into numerical intervals. A scatterplot is used to examine the relationship between two quantitative variables, such as height and weight. A boxplot summarizes a quantitative distribution using quartiles, median, spread, and outliers. Since the question asks specifically about categorical data, the display must preserve category labels rather than numerical intervals or continuous measurement. Therefore, the bar chart is the correct choice. Study Guide references/topics: categorical data, bar charts, frequency displays, descriptive statistics.


                                    NEW QUESTION # 95
                                    Empirical probability = ?

                                    Answer: D

                                    Explanation:
                                    Empirical probability is probability determined from observed data rather than from a purely theoretical model. It is calculated by dividing the number of times an event actually occurs by the total number of trials or observations. For example, if a basketball player makes 72 free throws in 100 attempts, the empirical probability of a made free throw is 72/100 = 0.72. This differs from theoretical probability, which is derived from known equally likely outcomes, such as rolling a 3 on a fair six-sided die. It also differs from a guess or subjective estimate because empirical probability requires actual recorded evidence. The term "uniform" describes a distribution in which outcomes or intervals have equal probability, not the basis for empirical probability. Since the question asks for the definition of empirical probability, the correct selection is observed data. Study Guide references/topics: empirical probability, relative frequency, observed outcomes, probability interpretation.


                                    NEW QUESTION # 96
                                    ......

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