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

SectionObjectives
Topic 1: Regression and Modeling- Linear Relationships
  • 1. Simple linear regression
    • 2. Slope and intercept interpretation
      Topic 2: Descriptive Statistics- Two Variable Data Analysis
      • 1. Outliers and relationships
        • 2. Correlation
          • 3. Scatter plots interpretation
            - Single Variable Data Analysis
            • 1. Measures of central tendency (mean, median, mode)
              • 2. Data visualization (histograms, box plots)
                • 3. Measures of dispersion (variance, standard deviation, range)
                  Topic 3: Statistical Inference- Estimation and Confidence Intervals
                  • 1. Confidence interval interpretation
                    • 2. Point estimates
                      - Hypothesis Testing (Introductory Level)
                      • 1. p-values interpretation
                        • 2. Null vs alternative hypothesis
                          Topic 4: Probability Theory- Probability Distributions
                          • 1. Normal distribution
                            • 2. Binomial distribution basics
                              - Fundamental Probability Concepts
                              • 1. Conditional probability
                                • 2. Basic probability rules
                                  • 3. Independent vs dependent events

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                                    Applied Probability and Statistics (FZO1 C955)latest test questions & Applied-Probability-and-Statistics reliable braindumps & Applied Probability and Statistics (FZO1 C955)free practice dumps

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                                    WGU Applied Probability and Statistics (FZO1 C955) Sample Questions (Q90-Q95):

                                    NEW QUESTION # 90
                                    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 # 91
                                    Given a normal distribution with a mean of 40 and a standard deviation of 6, what is the range that contains approximately 95% of the data?

                                    Answer: B

                                    Explanation:
                                    For a normal distribution, the empirical rule states that approximately 95% of the data fall within two standard deviations of the mean. The mean is 40, and the standard deviation is 6. Two standard deviations equal 2 × 6
                                    = 12. To construct the 95% interval, subtract and add 12 from the mean: 40 # 12 = 28 and 40 + 12 = 52.
                                    Therefore, the range containing approximately 95% of the data is 28 to 52. Option D, 34 to 46, represents one standard deviation from the mean and corresponds to about 68% of the data. Option B, 22 to 58, represents three standard deviations from the mean and corresponds to approximately 99.7% of the data. Option C is not based on the stated standard deviation. The correct interval must be symmetric around the mean and extend exactly two standard deviations in each direction. References/topics from the Study Guide: normal distribution, empirical rule, mean, standard deviation.


                                    NEW QUESTION # 92
                                    The average lifespan of a dalmatian is 11.5 years, with a standard deviation of 1.5 years.
                                    What are the two values between which 95% of the data falls for the average lifespan of a dalmatian, assuming a normal distribution?

                                    Answer: A

                                    Explanation:
                                    For a normal distribution, the empirical rule states that approximately 95% of observations lie within two standard deviations of the mean. The mean lifespan is 11.5 years, and the standard deviation is 1.5 years. Two standard deviations equal 2 × 1.5 = 3.0 years. Therefore, the interval containing approximately 95% of the data is found by subtracting and adding 3.0 years to the mean: 11.5 # 3.0 = 8.5 and 11.5 + 3.0 = 14.5. The resulting interval is 8.5 years to 14.5 years. Option C, 10.0 to 13.0, represents one standard deviation from the mean and would correspond to about 68% of the data. Options A and D are not centered correctly at the proper two-standard-deviation distance. The correct interval must be symmetric around the mean and use two standard deviations. References/topics from the Study Guide: normal distributions, empirical rule, standard deviation, measures of spread.


                                    NEW QUESTION # 93
                                    Type II error = ?

                                    Answer: B

                                    Explanation:
                                    A Type II error occurs when the null hypothesis is false, but the test fails to reject it. Many introductory materials describe this as "accepting H# when false," although the more precise statistical wording is "failing to reject H#." This is a false negative: a real effect, difference, or relationship exists, but the test does not detect enough evidence to conclude it. For example, if a new teaching method truly improves scores but the test fails to find significance, the result is a Type II error. Option B describes a Type I error, which is rejecting a true null hypothesis. Option C is a correct test decision, not an error. Option D is invalid because Type II error is a defined concept. The probability of Type II error is #, and statistical power is 1 # #. Study Guide references/topics: hypothesis testing, Type II error, null hypothesis, statistical power.


                                    NEW QUESTION # 94
                                    A researcher has collected information on students from a school. The researcher wants to display the ethnic groups represented in the school.
                                    Which pair of graphs both display data in this manner?

                                    Answer: C

                                    Explanation:
                                    Ethnic group is a categorical variable because it classifies students into named groups rather than measuring a numerical quantity. Categorical data are commonly displayed with bar graphs or pie charts. A bar graph shows the frequency or relative frequency of each category using separate bars, making it easy to compare group sizes. A pie chart shows how the whole student population is divided among categories, making it useful for displaying proportions or percentages. Therefore, the correct pair is bar graph and pie chart. A box plot is used for quantitative data and summarizes values using quartiles and a median, so it is not appropriate for ethnic categories. A line graph is typically used to show change over time or ordered numerical trends. A histogram is used for distributions of quantitative data grouped into intervals, not named categories. Since the goal is to display category membership, both selected graphs must support categorical frequency or percentage displays. References/topics from the Study Guide: categorical data displays, bar graphs, pie charts, relative frequency.


                                    NEW QUESTION # 95
                                    ......

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