Applied-Probability-and-Statistics Valid Braindumps Sheet - Applied-Probability-and-Statistics Valid Exam Sample

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

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                                    Applied-Probability-and-Statistics Valid Exam Sample - Valid Applied-Probability-and-Statistics Exam Dumps

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                                    WGU Applied Probability and Statistics (FZO1 C955) Sample Questions (Q153-Q158):

                                    NEW QUESTION # 153
                                    Boxplot shows:

                                    Answer: D

                                    Explanation:
                                    A boxplot summarizes the distribution of a quantitative variable using key positional statistics. It displays the median, first quartile, third quartile, and typically the minimum and maximum non-outlier values. It may also mark outliers separately. The box itself spans from Q1 to Q3, representing the interquartile range, or middle
                                    50% of the data. The line inside the box marks the median. Whiskers extend to values within the non-outlier range, depending on the graphing convention. A boxplot does not primarily show frequency counts; histograms, dot plots, and bar charts are better for frequencies. A scatterplot displays the relationship between two quantitative variables. Probability is not directly displayed by a standard boxplot, although distributional interpretation can be supported by it. The correct answer is therefore median, quartiles, and outliers. Study Guide references/topics: boxplots, five-number summary, quartiles, outliers.


                                    NEW QUESTION # 154
                                    Variance formula = ?

                                    Answer: C

                                    Explanation:
                                    The sample variance formula is s² = #(x# # x#)² / (n # 1). In this formula, x# represents each data value, x# is the sample mean, and n is the sample size. The expression x# # x# gives each value's deviation from the mean. Squaring the deviations prevents negative and positive deviations from canceling and emphasizes larger departures. Dividing by n # 1 gives the sample variance, using degrees of freedom to correct bias when estimating population variance from a sample. Option B is the formula for the sample mean, not variance.
                                    Option C squares the mean and does not measure spread. Option D resembles part of the standard deviation process but omits division by n # 1 and is not the variance formula. Variance is foundational because standard deviation is the square root of variance. Study Guide references/topics: variance, sample variance formula, mean deviations, measures of spread.


                                    NEW QUESTION # 155
                                    Standard error decreases when:

                                    Answer: D

                                    Explanation:
                                    The standard error of the sample mean is calculated as SE = s/#n, where s is the sample standard deviation and n is the sample size. Since n appears in the denominator, increasing the sample size reduces the standard error, assuming the standard deviation stays constant. This reflects the fact that larger samples produce more stable estimates of the population mean. Option B is incorrect because decreasing sample size increases standard error. Option C is incorrect because a larger standard deviation increases standard error by increasing the numerator. Option D is incorrect because the mean affects the center of the distribution but does not directly determine the standard error. Standard error is about precision: smaller standard error means less sampling variability and a more precise estimate. That is why larger samples are preferred in inference. Study Guide references/topics: standard error, sample size, standard deviation, sampling variability.


                                    NEW QUESTION # 156
                                    Expected value of X = 1×0.2 + 2×0.5 + 3×0.3 = ?

                                    Answer: D

                                    Explanation:
                                    Expected value is the long-run average value of a random variable. For a discrete random variable, it is calculated by multiplying each possible value by its probability and then adding those products. Here, the expression is already structured as an expected value calculation: 1×0.2 + 2×0.5 + 3×0.3. Compute each product: 1×0.2 = 0.2, 2×0.5 = 1.0, and 3×0.3 = 0.9. Add them: 0.2 + 1.0 + 0.9 = 2.1. Therefore, the expected value is 2.1. This does not mean the random variable must equal 2.1 in a single trial; it means that over many repetitions, the average outcome would approach 2.1. Option B is close but omits part of the weighted contribution. Options C and D do not match the weighted-average computation. Study Guide references
                                    /topics: expected value, discrete random variables, weighted average, probability distributions.


                                    NEW QUESTION # 157
                                    A recording studio raises its use fee to $75 and charges $40 per hour for studio time. The equation of the total cost of a recording session as a function of studio time is y = 40x + 75.
                                    Which graph represents this equation?



                                    Answer: C

                                    Explanation:
                                    The equation y = 40x + 75 is written in slope-intercept form, y = mx + b. In this form, m represents the rate of change and b represents the initial value. The constant term 75 means the graph must cross the y-axis at 75, because the studio charges $75 before any hourly time is added. The coefficient 40 means that for every additional hour of studio time, the total cost increases by $40. Therefore, the correct graph must begin at y =
                                    75 when x = 0 and rise at a steady linear rate of 40 dollars per hour. For example, at x = 6 hours, the model gives y = 40(6) + 75 = 315, so the line should pass near the point (6, 315). Among the displayed graphs, Graph 4 matches both the y-intercept and the slope. References/topics from the Study Guide: basic algebra, linear equations, slope-intercept form, interpreting rate of change.


                                    NEW QUESTION # 158
                                    ......

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