시험대비Applied-Probability-and-Statistics인기자격증시험대비공부자료최신덤프

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

SectionObjectives
Descriptive Statistics- Data summarization
  • 1. Measures of variability (range, variance, standard deviation)
    • 2. Measures of central tendency (mean, median, mode)
      - Data visualization
      • 1. Box plots and interpretation
        • 2. Histograms and frequency distributions
          Probability Distributions- Continuous distributions
          • 1. Normal distribution
            • 2. Standard normal and z-scores
              - Discrete distributions
              • 1. Binomial distribution
                • 2. Poisson distribution (introductory use cases)
                  Probability- Fundamental probability concepts
                  • 1. Conditional probability and independence
                    • 2. Events and sample spaces
                      - Probability rules
                      • 1. Addition and multiplication rules
                        • 2. Bayes’ theorem (introductory level)
                          Statistical Inference- Estimation
                          • 1. Confidence intervals for means and proportions
                            - Hypothesis testing
                            • 1. Null and alternative hypotheses
                              • 2. t-tests and z-tests (basic application)
                                Regression and Correlation- Relationship analysis
                                • 1. Correlation coefficient interpretation
                                  • 2. Simple linear regression basics

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                                    최신 Courses and Certificates Applied-Probability-and-Statistics 무료샘플문제 (Q142-Q147):

                                    질문 # 142
                                    Confidence interval = sample mean ± ?

                                    정답：A

                                    설명：
                                    A confidence interval for a population mean is generally constructed as sample mean ± margin of error. The margin of error equals a critical value multiplied by the standard error. Therefore, the structure is sample mean ± critical value × SE. The critical value depends on the confidence level and distribution used, such as a z critical value when the population standard deviation is known or a t critical value when it is unknown. The standard error measures the sampling variability of the sample mean, often computed as s/#n when using sample standard deviation. Option B is incorrect because variance times sample size is not a margin of error.
                                    Option C is incomplete because standard deviation alone measures spread among data values, not uncertainty of the sample mean. Option D is incorrect because the median is a measure of center and is not the typical component of a mean-based confidence interval. Study Guide references/topics: confidence intervals, standard error, critical value, margin of error.


                                    질문 # 143
                                    Z-score negative #

                                    정답：C

                                    설명：
                                    A z-score measures how many standard deviations a data value is from the mean. The formula is z = (x # #)/#, where x is the observed value, # is the mean, and # is the standard deviation. Since standard deviation is positive, the sign of the z-score depends on the numerator, x # #. If x is less than the mean, then x # # is negative, producing a negative z-score. Therefore, a negative z-score indicates that the observed value is below the mean. A positive z-score indicates a value above the mean, while a z-score of 0 indicates a value exactly equal to the mean. Option D is incorrect because the sign of the z-score gives direct positional information relative to the mean. Study Guide references/topics: z-scores, standard normal distribution, mean, standard deviation.


                                    질문 # 144
                                    Probability of exactly 1 head in 2 coin flips = ?

                                    정답：C

                                    설명：
                                    Two coin flips produce four equally likely ordered outcomes: HH, HT, TH, and TT. Exactly one head occurs in two of these outcomes: HT and TH. Therefore, the probability is 2 favorable outcomes out of 4 total outcomes, or 2/4 = 1/2. This can also be computed using the binomial model. There are n = 2 independent trials, success probability p = 1/2, and exactly one success is required. The binomial calculation is C(2,1)(1/2)