Applied-Probability-and-Statistics学習教材、Applied-Probability-and-Statistics模擬練習

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

SectionObjectives
Probability Theory- Fundamental Probability Concepts
  • 1. Basic probability rules
    • 2. Conditional probability
      • 3. Independent vs dependent events
        - Probability Distributions
        • 1. Normal distribution
          • 2. Binomial distribution basics
            Regression and Modeling- Linear Relationships
            • 1. Slope and intercept interpretation
              • 2. Simple linear regression
                Descriptive Statistics- 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)
                      - Two Variable Data Analysis
                      • 1. Scatter plots interpretation
                        • 2. Correlation
                          • 3. Outliers and relationships
                            Statistical Inference- Estimation and Confidence Intervals
                            • 1. Point estimates
                              • 2. Confidence interval interpretation
                                - Hypothesis Testing (Introductory Level)
                                • 1. p-values interpretation
                                  • 2. Null vs alternative hypothesis

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                                    Applied-Probability-and-Statistics　Applied Probability and Statistics (FZO1 C955)問題と回答、Applied-Probability-and-Statisticsテスト練習

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                                    WGU Applied Probability and Statistics (FZO1 C955) 認定 Applied-Probability-and-Statistics 試験問題 (Q33-Q38):

                                    質問 # 33
                                    Correlation coefficient = #0.7. This indicates:

                                    正解：C

                                    解説：
                                    The correlation coefficient r measures the direction and strength of a linear relationship between two quantitative variables. Values of r range from #1 to 1. A negative value indicates that as one variable increases, the other variable tends to decrease. The value #0.7 is fairly close to #1, so it represents a strong negative linear relationship. It is not perfect, because perfect negative correlation would be r = #1, but it is clearly stronger than a weak association. Option B is incorrect because the sign is negative, not positive.
                                    Option C is incorrect because no linear relationship would be represented by a correlation near 0. Option D is incorrect both in direction and strength. A scatterplot with r = #0.7 would generally show points trending downward from left to right, with some scatter around the trend. Study Guide references/topics: correlation coefficient, negative association, linear relationships, scatterplot interpretation.


                                    質問 # 34
                                    Probability it does NOT rain = 1 # 0.25 = ?

                                    正解：B


                                    質問 # 35
                                    Sample mean = best point estimate of population mean?

                                    正解：B

                                    解説：
                                    The sample mean is the standard point estimate for the population mean. A point estimate is a single statistic calculated from sample data and used to estimate an unknown population parameter. If the parameter of interest is the population mean #, the corresponding sample statistic is x#. Therefore, the statement is true.
                                    This does not mean the sample mean is guaranteed to equal the population mean exactly; sampling variability can cause sample means to differ from the true population mean. However, the sample mean is unbiased under random sampling and becomes more stable as sample size increases. Confidence intervals expand this idea by placing a margin of error around the sample mean. Option B is incorrect because the sample mean is precisely the conventional point estimator for #. Options C and D impose invalid restrictions. Study Guide references/topics: sample mean, population mean, point estimate, sampling variability.


                                    質問 # 36
                                    Probability of rolling sum = 2 on 2 dice = ?

                                    正解：B

                                    解説：
                                    When two standard six-sided dice are rolled, there are 6 × 6 = 36 equally likely ordered outcomes. To get a sum of 2, the only possible ordered pair is (1, 1). No other pair of die faces can produce a total of 2 because 1 is the smallest value on each die. Therefore, there is 1 favorable outcome out of 36 total outcomes, giving a probability of 1/36. Option B, 1/6, is the probability of one specific result on a single die, not a two-dice sum.
                                    Option C, 2/36, would require two favorable ordered pairs, but only one exists. Option D, 1/12, is also too large because it corresponds to 3 outcomes out of 36. The key is to count ordered outcomes in the full two- dice sample space. Study Guide references/topics: dice probability, sample space, favorable outcomes, theoretical probability.


                                    質問 # 37
                                    Which measure of central tendency is least affected by outliers?

                                    正解：C

                                    解説：
                                    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.


                                    質問 # 38
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