IT業種が新しい業種で、経済発展を促進するチェーンですから、極めて重要な存在ということを我々は良く知っています。IT認証はIT業種での競争な手段の一つです。認証に受かったらあなたは各方面でよく向上させます。でも、受かることが難しいですから、トレーニングツールを利用するのを勧めます。トレーニング資料を選びたいのなら、MogiExamのWGUのApplied-Probability-and-Statistics試験トレーニング資料は最高の選択です。この資料の成功率が１００パーセントに達して、あなたが試験に合格することを保証します。
| Section | Objectives |
|---|---|
| Topic 1: Probability | - Fundamental probability concepts
|
| Topic 2: Descriptive Statistics | - Data summarization
|
| Topic 3: Regression and Correlation | - Relationship analysis
|
| Topic 4: Probability Distributions | - Continuous distributions
|
| Topic 5: Statistical Inference | - Hypothesis testing
|
>> Applied-Probability-and-Statistics模擬対策 <<
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質問 # 146
Mean = 50, SD = 5, n = 25. Standard error = ?
正解：D
解説：
The standard error of the mean measures the expected sampling variability of the sample mean. It is calculated by dividing the sample standard deviation by the square root of the sample size: SE = s / #n. In this question, the standard deviation is 5 and the sample size is 25. Therefore, SE = 5 / #25 = 5 / 5 = 1. The mean of 50 identifies the center of the sample distribution but is not directly used in the standard error calculation.
Option B, 5, is the standard deviation, not the standard error. Option C, 25, is the sample size. Option D, 0.2, would result from incorrectly dividing 5 by 25 rather than by the square root of 25. The distinction between standard deviation and standard error is important: standard deviation describes spread among individual observations, while standard error describes spread among sample means. Study Guide references/topics:
standard error, standard deviation, sample size, sampling distributions.
質問 # 147
A marketing analyst is studying the relationship between customer age groups, teens, adults, and seniors, and their preferred shopping methods, online and in-store.
Which numerical measure is most appropriate for this study?
正解：D
解説：
This study involves two categorical variables: customer age group and preferred shopping method. Age group is categorical because customers are classified into groups such as teens, adults, and seniors. Shopping method is also categorical because customers are classified as preferring either online or in-store shopping.
When two categorical variables are analyzed together, conditional percentages are the most appropriate numerical summary because they describe how the distribution of one categorical variable changes within levels of another categorical variable. For example, the analyst could compute the percentage of teens who prefer online shopping, the percentage of adults who prefer online shopping, and the percentage of seniors who prefer online shopping. A five-number summary is used for quantitative data, not categorical data. Mean difference requires numerical measurements. A correlation coefficient measures the strength and direction of a linear relationship between two quantitative variables, so it is not appropriate here. References/topics from the Study Guide: two-variable categorical data, conditional percentages, categorical association, numerical summaries.
質問 # 148
A dataset: 4, 8, 12, 16, 20. Mean = ?
正解：D
解説：
The mean is the arithmetic average of a data set. To compute it, add all values and divide by the number of observations. For the dataset 4, 8, 12, 16, and 20, the sum is 4 + 8 + 12 + 16 + 20 = 60. There are 5 values, so the mean is 60 ÷ 5 = 12. The mean represents the balance point of the data. This dataset is evenly spaced around 12: 4 and 20 are equally distant from 12, and 8 and 16 are equally distant from 12. That symmetry supports the computed result. Option A, 10, is too low because it does not account for the higher values 16 and 20. Option C, 14, is too high, and option D is one of the data values but not the average. The correct answer is 12. Study Guide references/topics: mean, arithmetic average, measures of center, quantitative data.
質問 # 149
Regression slope indicates:
正解：A
解説：
In a linear regression equation, the slope represents the predicted change in the response variable Y for each one-unit increase in the explanatory variable X. In slope-intercept form, # = b# + b#x, the slope is b#. For example, if a regression equation predicts cost as # = 25 + 4x, the slope 4 means the predicted cost increases by 4 units for each additional unit of x. The intercept, b#, is the predicted value of Y when X = 0, so option B describes a different component. R² measures the proportion of variation in Y explained by the regression model, not the rate of change. Correlation measures strength and direction of linear association, but it is not the same as the slope because it is unitless and standardized. The slope is the operational rate of change in the model. Study Guide references/topics: linear regression, slope interpretation, response variable, explanatory variable.
質問 # 150
Sample mean = 40, SD = 8, n = 16. Standard error = ?
正解：A
解説：
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. Here, the standard deviation is 8 and the sample size is 16. The square root of 16 is 4, so SE = 8/4 = 2. The sample mean of 40 is not used directly in the standard error formula; it identifies the center of the sample, not the variability of the sample mean across repeated samples. Option B, 8, is the standard deviation, not the standard error. Option D, 4, is the square root of the sample size. Option C, 0.5, would result from an incorrect calculation. Standard error decreases as sample size increases because larger samples provide more precise estimates. Study Guide references/topics: standard error, standard deviation, sample size, sampling distribution.
質問 # 151
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