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| Section | Objectives |
|---|---|
| Statistical Inference | - Hypothesis Testing (Introductory Level)
|
| Descriptive Statistics | - Two Variable Data Analysis
|
| Probability Theory | - Fundamental Probability Concepts
|
| Regression and Modeling | - Linear Relationships
|
>> Applied-Probability-and-Statistics学習資料 <<
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質問 # 13
Mean of Poisson # = 5 = ?
正解：A
解説：
For a Poisson distribution, the parameter # represents the mean number of events occurring in a fixed interval.
Therefore, if # = 5, the mean is 5. This means that over many repeated intervals of the same size, the long-run average number of events per interval would be 5. The Poisson distribution is used for count data, such as calls per hour, accidents per week, or defects per batch, when events occur independently and at a constant average rate. A special property of the Poisson distribution is that its variance also equals #, so in this case the variance would also be 5. However, the question asks for the mean, so the direct answer is 5. Options B, C, and D are not supported by the stated parameter. Study Guide references/topics: Poisson distribution, # parameter, expected value, count data.
質問 # 14
One-sample t-test compares:
正解：C
解説：
A one-sample t-test is used to compare a sample mean to a hypothesized or known population mean when the population standard deviation is unknown and the data are approximately normal or the sample size is sufficiently large. The test statistic evaluates how far the sample mean is from the hypothesized mean in standard error units. Option A is therefore correct. A two-sample t-test compares means from two independent groups, so option B describes a different test. Tests of variances use procedures such as chi-square or F-based methods depending on context, so option C is not appropriate. Tests of proportions use z procedures for categorical success/failure data, not a one-sample t-test for means. The t-test is part of inferential statistics because it uses sample evidence to make a decision about a population parameter. Study Guide references
/topics: one-sample t-test, sample mean, population mean, hypothesis testing.
質問 # 15
Independent events: P(A|B) = ?
正解：C
解説：
For independent events, the occurrence of one event does not change the probability of the other. Conditional probability P(A|B) means the probability of A occurring given that B has occurred. If A and B are independent, knowing B occurred gives no new information about A. Therefore, P(A|B) = P(A). This is one of the defining properties of independence. For example, if a coin toss and a die roll are independent, knowing the die landed on 4 does not change the probability that the coin landed heads; it remains 1/2. Option B reverses the event being measured. Option C would imply that A becomes impossible after B, which describes a different situation. Option D is an addition expression and does not represent conditional probability. The correct relationship is that the conditional probability equals the original probability when events are independent. Study Guide references/topics: independent events, conditional probability, probability rules, event relationships.
質問 # 16
In a game, a coin is tossed, and a spinner with 8 equal spaces numbered 1 through 8 is spun.
What is the probability of getting heads on the coin and a number less than 3 on the spinner?
正解：B
質問 # 17
A teacher plots the test scores of a class using the box plot.
What is true about the test scores?
正解：D
解説：
A box plot displays the five-number summary of a quantitative data set: minimum, first quartile, median, third quartile, and maximum. The median is represented by the vertical line inside the box. In the given box plot, that internal vertical line is positioned at 80 on the score axis. Therefore, the median test score for Class A is
80 points. The value 70 corresponds to the left edge of the box, which represents the first quartile, not the median. The value near 88 represents the right edge of the box, which is the third quartile. The whiskers extend to the approximate minimum and maximum scores, but those values do not determine the median. The median divides the ordered data into two equal halves, meaning about 50% of the students scored at or below
80 and about 50% scored at or above 80. References/topics from the Study Guide: box plots, five-number summary, median, quartiles.
質問 # 18
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Applied-Probability-and-Statistics準備資料で20〜30時間学習した直後に、今後の試験に自信を持つことができるという誇張はありません。何万人ものお客様が弊社の試験資料の恩恵を受け、Applied-Probability-and-Statistics試験に簡単に合格しました。データは、私たちのハイパス率が信じられないほど98％から100％であることを示しました。間違いなく、あなたの成功はApplied-Probability-and-Statisticsトレーニングガイドで100％保証されています。リンクをクリックするだけで概要を表示できるのが便利であり、あらゆる種類のApplied-Probability-and-Statisticsバージョンを体験できます。
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