Applied-Probability-and-Statistics 認證是互聯網界具有極大聲望的網路技能認證，在全球，通過IBM認證考試的工程師，平均年薪在10萬元以上。通過 HP 認證考試的工程師，平均年薪在30萬元以上。獲得 WGU 的 Applied-Probability-and-Statistics 認證的工程師，平均年薪也不低於20萬人民幣。據說，這還只是基本工資，不包括獎金，紅利和其他非工資性補貼。難怪美國副總統戈爾曾把 WGU Applied-Probability-and-Statistics 認證恰當而幽默地稱為“獲得高技術，高薪水的頭等艙船票”。
| Section | Objectives |
|---|---|
| Probability | - Probability rules
|
| Regression and Correlation | - Relationship analysis
|
| Statistical Inference | - Estimation
|
| Probability Distributions | - Continuous distributions
|
| Descriptive Statistics | - Data visualization
|
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問題 #101
A tech company surveys its employees to assess remote work preferences. The survey reveals that 55% of employees prefer working remotely, while the remaining employees prefer working in the office. Of the employees who prefer remote work, 75% report high productivity. Among those who prefer working in the office, only 50% report high productivity.
Which percentage of employees prefer working in the office and report high productivity?
答案：C
解題說明：
The question asks for a joint percentage: employees who both prefer working in the office and report high productivity. First identify the percentage who prefer office work. Since 55% prefer remote work, the remaining 45% prefer working in the office. The problem then states that among office-preferring employees,
50% report high productivity. This is a conditional percentage: P(high productivity | office preference) = 50%.
To find the overall percentage of all employees who satisfy both conditions, multiply the base percentage by the conditional percentage: 45% × 50% = 0.45 × 0.50 = 0.225 = 22.5%. Option D gives only the conditional rate within the office group, not the percentage of all employees. Option C gives only the office-preference percentage, not productivity within that group. Option B does not match the correct joint probability calculation. The correct selection is therefore 22.5%. References/topics from the Study Guide: probability, conditional percentages, joint probability, two-way categorical reasoning.
問題 #102
Binomial distribution parameters = ?
答案：B
解題說明：
A binomial distribution is defined by two parameters: n and p. The parameter n is the fixed number of trials, and p is the probability of success on each trial. The model applies when trials are independent, each trial has two possible outcomes, and p remains constant. For example, if X is the number of heads in 10 fair coin flips, then X follows a binomial distribution with n = 10 and p = 0.5. Option B, #, is the parameter of a Poisson distribution, used for counts of events over intervals. Option C, # and #, commonly describes a normal distribution, where # is the mean and # is the standard deviation. Option D is incorrect because the binomial model has a precise parameter structure. Identifying n and p is essential before calculating binomial probabilities or expected value. Study Guide references/topics: binomial distribution, independent trials, success probability, discrete probability.
問題 #103
Type II error occurs when:
答案：A
解題說明：
A Type II error occurs when the null hypothesis is false but the statistical test fails to reject it. In many answer choices, this is expressed as "accepting the null when false," though the more precise language is "failing to reject the null." This error is a false negative: the test misses a real effect, difference, or relationship. For example, if a medication truly improves recovery but a study fails to detect sufficient evidence of improvement, that is a Type II error. Option B describes a Type I error, which occurs when a true null hypothesis is rejected. Option C is not an error. Option D is too vague; statistical decision errors refer specifically to incorrect conclusions about hypotheses, not ordinary data-entry mistakes. The probability of a Type II error is denoted #, and statistical power is 1 # #. Study Guide references/topics: hypothesis testing, Type II error, null hypothesis, statistical power.
問題 #104
Probability of rolling 1, 2, or 3 on die = ?
答案：B
解題說明：
A standard six-sided die has six equally likely outcomes: 1, 2, 3, 4, 5, and 6. The event "rolling 1, 2, or 3" has three favorable outcomes: 1, 2, and 3. The probability is therefore favorable outcomes divided by total outcomes: 3/6. This fraction simplifies to 1/2. Option B, 1/3, would correspond to two favorable outcomes out of six. Option C, 1/6, is the probability of rolling one specific number only. Option D, 2/3, would require four favorable outcomes out of six. Since exactly half of the die faces are 1, 2, or 3, the correct probability is one- half. This is a direct application of theoretical probability with equally likely outcomes. Study Guide references/topics: die probability, favorable outcomes, sample space, theoretical probability.
問題 #105
Two mutually exclusive events: P(A and B) = ?
答案：D
解題說明：
Mutually exclusive events cannot occur at the same time. If event A occurs, event B cannot occur, and if event B occurs, event A cannot occur. Therefore, the probability of both events occurring together is zero: P (A and B) = 0. For example, when rolling one die, the event "roll a 2" and the event "roll a 5" are mutually exclusive because one roll cannot produce both outcomes simultaneously. Option B applies to independent events, not mutually exclusive events. In fact, mutually exclusive events with positive probabilities are not independent because the occurrence of one eliminates the possibility of the other. Option C is part of the addition rule for mutually exclusive events when calculating P(A or B), not P(A and B). Option D would mean both events always occur together, which contradicts mutual exclusivity. Study Guide references/topics:
mutually exclusive events, joint probability, addition rule, probability foundations.
問題 #106
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