It 업계 중 많은 분들이 인증시험에 관심이 많은 인사들이 많습니다.it산업 중 더 큰 발전을 위하여 많은 분들이WGU Applied-Probability-and-Statistics를 선택하였습니다.인증시험은 패스를 하여야 자격증취득이 가능합니다.그리고 무엇보다도 통행증을 받을 수 잇습니다.WGU Applied-Probability-and-Statistics은 그만큼 아주 어려운 시험입니다. 그래도WGU Applied-Probability-and-Statistics인증을 신청하여야 좋은 선택입니다.우리는 매일매일 자신을 업그레이드 하여야만 이 경쟁이 치열한 사회에서 살아남을 수 있기 때문입니다.
| Section | Objectives |
|---|---|
| Topic 1: Descriptive Statistics | - Data summarization
|
| Topic 2: Probability | - Fundamental probability concepts
|
| Topic 3: Statistical Inference | - Hypothesis testing
|
| Topic 4: Regression and Correlation | - Relationship analysis
|
| Topic 5: Probability Distributions | - Discrete distributions
|
>> Applied-Probability-and-Statistics최신버전 시험대비자료 <<
WGU인증 Applied-Probability-and-Statistics시험은 인기있는 IT자격증을 취득하는데 필요한 국제적으로 인정받는 시험과목입니다. WGU인증 Applied-Probability-and-Statistics시험을 패스하려면 PassTIP의WGU인증 Applied-Probability-and-Statistics덤프로 시험준비공부를 하는게 제일 좋은 방법입니다. PassTIP덤프는 IT전문가들이 최선을 다해 연구해낸 멋진 작품입니다. WGU인증 Applied-Probability-and-Statistics덤프구매후 업데이트될시 업데이트버전을 무료서비스료 제공해드립니다.
질문 # 25
A die is rolled twice. Probability of rolling two sixes?
정답：C
설명：
Rolling a standard six-sided die twice creates two independent events. The probability of rolling a six on the first roll is 1/6 because there is one favorable outcome, six, out of six equally likely outcomes. The probability of rolling a six on the second roll is also 1/6. Because the outcome of the first roll does not affect the outcome of the second roll, the multiplication rule for independent events applies. Thus, P(six and six) = 1/6 × 1/6 = 1
/36. Another way to verify the result is to list the sample space: two die rolls produce 6 × 6 = 36 equally likely ordered outcomes. Only one outcome, (6, 6), satisfies the condition of two sixes. Therefore, the probability is
1 favorable outcome out of 36 total outcomes. Study Guide references/topics: independent events, multiplication rule, sample space, theoretical probability.
질문 # 26
In a normal distribution, 95% of data lies within:
정답：C
설명：
For a normal distribution, the empirical rule states that approximately 68% of data fall within one standard deviation of the mean, approximately 95% fall within two standard deviations, and approximately 99.7% fall within three standard deviations. The notation ±2 SD means two standard deviations below the mean to two standard deviations above the mean, or # # 2# to # + 2#. Therefore, the interval containing about 95% of normally distributed observations is ±2 standard deviations. Option B corresponds to approximately 68%, not
95%. Option C corresponds to approximately 99.7%, and option D extends beyond the standard empirical- rule benchmarks. This concept is central when estimating the typical spread of bell-shaped data, such as test scores, biological measurements, or repeated measurement errors. The correct answer is ±2 SD because it matches the 95% portion of the 68-95-99.7 rule. Study Guide references/topics: normal distribution, empirical rule, standard deviation, distribution spread.
질문 # 27
Probability it does NOT rain = 1 # 0.25 = ?
정답：A
설명：
This question uses the complement rule of probability. If the probability that it rains is 0.25, then the probability that it does not rain is the complement of that event. The complement rule states that P(not A) = 1
# P(A). Here, A represents the event "it rains," so P(not rain) = 1 # 0.25 = 0.75. This means there is a 75% probability that rain does not occur. Option B repeats the probability of rain rather than its complement.
Option C would imply rain and no rain are equally likely, which is not supported by the given probability.
Option D would mean no rain is certain, but a 0.25 probability of rain means rain is still possible. The key technical point is that an event and its complement must sum to 1. Study Guide references/topics: probability, complement rule, event probability, sample-space total.
질문 # 28
Z-score formula = ?
정답：C
설명：
The z-score formula is z = (x # #)/#, where x is the observed value, # is the population mean, and # is the population standard deviation. A z-score standardizes a raw value by measuring how many standard deviations it lies above or below the mean. The numerator, x # #, gives the deviation from the mean. Dividing by # converts that deviation into standard deviation units. If z is positive, the value is above the mean. If z is negative, the value is below the mean. If z = 0, the value equals the mean. Option B incorrectly adds the value and mean, which does not measure deviation. Option C ignores the mean, and option D ignores the observed value entirely. The z-score is central for normal distribution calculations because it allows values from different scales to be compared using the standard normal distribution. Study Guide references/topics: z- scores, standard normal distribution, mean, standard deviation.
질문 # 29
Standard error decreases when:
정답：C
설명：
The standard error of the mean is calculated as SE = s/#n, where s is the sample standard deviation and n is the sample size. Because n appears in the denominator under a square root, increasing the sample size decreases the standard error when the standard deviation is held constant. This reflects a central idea in sampling: larger samples tend to produce more stable and precise estimates of the population mean. Option C is incorrect because increasing the standard deviation increases the standard error, not decreases it. Option B is incomplete and does not identify what is decreasing. Option D is not the direct driver of standard error; confidence level affects the critical value and margin of error, but the standard error itself is determined by variability and sample size. The correct relationship is inverse: as sample size increases, standard error decreases. Study Guide references/topics: standard error, sample size, sampling variability, precision of estimates.
질문 # 30
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