Je früher die Zertifizierung der WGU Applied-Probability-and-Statistics zu erwerben, desto hilfreicher ist es für Ihre Karriere in der IT-Branche. Vielleicht haben Sie erfahren, dass die Vorbereitung dieser Prüfung viel Zeit oder Gebühren fürs Training braucht. Aber die WGU Applied-Probability-and-Statistics Prüfungssoftware von uns widerspricht diese Darstellung. Die komplizierte Sammlung und Ordnung der Prüfungsunterlagen der WGU Applied-Probability-and-Statistics werden von unserer professionellen Gruppen fertiggemacht. Genießen Sie doch die wunderbare Wirkungen der Prüfungsvorbereitung und den Erfolg bei der WGU Applied-Probability-and-Statistics Prüfung!
| Section | Weight | Objectives |
|---|---|---|
| Probability Concepts | 20% | - Conditional probability and Venn diagrams - Discrete and continuous probability distributions - Probability rules, independent and dependent events - Normal distribution and empirical rule |
| Basic Numeracy & Algebra | 15% | - Linear equations, inequalities, graphing functions - Arithmetic operations, fractions, decimals, percentages - Exponents, roots, and basic formulas |
| Correlation & Regression | 20% | - Interpreting slope, intercept, and R-squared - Predictions and limitations of regression - Simple linear regression models - Correlation coefficient and interpretation |
| Inferential Statistics & Study Design | 20% | - Sampling methods and bias - Observational studies vs experiments - Hypothesis testing framework and interpretation - Confidence intervals for means/proportions |
| Descriptive Statistics | 25% | - Types of data: categorical, discrete, continuous - Measures of spread: range, IQR, variance, standard deviation - Measures of center: mean, median, mode - Graphical displays: histograms, boxplots, scatterplots |
>> Applied-Probability-and-Statistics Prüfungs-Guide <<
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95. Frage
Probability sum for all outcomes = ?
Antwort: C
Begründung:
In any valid probability model, the probabilities of all outcomes in the sample space must sum to 1. The sample space is the complete set of possible outcomes for an experiment, and exactly one outcome from that set must occur. A total probability of 1 represents certainty. For example, when rolling a fair six-sided die, the six outcomes each have probability 1/6, and their sum is 6 × 1/6 = 1. A total of 0 would imply no possible outcome can occur, which is not a valid probability model. A total greater than 1 violates the maximum boundary of probability, and a total less than 1 would mean the sample space is incomplete or some probability has been omitted. This rule is one of the axioms of probability and is used to verify distributions.
Study Guide references/topics: sample space, probability axioms, total probability, probability distributions.
96. Frage
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?
Antwort: B
Begründung:
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.
97. Frage
P(A) = 0.3, P(B) = 0.4, A and B independent. P(A and B) = ?
Antwort: C
Begründung:
For independent events, the occurrence of one event does not change the probability of the other event. The multiplication rule states that if A and B are independent, then P(A and B) = P(A) × P(B). Here, P(A) = 0.3 and P(B) = 0.4. Therefore, P(A and B) = 0.3 × 0.4 = 0.12. This means there is a 12% probability that both events occur. Option B, 0.7, incorrectly adds the probabilities and would only be part of an "or" calculation, not an "and" calculation. Option D repeats P(A), and option C does not follow from the multiplication rule.
The phrase "A and B independent" is the decisive condition because it permits direct multiplication without adjusting for conditional probability. Study Guide references/topics: independent events, multiplication rule, compound probability, joint probability.
98. Frage
Standard error decreases when:
Antwort: A
Begründung:
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.
99. Frage
Correlation r = 0.8 # strong positive relationship #
Antwort: C
Begründung:
A correlation coefficient of r = 0.8 indicates a strong positive linear relationship between two quantitative variables. The positive sign means that as one variable increases, the other tends to increase. The magnitude,
0.8, is close to 1, which indicates a strong linear pattern. It is not perfect, because perfect positive correlation would be r = 1, but it is clearly stronger than a weak or moderate association. Option B is incorrect because the interpretation matches both the sign and magnitude of r. Option C is incorrect because correlation is used for quantitative variables, not categorical variables. Option D is incorrect because a negative r would indicate a negative relationship. Importantly, correlation does not prove causation; it describes the direction and strength of linear association. Study Guide references/topics: correlation coefficient, positive association, linear relationship, scatterplot interpretation.
100. Frage
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