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| Section | Objectives |
|---|---|
| Regression and Correlation | - Relationship analysis
|
| Statistical Inference | - Estimation
|
| Descriptive Statistics | - Data visualization
|
| Probability Distributions | - Discrete distributions
|
| Probability | - Probability rules
|
>> Exam Applied-Probability-and-Statistics Introduction <<
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NEW QUESTION # 66
A golf course is attempting to correlate golfing handicap with math SAT scores among local high school golfers. Ignoring potential confounding variables such as socioeconomic status, the golf course creates the following scatterplot.
What is the estimated value of r, the correlation coefficient, between these variables?
Answer: D
Explanation:
The correlation coefficient r measures the direction and strength of a linear relationship between two quantitative variables. In the scatterplot, the points are widely dispersed, so the relationship is weak rather than strong. The fitted trend line slopes slightly downward, indicating a negative association: as golf handicap increases, math SAT score tends to decrease slightly. Because the pattern is weak and negative, r should be close to 0 but less than 0. The best match is #0.10. Option A, #0.63, would represent a moderately strong negative linear relationship, which would require the points to cluster more tightly around a downward- sloping line. Option C, 0.10, has the right weak magnitude but the wrong direction because it is positive.
Option D, 0.63, is both too strong and positive. The visual evidence supports only a very slight negative linear association. References/topics from the Study Guide: scatterplots, correlation coefficient, positive and negative association, strength of linear relationship.
NEW QUESTION # 67
Probability it does NOT rain = 1 # 0.25 = ?
Answer: A
Explanation:
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.
NEW QUESTION # 68
R² = 0.81 # correlation r = ?
Answer: B
Explanation:
In simple linear regression, R² is the square of the correlation coefficient r. Therefore, to recover the possible correlation value from R², take the square root: r = ±#R². With R² = 0.81, the square root is #0.81 = 0.9, so r may be +0.9 or #0.9. The sign cannot be determined from R² alone because squaring removes direction. A positive r would indicate an upward linear association, while a negative r would indicate a downward linear association. Option D gives only +0.9, which would be correct only if the slope or scatterplot confirmed a positive relationship. Option B incorrectly treats R² as though it were r. Option C incorrectly keeps 0.81 after applying the square-root relationship. The technically complete answer is ±0.9. Study Guide references
/topics: coefficient of determination, correlation coefficient, regression, explained variation.
NEW QUESTION # 69
In a normal distribution, 95% of data lies within:
Answer: A
Explanation:
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.
NEW QUESTION # 70
In a standard normal distribution, z-score for the mean = ?
Answer: D
Explanation:
A z-score measures how many standard deviations a value is above or below the mean. The formula is z = (x
# #) / #, where x is the observed value, # is the mean, and # is the standard deviation. If the observed value equals the mean, then x = #. Substituting into the formula gives z = (# # #) / # = 0 / # = 0. Therefore, the z- score corresponding to the mean is always 0 in any normal distribution, including the standard normal distribution. In the standard normal distribution specifically, the mean is 0 and the standard deviation is 1, so the mean lies exactly at z = 0. A z-score of 1 would indicate one standard deviation above the mean, and #1 would indicate one standard deviation below the mean. Study Guide references/topics: standard normal distribution, z-scores, mean, standard deviation.
NEW QUESTION # 71
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