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| Section | Objectives |
|---|---|
| Topic 1: Probability | - Probability rules
|
| Topic 2: Regression and Correlation | - Relationship analysis
|
| Topic 3: Statistical Inference | - Hypothesis testing
|
| Topic 4: Descriptive Statistics | - Data summarization
|
| Topic 5: Probability Distributions | - Discrete distributions
|
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NEW QUESTION # 68
A city council surveys residents and business owners about a proposed new public transportation system. The results of the survey are shown in the following 2 × 2 contingency table.
Which statement is true?
Answer: B
Explanation:
This question requires comparing conditional percentages from a two-way table. For residents, 150 out of 200 are in favor of the proposed transportation system. The resident support rate is therefore 150/200 = 0.75, or
75%. For business owners, 30 out of 100 are in favor. The business owner support rate is 30/100 = 0.30, or
30%. The difference is 75% # 30% = 45 percentage points, which is a large gap. Therefore, a resident is much more likely than a business owner to favor the new transportation system. Option A understates the magnitude of the difference by calling it slight. Options B and C reverse the direction of the comparison because residents have the higher support rate, not the lower one. The appropriate statistical tool here is conditional percentage because support is being compared within each respondent group. References/topics from the Study Guide: contingency tables, conditional percentages, two-variable categorical data, comparative proportions.
NEW QUESTION # 69
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 # 70
Sample mean = best point estimate of population mean?
Answer: D
Explanation:
The sample mean is the standard point estimate for the population mean. A point estimate is a single statistic calculated from sample data and used to estimate an unknown population parameter. If the parameter of interest is the population mean #, the corresponding sample statistic is x#. Therefore, the statement is true.
This does not mean the sample mean is guaranteed to equal the population mean exactly; sampling variability can cause sample means to differ from the true population mean. However, the sample mean is unbiased under random sampling and becomes more stable as sample size increases. Confidence intervals expand this idea by placing a margin of error around the sample mean. Option B is incorrect because the sample mean is precisely the conventional point estimator for #. Options C and D impose invalid restrictions. Study Guide references/topics: sample mean, population mean, point estimate, sampling variability.
NEW QUESTION # 71
A child's parents want to analyze the relationship between the daily high temperature and ice cream sales at their child's ice cream stand. They create the following scatterplot.
What is the estimated value of r, the correlation coefficient, between these variables?
Answer: C
Explanation:
The correlation coefficient r measures both the direction and strength of a linear relationship between two quantitative variables. In this scatterplot, the points rise from lower left to upper right, showing a positive association between temperature and daily ice cream sales. As temperature increases, sales also tend to increase. The points are fairly close to an upward-sloping linear pattern, so the relationship is strong rather than weak. A value of r near 1 indicates a strong positive linear association, while a value near #1 indicates a strong negative association. Since the association is clearly positive, the negative options, #0.93 and #0.39, are not appropriate. Since the points show a strong trend rather than a loose or weak trend, 0.39 is too small.
The best estimate is 0.93. This is consistent with the visual pattern: temperature explains a substantial amount of the linear movement in ice cream sales. References/topics from the Study Guide: scatterplots, correlation coefficient, positive association, strength of linear relationship.
NEW QUESTION # 72
Variance formula = ?
Answer: D
Explanation:
The sample variance formula is s² = #(x# # x#)² / (n # 1). In this formula, x# represents each data value, x# is the sample mean, and n is the sample size. The expression x# # x# gives each value's deviation from the mean. Squaring the deviations prevents negative and positive deviations from canceling and emphasizes larger departures. Dividing by n # 1 gives the sample variance, using degrees of freedom to correct bias when estimating population variance from a sample. Option B is the formula for the sample mean, not variance.
Option C squares the mean and does not measure spread. Option D resembles part of the standard deviation process but omits division by n # 1 and is not the variance formula. Variance is foundational because standard deviation is the square root of variance. Study Guide references/topics: variance, sample variance formula, mean deviations, measures of spread.
NEW QUESTION # 73
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