1What does descriptive statistics primarily aim to do?
statistical analysis
Easy
A.Generate random numbers for simulations
B.Encrypt data for secure storage
C.Summarize and describe the main features of a dataset
D.Prove that a theory is universally true
Correct Answer: Summarize and describe the main features of a dataset
Explanation:
Descriptive statistics summarize data using measures like mean, median, and standard deviation, describing what the data shows without making broader inferences.
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2Which measure of central tendency is most affected by extreme outliers?
statistical analysis
Easy
A.Median
B.Mode
C.Mean
D.Range
Correct Answer: Mean
Explanation:
The mean adds all values and divides by the count, so a very large or small value pulls it in that direction. The median and mode are more resistant to outliers.
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3The standard deviation is a measure of:
statistical analysis
Easy
A.The most frequent value in the data
B.The middle value of the data
C.The total sum of all data points
D.The spread or dispersion of data around the mean
Correct Answer: The spread or dispersion of data around the mean
Explanation:
Standard deviation quantifies how much the data values deviate, on average, from the mean. A larger value means more spread.
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4In hypothesis testing, the null hypothesis () typically represents:
hypothesis testing
Easy
A.The alternative claim being tested
B.A guaranteed positive result
C.No effect or no difference
D.The largest possible effect size
Correct Answer: No effect or no difference
Explanation:
The null hypothesis states there is no effect, no difference, or no relationship. It is the default assumption we try to reject.
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5A Type I error occurs when we:
hypothesis testing
Easy
A.Fail to collect enough data
B.Accept a true null hypothesis
C.Reject a true null hypothesis
D.Reject a false null hypothesis
Correct Answer: Reject a true null hypothesis
Explanation:
A Type I error (false positive) happens when we reject even though it is actually true. Its probability is denoted by .
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6The significance level of a test is usually denoted by which symbol?
hypothesis testing
Easy
A.
B.
C.
D.
Correct Answer:
Explanation:
The significance level is denoted and represents the probability of committing a Type I error, commonly set at 0.05.
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7A p-value represents the probability of:
significance of p-value
Easy
A.Observing results as extreme as the data, assuming is true
B.The alternative hypothesis being true
C.The null hypothesis being true
D.Making a correct decision in the test
Correct Answer: Observing results as extreme as the data, assuming is true
Explanation:
The p-value is the probability of getting results at least as extreme as those observed, under the assumption that the null hypothesis is true.
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8If a p-value is less than the significance level , we typically:
significance of p-value
Easy
A.Accept the null hypothesis
B.Change the alternative hypothesis
C.Reject the null hypothesis
D.Increase the sample size
Correct Answer: Reject the null hypothesis
Explanation:
When , the result is statistically significant, so we reject in favor of the alternative hypothesis.
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9A smaller p-value indicates:
significance of p-value
Easy
A.Stronger evidence for the null hypothesis
B.A larger sample was required
C.Stronger evidence against the null hypothesis
D.A guaranteed real effect exists
Correct Answer: Stronger evidence against the null hypothesis
Explanation:
The smaller the p-value, the stronger the evidence against , making it more likely we reject the null hypothesis.
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10The chi-square test is most commonly used to analyze:
chi-square
Easy
A.Correlation between two continuous variables
B.Time-series trends
C.Categorical (frequency) data
D.Continuous numeric averages
Correct Answer: Categorical (frequency) data
Explanation:
The chi-square test works with categorical data, comparing observed frequencies against expected frequencies in categories.
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11A chi-square test of independence checks whether:
chi-square
Easy
A.Two means are equal
B.Two categorical variables are associated
C.A sample follows a normal distribution
D.Three or more group variances differ
Correct Answer: Two categorical variables are associated
Explanation:
The chi-square test of independence determines whether there is a significant association between two categorical variables.
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12In the chi-square statistic , what does represent?
chi-square
Easy
A.The expected frequency
B.The number of outcomes
C.The observed frequency
D.The overall mean
Correct Answer: The observed frequency
Explanation:
In the formula, is the observed frequency (actual counts) and is the expected frequency under the null hypothesis.
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13A t-test is generally used to compare:
t-test
Easy
A.The variances of three or more groups
B.The correlation of two datasets
C.The frequencies of categorical data
D.The means of one or two groups
Correct Answer: The means of one or two groups
Explanation:
A t-test compares means, either a sample mean to a known value (one-sample) or the means of two groups, especially with small samples.
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14Which type of t-test compares the means of two related measurements from the same subjects?
t-test
Easy
A.Welch's t-test
B.Independent samples t-test
C.One-sample t-test
D.Paired t-test
Correct Answer: Paired t-test
Explanation:
A paired t-test compares two related measurements, such as before-and-after values from the same subjects.
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15The t-test is preferred over the z-test mainly when:
t-test
Easy
A.The population is infinitely large
B.More than three groups are compared
C.The sample size is small and population variance is unknown
D.The data is purely categorical
Correct Answer: The sample size is small and population variance is unknown
Explanation:
The t-test is designed for small samples where the population standard deviation is unknown and must be estimated from the sample.
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16ANOVA is primarily used to compare:
ANOVA
Easy
A.Two categorical variables
B.The spread of a single dataset
C.The median of two groups
D.Means of three or more groups
Correct Answer: Means of three or more groups
Explanation:
ANOVA (Analysis of Variance) tests whether the means of three or more groups differ significantly from one another.
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17The test statistic used in ANOVA is the:
ANOVA
Easy
A.z-statistic
B.Chi-square statistic
C.t-statistic
D.F-statistic
Correct Answer: F-statistic
Explanation:
ANOVA uses the F-statistic, which is the ratio of variance between groups to variance within groups.
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18What does the null hypothesis of a one-way ANOVA state?
ANOVA
Easy
A.All group variances are zero
B.All group means are equal
C.The groups are categorical
D.At least one mean is different
Correct Answer: All group means are equal
Explanation:
The null hypothesis in one-way ANOVA is that all group means are equal ().
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19Bayes' theorem is used to update the probability of a hypothesis based on:
bayesian probability
Easy
A.The sample size only
B.New evidence or data
C.The number of groups compared
D.The significance level
Correct Answer: New evidence or data
Explanation:
Bayes' theorem revises a prior probability into a posterior probability as new evidence becomes available.
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20In Bayesian probability, the probability assigned before observing any new data is called the:
bayesian probability
Easy
A.Likelihood
B.Prior probability
C.Posterior probability
D.Marginal probability
Correct Answer: Prior probability
Explanation:
The prior probability represents our initial belief before new evidence; after updating with data it becomes the posterior probability.
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21A researcher sets a significance level of and obtains a test statistic that leads to a p-value of . What is the correct decision?
hypothesis testing
Medium
A.Increase the sample size before deciding
B.Accept the null hypothesis as true
C.Fail to reject the null hypothesis
D.Reject the null hypothesis
Correct Answer: Reject the null hypothesis
Explanation:
Since the p-value () is less than (), the result is statistically significant, so we reject the null hypothesis.
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22Which statement best describes the meaning of a p-value in hypothesis testing?
significance of p-value
Medium
A.The probability that the alternative hypothesis is correct
B.The probability that the null hypothesis is true given the data
C.The probability of making a Type II error in the test
D.The probability of observing data as extreme as the sample, assuming the null hypothesis is true
Correct Answer: The probability of observing data as extreme as the sample, assuming the null hypothesis is true
Explanation:
The p-value is the probability of obtaining results at least as extreme as those observed, computed under the assumption that is true. It is not the probability that itself is true.
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23You want to compare the mean test scores of two independent groups with small samples and unknown, unequal variances. Which test is most appropriate?
t-test
Medium
A.One-sample z-test
B.Chi-square test of independence
C.Welch's two-sample t-test
D.Paired t-test
Correct Answer: Welch's two-sample t-test
Explanation:
Welch's t-test compares means of two independent groups without assuming equal variances, making it suitable for small samples with unequal variances.
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24A chi-square goodness-of-fit test compares observed frequencies with expected frequencies . What is the test statistic formula?
chi-square
Medium
A.
B.
C.
D.
Correct Answer:
Explanation:
The chi-square statistic sums the squared differences between observed and expected counts, each divided by the expected count .
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25When comparing the means of four different groups simultaneously, why is one-way ANOVA preferred over multiple t-tests?
ANOVA
Medium
A.It works only when variances are unequal
B.It controls the inflation of the overall Type I error rate
C.It eliminates the need for a null hypothesis
D.It requires fewer assumptions about the data
Correct Answer: It controls the inflation of the overall Type I error rate
Explanation:
Running many pairwise t-tests inflates the family-wise Type I error rate. ANOVA tests all group means together with a single test, controlling this error.
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26A disease affects of a population. A test is sensitive and specific. Using Bayes' theorem, which quantity is the posterior probability of disease given a positive test?
bayesian probability
Medium
A.
B.
C.
D.
Correct Answer:
Explanation:
The posterior probability is , computed via Bayes' theorem using the prior, sensitivity, and specificity. Sensitivity is the likelihood term .
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27A test fails to reject the null hypothesis even though the alternative is actually true. What type of error has occurred?
hypothesis testing
Medium
A.Sampling error
B.Type I error
C.Standard error
D.Type II error
Correct Answer: Type II error
Explanation:
A Type II error () occurs when we fail to reject a false null hypothesis. A Type I error is rejecting a true null hypothesis.
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28In a study measuring blood pressure of the same patients before and after treatment, which t-test correctly accounts for the data structure?
t-test
Medium
A.One-way ANOVA
B.Independent two-sample t-test
C.Welch's t-test
D.Paired t-test
Correct Answer: Paired t-test
Explanation:
Measurements on the same subjects before and after are dependent (paired). A paired t-test uses the differences within each subject to test for change.
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29A result yields with . Which interpretation is most accurate?
significance of p-value
Medium
A.The result proves the alternative hypothesis is true
B.The effect size is guaranteed to be large
C.The result is statistically significant but the effect may still be small
D.There is a chance the alternative is correct
Correct Answer: The result is statistically significant but the effect may still be small
Explanation:
Statistical significance () does not imply practical importance. A small p-value can accompany a small effect, especially with large samples.
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30A chi-square test of independence uses a contingency table. How many degrees of freedom does it have?
chi-square
Medium
A.
B.
C.
D.
Correct Answer:
Explanation:
Degrees of freedom equal .
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31In one-way ANOVA, what does a large F-statistic generally indicate?
ANOVA
Medium
A.Within-group variance is large relative to between-group variance
B.All group means are exactly equal
C.The sample sizes are too small to analyze
D.Between-group variance is large relative to within-group variance
Correct Answer: Between-group variance is large relative to within-group variance
Explanation:
The F-statistic is the ratio of between-group to within-group variance. A large F suggests group means differ more than expected from random variation.
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32In Bayesian inference, how is the posterior distribution related to the prior and the likelihood?
bayesian probability
Medium
A.Posterior Likelihood Prior
B.Posterior Prior Likelihood
C.Posterior Prior Likelihood
D.Posterior Likelihood Prior
Correct Answer: Posterior Likelihood Prior
Explanation:
By Bayes' theorem, the posterior is proportional to the product of the likelihood and the prior, normalized by the evidence.
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33A dataset is strongly right-skewed with several large outliers. Which measure of central tendency best represents its typical value?
statistical analysis
Medium
A.Standard deviation
B.Range
C.Mean
D.Median
Correct Answer: Median
Explanation:
The median is resistant to outliers and skew, while the mean is pulled toward the tail. Range and standard deviation measure spread, not central tendency.
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34Increasing the sample size in a hypothesis test, while keeping other factors fixed, generally has what effect on statistical power?
hypothesis testing
Medium
A.Power decreases
B.Power increases
C.Power stays exactly the same
D.Power becomes undefined
Correct Answer: Power increases
Explanation:
Larger samples reduce the standard error, making it easier to detect a true effect, thereby increasing the power () of the test.
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35A one-sample t-test gives with degrees of freedom and a two-tailed critical value of at . What is the conclusion?
t-test
Medium
A.Switch to a chi-square test
B.The test is inconclusive
C.Reject the null hypothesis
D.Fail to reject the null hypothesis
Correct Answer: Reject the null hypothesis
Explanation:
Since exceeds the critical value , the statistic falls in the rejection region, so we reject .
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36In a chi-square test, expected cell counts are recommended to be at least . What is the main reason for this guideline?
chi-square
Medium
A.To make the degrees of freedom larger
B.To guarantee the observed counts are whole numbers
C.To ensure the chi-square approximation to the sampling distribution is reliable
D.To force the null hypothesis to be true
Correct Answer: To ensure the chi-square approximation to the sampling distribution is reliable
Explanation:
With small expected counts, the chi-square distribution poorly approximates the true sampling distribution, making p-values inaccurate. Fisher's exact test is an alternative.
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37After a significant one-way ANOVA result, why are post-hoc tests such as Tukey's HSD performed?
ANOVA
Medium
A.To increase the between-group variance
B.To identify which specific group means differ from each other
C.To reduce the number of groups compared
D.To confirm the ANOVA assumptions were met
Correct Answer: To identify which specific group means differ from each other
Explanation:
ANOVA only tells us that at least one mean differs. Post-hoc tests like Tukey's HSD pinpoint which pairs of group means are significantly different while controlling error.
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38A prior probability of rain is . New forecast evidence has likelihood under rain and under no rain. Which value is the denominator (evidence) in Bayes' theorem for updating?
bayesian probability
Medium
A.
B.
C.
D.
Correct Answer:
Explanation:
The evidence is the total probability of the observation: .
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39Two variables have a Pearson correlation of . Which conclusion is justified?
statistical analysis
Medium
A.There is a strong positive linear association between the variables
B.The relationship is strongly negative
C.The variables are unrelated
D.One variable definitely causes the other
Correct Answer: There is a strong positive linear association between the variables
Explanation:
A correlation near indicates a strong positive linear relationship, but correlation does not establish causation.
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40A researcher lowers the significance threshold from to . What is the direct effect on the two error types?
significance of p-value
Medium
A.Both error probabilities decrease equally
B.Neither error probability is affected
C.Type I error probability increases while Type II decreases
D.Type I error probability decreases while Type II error probability tends to increase
Correct Answer: Type I error probability decreases while Type II error probability tends to increase
Explanation:
A smaller makes it harder to reject , lowering Type I error risk but raising the chance of missing a true effect (Type II error), for a fixed sample size.
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41A researcher obtains in a two-sided test with and declares the effect "real and important." Which statement is the most accurate critique?
significance of p-value
Hard
A.The result cannot be significant because is too close to the threshold
B.A -value this small guarantees the finding will replicate
C.A -value just below neither quantifies effect size nor the probability the null is true; significance and importance are distinct
D.A means there is a probability the null hypothesis is true
Correct Answer: A -value just below neither quantifies effect size nor the probability the null is true; significance and importance are distinct
Explanation:
The -value is , not , and says nothing about magnitude or replicability. Statistical significance does not imply practical importance.
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42In a fixed-sample test, holding effect size and sample size constant, what happens to the Type II error rate as you lower from to ?
hypothesis testing
Hard
A. is unaffected by
B. increases (power decreases)
C. becomes equal to
D. decreases (power increases)
Correct Answer: increases (power decreases)
Explanation:
Lowering shrinks the rejection region, making it harder to reject . With everything else fixed, this raises and reduces power .
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43Two groups have equal sample sizes but markedly unequal variances. Using a Student's pooled-variance -test instead of Welch's -test primarily risks:
t-test
Hard
A.Always inflating power regardless of variance ratio
B.Making the test invalid only when exceeds 30
C.Distorting the Type I error rate because the pooled variance misestimates the standard error
D.Producing an identical result to Welch's test in all cases
Correct Answer: Distorting the Type I error rate because the pooled variance misestimates the standard error
Explanation:
With unequal variances the pooled estimate is wrong, so the actual Type I error deviates from the nominal . Welch's test does not assume equal variances and is generally safer.
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44A one-way ANOVA across 4 groups yields a significant . What is the correct next step and why?
ANOVA
Hard
A.Run post-hoc pairwise comparisons with a correction (e.g., Tukey HSD) because ANOVA only shows that at least one mean differs
B.Conclude only the largest and smallest means differ
C.Conclude all four means are pairwise different
D.Run 6 independent -tests at each with no correction
Correct Answer: Run post-hoc pairwise comparisons with a correction (e.g., Tukey HSD) because ANOVA only shows that at least one mean differs
Explanation:
A significant omnibus indicates some difference exists but not where. Multiplicity-corrected post-hoc tests locate the differences while controlling the family-wise error rate.
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45In a chi-square test of independence on a table, several expected cell counts fall below 5. The most appropriate response is to:
chi-square
Hard
A.Use Fisher's exact test, since the chi-square approximation is unreliable with small expected counts
B.Report the chi-square statistic anyway with no adjustment
C.Convert counts to proportions and use a -test on raw percentages
D.Increase to compensate for the small counts
Correct Answer: Use Fisher's exact test, since the chi-square approximation is unreliable with small expected counts
Explanation:
The chi-square distribution is an asymptotic approximation that fails with small expected frequencies. Fisher's exact test gives exact probabilities and is preferred for sparse tables.
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46A disease affects of a population. A test has sensitivity and specificity. Given a positive result, the posterior probability of disease is approximately:
bayesian probability
Hard
A.
B.
C.
D.
Correct Answer:
Explanation:
. Then . Low prevalence keeps the posterior low despite high accuracy.
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47A dataset is strongly right-skewed with several extreme high values. Which pair of summary statistics best describes its center and spread?
statistical analysis
Hard
A.Mean and standard deviation
B.Mean and variance
C.Mode and range
D.Median and interquartile range (IQR)
Correct Answer: Median and interquartile range (IQR)
Explanation:
The median and IQR are robust to skew and outliers, whereas the mean and standard deviation are pulled by extreme values and misrepresent a skewed center and spread.
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48Researchers test 100 independent true null hypotheses each at . What is the expected number of false positives, and what does this illustrate?
hypothesis testing
Hard
A.Exactly 1 false positive, fixed by
B.About 50 false positives, because compounds multiplicatively
C.About 5 false positives, illustrating the multiple-comparisons problem
D.Zero false positives, because all nulls are true
Correct Answer: About 5 false positives, illustrating the multiple-comparisons problem
Explanation:
Each true null has a chance of a false rejection, so the expected count is . Testing many hypotheses inflates the chance of spurious findings, motivating corrections.
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49A paired-samples design (before/after on the same subjects) is incorrectly analyzed with an independent two-sample -test. The typical consequence is:
t-test
Hard
A.The test becomes invalid only for negative correlations
B.An identical -statistic to the paired test
C.Automatic Type I error inflation regardless of correlation
D.Loss of power because the analysis ignores within-subject correlation and inflates the standard error
Correct Answer: Loss of power because the analysis ignores within-subject correlation and inflates the standard error
Explanation:
Positive within-subject correlation is exploited by the paired test to reduce error variance. An independent-samples test ignores this pairing, inflating the standard error and reducing power.
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50In a one-way ANOVA, if the between-group variability is small relative to within-group variability, the -statistic will be:
ANOVA
Hard
A.Very large, indicating strong group differences
B.Negative, indicating error in computation
C.Close to 1, suggesting group means do not differ beyond chance
D.Exactly 0 whenever means are unequal
Correct Answer: Close to 1, suggesting group means do not differ beyond chance
Explanation:
. When between-group variance is comparable to within-group variance, , consistent with the null of equal means.
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51Which interpretation of a confidence interval that excludes 0 for a mean difference is correct?
significance of p-value
Hard
A.The -value must be exactly
B.The corresponding two-sided test rejects at
C.There is a probability the true difference lies in this specific interval
D.The true difference is definitely nonzero
Correct Answer: The corresponding two-sided test rejects at
Explanation:
CIs and two-sided tests are dual: if a CI excludes the null value, the test rejects at . The refers to the long-run coverage of the procedure, not a probability about one fixed interval.
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52A chi-square goodness-of-fit test compares observed counts across 6 categories to a theoretical distribution with no estimated parameters. The degrees of freedom are:
chi-square
Hard
A.1
B.6
C.5
D.4
Correct Answer: 5
Explanation:
For goodness-of-fit, , where categories and estimated parameters. Thus .
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53In Bayesian inference, as the sample size grows very large, the influence of a proper prior on the posterior typically:
bayesian probability
Hard
A.Becomes undefined for continuous parameters
B.Diminishes, so the posterior is dominated by the likelihood
C.Stays constant regardless of data
D.Grows, so the prior overwhelms the data
Correct Answer: Diminishes, so the posterior is dominated by the likelihood
Explanation:
With large , the likelihood concentrates sharply and swamps a fixed proper prior, so posteriors from different reasonable priors converge—a form of Bayesian consistency.
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54A strong positive linear correlation () is found between ice-cream sales and drowning incidents. The best explanation is:
statistical analysis
Hard
A.Drownings cause increased ice-cream sales
B.The correlation must be a computational artifact
C.A likely confounder (e.g., temperature) drives both; correlation does not imply causation
D.Ice-cream consumption causes drowning
Correct Answer: A likely confounder (e.g., temperature) drives both; correlation does not imply causation
Explanation:
A lurking variable such as hot weather increases both quantities, producing spurious correlation. Association alone cannot establish a causal link.
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55For a one-sample -test with , the degrees of freedom and the reason are:
t-test
Hard
A., because two parameters are estimated
B., because equals the sample size
C., because
D., because one parameter (the sample mean) is estimated from the data
Correct Answer: , because one parameter (the sample mean) is estimated from the data
Explanation:
The one-sample -test uses the sample mean to estimate the standard error, consuming one degree of freedom: .
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56A study is 'underpowered.' What is the most direct risk this poses to interpreting a non-significant result?
hypothesis testing
Hard
A.The -value is guaranteed to be below
B.The Type I error rate is inflated above
C.The confidence interval will be too narrow
D.A true effect may exist but go undetected (high Type II error)
Correct Answer: A true effect may exist but go undetected (high Type II error)
Explanation:
Low power means a high : real effects are often missed. A non-significant result from an underpowered study is inconclusive, not evidence of no effect.
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57A two-way ANOVA shows a significant interaction between Factor A and Factor B. How should the main effects be interpreted?
ANOVA
Hard
A.As fully independent and directly interpretable
B.As identical to the interaction effect
C.With caution, because the effect of one factor depends on the level of the other
D.As automatically non-significant
Correct Answer: With caution, because the effect of one factor depends on the level of the other
Explanation:
A significant interaction means the factors' effects are not additive; interpreting main effects in isolation can be misleading, so simple-effects analyses are preferred.
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58Which practice most directly leads to 'p-hacking' and inflated false-positive rates?
significance of p-value
Hard
A.Trying many analyses and reporting only those with
B.Pre-registering a single hypothesis before data collection
C.Correcting for multiple comparisons
D.Reporting effect sizes with confidence intervals
Correct Answer: Trying many analyses and reporting only those with
Explanation:
Selectively reporting significant results out of many analyses exploits random variation, so the reported -values no longer reflect the true false-positive rate.
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59For a contingency table with rows and columns, the degrees of freedom for the chi-square test of independence are:
chi-square
Hard
A.
B.
C.
D.
Correct Answer:
Explanation:
Independence uses row and column marginals as constraints, leaving freely varying cells, which sets the degrees of freedom.
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60You flip a coin 10 times and get 8 heads. Using a uniform prior on the head probability , the posterior distribution is:
bayesian probability
Hard
A.
B.
C.
D.
Correct Answer:
Explanation:
The Beta is conjugate to the binomial: posterior .
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