Proportions
When calculating a 95% confidence interval for a population proportion, what is the z* value that should be used?
Approximately 2.33
Approximately 1.65
Approximately 2.58
Approximately 1.96
Given a large sample size with minimal expected proportion, which formula alteration for the z-interval is most appropriate when constructing a confidence interval for a population proportion?
Employing Bayesian inference with non-informative priors for estimation.
Applying the continuity correction factor to both the upper and lower bounds.
Utilizing bootstrapping techniques to simulate sampling distribution.
Adjusting the standard error by using the adjusted Wald method.
What should you check about your sample before using it to create a confidence interval?
It consists entirely of numerical measurements without categories.
It includes outliers only.
The responses are all identical.
That it was randomly selected.
Which factor must remain constant when comparing two different percentiles computed using standard normal distributions as part z-scores used constructing percent c.I.s pop.proportions?
Different cumulative probabilities same percentile
Same cumulative probability corresponding percentile
Mean and std.deviation shift to accommodate changes in overall shape of distribution
Same mean and std.deviation regardless whether these correspond to actual underlying distributions
In skewed distributions with outliers present that still meet central limit theorem conditions (CLT), what measure can you take during construction of confidence intervals around means rather than medians despite potential robustness concerns?
Introduce winsorization processes truncating distribution tails before analysis.
Increasing sample sizes further beyond CLT requirements until empirical rule approximations hold true.
Use quantile regression methods suited toward median-centered parameters.
Applying Tukey's ladder transformation before calculating standard errors.
What should be increased in order to decrease the margin of error when estimating the population proportion of left-handed students at a high school using confidence intervals?
Sample size
Variance within the sample data
Range of values in the population
Level of significance (alpha)
What is the best interpretation of a 95% confidence interval for a population proportion?
We can expect 95% of sample proportions to fall within the interval.
There is a certainty that exactly 95% of the population is described by this interval.
We are 95% confident that the true population proportion falls within the interval.
The population proportion will be in the interval in 95 out of 100 repeated samples.

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If you must apply finite population correction while estimating confidence intervals for small populations, how would this adjustment affect your calculated margin of error?
It has no effect as it only applies when samples exceed more than half of the population size.
It leads to wider intervals as it assumes increased uncertainty about parameter estimates in small populations.
It would increase due to higher variability associated with smaller populations.
It would decrease if sampled without replacement from less than 5% of the population.
How close should the initial pilot study estimate used prior to the calculation of margin of errors reflect the true parameter before proceeding to full-scale survey collection efforts?
Somewhat Near Estimations Roughly Five Percent Point Range
Large Deviation Greater Than Eight Percentage Points Away From Any Initial Estimates
Regardless of Precision, Any Initial Estimates Are Acceptable As Long As Adjustments Are Made During Actual Collection Phases
Appropriate Close Approximation Within Three Percent Points
If the margin of error for a confidence interval is desired to be smaller, while keeping the same level of confidence, what impact does this have on the necessary sample size?
The sample size can remain unchanged.
The sample size must increase.
The sample size must decrease.
The effect on the sample size cannot be determined without additional information.