Proportions

It determines whether a confidence interval can be constructed.

It decreases the width of the confidence interval.

It increases the width of the confidence interval.

It has no effect on the width of the confidence interval.

Median

Standard deviation

Range

Variance

They must ensure that both samples are independent and randomly selected from their respective populations.

Both samples need not only be large but also exactly equal in size for comparison purposes.

They should check if all individuals in both samples strongly support their candidate without any bias.

It is essential that both samples come from populations with the same standard deviation in opinions.

The proportion of students who prefer literature is higher than the proportion who prefer math.

There is not enough information to draw any conclusions.

There is no evidence to support a difference in the proportions of students who prefer math and literature.

The proportion of students who prefer math is higher than the proportion who prefer literature.

Mode

Mean

Variability

Median

There should be at least 30 successes and failures combined across both samples.

Sample sizes must be equal.

The samples must come from normally distributed populations.

Success-failure condition (np and nq should both be greater than or equal to 10)

There is strong evidence to support a difference in the proportions.

The student made a calculation error and should redo the interval.

There is no evidence to support a difference in the proportions.

The sample size was too small to make any inference.

There is no evidence to support a difference in the proportions.

The data collection method was flawed, leading to unreliable results.

The sample size was too small to make any inference.

The proportion of one group is significantly higher than the proportion of the other group.

Each individual observation within each group must follow an identical binomial distribution pattern.

There needs to exist perfect symmetry between success and failure rates within each binomial setting sampled.

There should be at least ten successes and ten failures within each sample group ($n[object Object]$ and $n$(1-p) \geq 10).

Trials within each group must depend on one another so that probabilities remain consistent across observations.

There cannot be any common value between these two populations' proportions.

At least one of the confidence intervals has been calculated incorrectly.

There is evidence to suggest that there may be a difference between the two population proportions.

The larger proportion is definitely greater than twice the smaller one.