What is the formula for the standard error (SE) in a two-sample z-interval?

SE = √(p̂1(1-p̂1)/n1 + p̂2(1-p̂2)/n2)

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What is the formula for the standard error (SE) in a two-sample z-interval?

SE = √(p̂1(1-p̂1)/n1 + p̂2(1-p̂2)/n2)

What is the formula for a two-sample z-interval?

(p̂1 - p̂2) ± z* * √(p̂1(1-p̂1)/n1 + p̂2(1-p̂2)/n2)

How do you calculate the point estimate for the difference of two proportions?

p̂1 - p̂2

What is the formula for the lower bound of a two-sample z-interval?

(p̂1 - p̂2) - z* * √(p̂1(1-p̂1)/n1 + p̂2(1-p̂2)/n2)

What is the formula for the upper bound of a two-sample z-interval?

(p̂1 - p̂2) + z* * √(p̂1(1-p̂1)/n1 + p̂2(1-p̂2)/n2)

Explain the concept of the Randomness condition for two-sample z-intervals.

Both samples must be random samples to generalize findings to the population.

Explain the concept of the Independence condition for two-sample z-intervals.

Each population should be at least 10 times larger than its respective sample size (10% condition), or random assignment is used.

Explain the concept of the Normality condition (Large Counts) for two-sample z-intervals.

Both samples must have at least 10 expected successes and 10 expected failures: n₁p̂₁ ≥ 10, n₁(1-p̂₁) ≥ 10, n₂p̂₂ ≥ 10, and n₂(1-p̂₂) ≥ 10.

Explain the importance of checking conditions before constructing a two-sample z-interval.

Checking conditions ensures the validity of the inference and that the results can be reliably generalized.

Explain how to interpret a two-sample z-interval.

We are [confidence level]% confident that the true difference in [context] is between [lower bound] and [upper bound].

What is a two-sample z-interval?

A confidence interval used to estimate the difference between two population proportions for a categorical variable.

Define point estimate in the context of two-sample z-intervals.

The difference between the two sample proportions: p̂1 - p̂2.

What is the margin of error in a two-sample z-interval?

The 'buffer zone' around the point estimate, calculated using the critical value (z-score) and standard error.

Define standard error (SE) in the context of two-sample z-intervals.

A measure of the variability of the difference between two sample proportions.

What does it mean if a two-sample z-interval contains 0?

It suggests there might not be a significant difference between the two population proportions.