뒤로Two Proportions definitions
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1/15뒤로Skip to main content뒤로Null Hypothesis
Default assumption that two population proportions are equal, often represented as p₁ = p₂. Alternative Hypothesis
Statement suggesting a difference exists between two population proportions, such as p₁ ≠ p₂. Test Statistic
Value, typically a z-score, calculated to measure the difference between sample proportions relative to expected variation. P-value
Probability of observing a test statistic as extreme as, or more extreme than, the one calculated, assuming the null hypothesis is true. Significance Level
Threshold, often denoted alpha, used to decide whether to reject the null hypothesis, such as 0.05. Confidence Interval
Range of values, based on sample data, likely to contain the true difference between population proportions. Point Estimate
Best guess for the difference between two population proportions, calculated from sample data. Margin of Error
Amount added and subtracted from the point estimate to create the confidence interval, reflecting sampling variability. Critical Value
Z-score corresponding to the desired confidence level, used in constructing confidence intervals. Pooled Proportion
Weighted average of sample proportions, combining successes and trials from both groups for hypothesis testing. Random Sampling
Method ensuring each subject in the population has an equal chance of selection, supporting valid inference. Independence
Condition where the outcome of one sample does not affect the outcome of the other, required for valid results. Successes and Failures Condition
Requirement that each sample has at least five successes and five failures to justify normal approximation. Two-tailed Test
Hypothesis test considering deviations in both directions from the null value, often used with p₁ ≠ p₂. TI-84 Calculator
Tool used to perform hypothesis tests and construct confidence intervals for two proportions efficiently.
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