BackTwo Proportions definitions
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1/15BackSkip to main contentBackNull Hypothesis
Default assumption that two population proportions are equal, forming the basis for statistical comparison. Alternative Hypothesis
Statement suggesting a difference exists between two population proportions, guiding the direction of the test. Z Score
Standardized value used to measure the difference between sample proportions relative to expected variation. P Value
Probability of observing a result as extreme as the sample, used to determine statistical significance. Alpha
Threshold for statistical significance, often set at 0.05, used to decide whether to reject the null hypothesis. Confidence Interval
Range estimating the difference between two population proportions, indicating the level of certainty in the result. Point Estimate
Best guess for the difference between two sample proportions, forming the center of the confidence interval. Margin of Error
Amount added and subtracted from the point estimate to create the confidence interval, reflecting sampling variability. Pooled Proportion
Weighted average of successes across both samples, used in hypothesis testing to calculate expected variation. Critical Value
Z score corresponding to the chosen confidence level, determining the width of the confidence interval. Sample Proportion
Ratio of successes to total observations in a sample, used to estimate population proportions. Complement
Value representing the proportion of failures, calculated as one minus the sample proportion. Two-Tailed Test
Statistical test considering differences in both directions, used when the alternative hypothesis is not equal. Independence
Condition ensuring that samples do not influence each other, required for valid hypothesis testing. Normality Condition
Requirement that each sample has at least five successes and failures, allowing use of normal approximation.
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