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Two Proportions definitions

컨트롤 버튼이 '내비게이션' 모드로 변경되었습니다.
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  • Null 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.