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Two Proportions Hypothesis Test - Excel definitions

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이 집합의 용어 (15)

  • Null Hypothesis
    Assumes no difference exists between two population proportions; serves as the default claim in hypothesis testing.
  • Alternative Hypothesis
    Represents the claim being tested, suggesting a difference or specific relationship between two population proportions.
  • Sample Proportion
    Calculated by dividing the number of successes in a sample by the sample size, representing observed probability.
  • Pooled Proportion
    Combines successes and sample sizes from both groups to estimate a common probability for hypothesis testing.
  • Z Score
    Quantifies how many standard errors the observed difference in sample proportions is from the hypothesized difference.
  • P Value
    Probability of observing a test statistic as extreme as, or more extreme than, the one calculated, assuming the null is true.
  • Significance Level
    Threshold probability, often set at 0.05, used to decide whether to reject the null hypothesis.
  • Sampling Distribution
    Describes the probability distribution of a statistic, such as the difference in sample proportions, over repeated samples.
  • Test Statistic
    Numerical summary, like a z score, calculated from sample data to assess evidence against the null hypothesis.
  • Alpha
    Symbol representing the significance level, indicating the maximum acceptable probability of a Type I error.
  • Left Tail Probability
    Area under the standard normal curve to the left of the test statistic, used for one-sided hypothesis tests.
  • Excel Function
    Built-in tool, such as NORM.S.DIST or COUNTIF, used to automate calculations in hypothesis testing.
  • Sample Size
    Number of observations in each group, crucial for calculating proportions and standard errors.
  • Standard Error
    Measures the variability of the difference in sample proportions, used in the denominator of the z score formula.
  • Conclusion
    Final decision in hypothesis testing, based on comparing the p value to alpha, about the validity of the null hypothesis.