Skip to main content
뒤로

Critical Values and Rejection Regions definitions

컨트롤 버튼이 '내비게이션' 모드로 변경되었습니다.
1/15
  • Hypothesis Test
    A procedure for evaluating claims about a population parameter using sample data and statistical evidence.
  • Null Hypothesis
    A statement asserting no effect or no difference, serving as the default assumption in statistical testing.
  • Alternative Hypothesis
    A statement proposing a change or difference from the null, representing what researchers seek evidence for.
  • Critical Value
    A threshold derived from the significance level, marking the boundary between typical and unusual test statistics.
  • Significance Level
    A probability, denoted by alpha, indicating the risk of incorrectly rejecting the null hypothesis.
  • Rejection Region
    An area in the distribution where test statistics are considered extreme enough to reject the null hypothesis.
  • Test Statistic
    A calculated value, such as a z-score, summarizing sample data for comparison against critical values.
  • P Value
    A probability measuring the strength of evidence against the null hypothesis, based on the test statistic.
  • Left-Tail Test
    A hypothesis test where the rejection region is in the lower end of the distribution, indicating values less than expected.
  • Right-Tail Test
    A hypothesis test with the rejection region in the upper end, focusing on values greater than expected.
  • Two-Tail Test
    A hypothesis test with rejection regions in both extremes, assessing deviations in either direction from the expected value.
  • Z Table
    A reference chart listing probabilities and critical values for the standard normal distribution.
  • Sample Size
    The number of observations in a sample, influencing the reliability and validity of statistical conclusions.
  • Population Standard Deviation
    A measure of variability in the entire population, used in calculating test statistics for hypothesis tests.
  • Normal Distribution
    A symmetric, bell-shaped curve describing the spread of data, foundational for many statistical tests.