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Steps in Hypothesis Testing definitions

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  • Null Hypothesis

    A default claim about a population parameter, typically involving equality, assumed true until evidence suggests otherwise.
  • Alternative Hypothesis

    A competing claim to the null, representing what the researcher seeks evidence for, often involving inequality.
  • Test Statistic

    A calculated value, such as a z or t score, that measures how far sample data deviates from the assumed population parameter.
  • Z Score

    A standardized value indicating how many standard deviations a sample statistic is from the population mean.
  • T Score

    A standardized value used when population standard deviation is unknown, reflecting sample mean deviation from the population mean.
  • P Value

    A probability quantifying how likely observed sample results are, assuming the null hypothesis is true.
  • Significance Level

    A threshold, often denoted alpha, that determines how unlikely a result must be to reject the null hypothesis.
  • Critical Region

    The set of values for the test statistic where the null hypothesis is rejected, defined by the significance level.
  • Left Tailed Test

    A test where the alternative hypothesis suggests a parameter is less than a specific value, focusing on the lower tail.
  • Right Tailed Test

    A test where the alternative hypothesis suggests a parameter is greater than a specific value, focusing on the upper tail.
  • Two Tailed Test

    A test where the alternative hypothesis suggests a parameter differs from a specific value, considering both tails.
  • Population Parameter

    A numerical value summarizing a characteristic of an entire population, such as mean, proportion, or standard deviation.
  • Sample Statistic

    A numerical value calculated from sample data, used to estimate or test claims about a population parameter.
  • Rejection Rule

    A guideline comparing the p value to the significance level to decide whether to reject or fail to reject the null hypothesis.
  • Evidence

    The degree to which sample data supports or contradicts a claim about a population, influencing hypothesis test conclusions.