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Steps in Hypothesis Testing quiz #3

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  • What are the two possible decisions you can make from performing a hypothesis test?
    You can either reject the null hypothesis or fail to reject the null hypothesis.
  • The t-test is principally a test of what?
    The t-test is principally a test of the population mean when the population standard deviation is unknown.
  • In a hypothesis test, if the computed p-value is less than 0.001, what does this indicate?
    If the p-value is less than 0.001, there is very strong evidence to reject the null hypothesis.
  • What is not true for a hypothesis test for correlation?
    It is not true that the null hypothesis for correlation uses a 'not equal to' sign; it typically states that the correlation coefficient equals zero.
  • When testing the difference of means for paired data, what is the null hypothesis?
    The null hypothesis for paired data is that the mean difference between pairs is zero.
  • What is the null hypothesis when using ANOVA procedures?
    The null hypothesis in ANOVA is that all group means are equal.
  • If the null hypothesis is rejected in hypothesis testing, what does this mean?
    If the null hypothesis is rejected, it means there is enough evidence to support the alternative hypothesis.
  • In hypothesis testing, if the null hypothesis is rejected, what is the implication?
    Rejecting the null hypothesis implies that the sample data provides sufficient evidence against the null hypothesis in favor of the alternative.
  • When the p-value is used for hypothesis testing, when is the null hypothesis rejected?
    The null hypothesis is rejected if the p-value is less than the significance level (alpha).
  • What are the main steps in conducting a hypothesis test?
    The main steps are: state the hypotheses, calculate the test statistic, find the p-value, compare p-value to alpha, and make a conclusion.
  • What does it mean for a hypothesis to be testable in the context of hypothesis testing?
    A hypothesis is testable if it makes a specific claim about a population parameter (such as a mean or proportion) that can be evaluated using sample data and statistical methods. This allows us to use a formal procedure, like hypothesis testing, to determine whether there is enough evidence to support or refute the claim.
  • In hypothesis testing, what does it mean to fail to reject the null hypothesis?
    Failing to reject the null hypothesis means that the sample data does not provide sufficient evidence to conclude that the null hypothesis is false. In other words, there is not enough evidence to support the alternative hypothesis, so we continue to assume the null hypothesis may be true.
  • What does it mean when a result is described as 'statistically significant' in hypothesis testing?
    A result is statistically significant if the p-value is less than the chosen significance level (alpha), indicating that the observed sample data is unlikely to have occurred by random chance if the null hypothesis is true. This provides enough evidence to reject the null hypothesis in favor of the alternative hypothesis.
  • What does revising the hypothesis mean in the context of hypothesis testing?
    Revising the hypothesis means modifying the original claim or statement about the population parameter based on the results of the hypothesis test. If the test does not provide enough evidence to support the alternative hypothesis, researchers may adjust their hypotheses and design new tests to further investigate the population.