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Questions and Answers
What is the purpose of the null hypothesis in hypothesis testing?
What is the purpose of the null hypothesis in hypothesis testing?
What does a significance level (α) of 0.05 indicate?
What does a significance level (α) of 0.05 indicate?
Which error occurs when the null hypothesis is rejected even though it is true?
Which error occurs when the null hypothesis is rejected even though it is true?
In hypothesis testing, what is calculated after summarizing the data?
In hypothesis testing, what is calculated after summarizing the data?
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What is the role of the alternative hypothesis in hypothesis testing?
What is the role of the alternative hypothesis in hypothesis testing?
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What does a smaller p-value indicate regarding the null hypothesis?
What does a smaller p-value indicate regarding the null hypothesis?
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Which hypothesis represents the claim that there is no effect or no difference?
Which hypothesis represents the claim that there is no effect or no difference?
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What should be concluded if the p-value is greater than the significance level (α)?
What should be concluded if the p-value is greater than the significance level (α)?
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Which statistical calculation is NOT typically performed when summarizing the data?
Which statistical calculation is NOT typically performed when summarizing the data?
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What is the typical significance level (α) used to determine the rejection of the null hypothesis?
What is the typical significance level (α) used to determine the rejection of the null hypothesis?
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Study Notes
Hypothesis Testing
- A statistical method used to determine if there is enough evidence in a sample to support a particular belief (hypothesis) about a population.
- Widely used in scientific research.
- Helps in making data-driven decisions.
- Essential in validating research findings and determining the effectiveness of drugs, treatments, and interventions in pharmacy.
Steps in Hypothesis Testing
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State the Hypotheses:
- Null Hypothesis (H0): A statement that there is no effect or no difference, serving as the default assumption.
- Alternative Hypothesis (Ha): A statement that there is an effect or a difference, representing what you want to prove.
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Choose the Significance Level (α):
- Probability of rejecting the null hypothesis when it is true.
- Commonly used values are 0.05 (5%) or 0.01 (1%).
- Collect and Summarize the Data: Obtain a sample and calculate relevant statistics, such as the mean, standard deviation, or proportion.
- Calculate the Test Statistic: Based on the data, calculate a test statistic that helps determine whether to reject or not reject the null hypothesis.
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Determine the p-value:
- Indicates the probability of obtaining the observed results if the null hypothesis is true.
- A smaller p-value suggests stronger evidence against the null hypothesis.
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Make a Decision:
- If the p-value is less than the significance level (α), reject the null hypothesis.
- Otherwise, do not reject the null hypothesis.
Understanding p-value and Significance Level (α)
- p-value: The probability under the assumption of no effect or no difference (null hypothesis), of obtaining a result equal to or more extreme than what was actually observed.
- Significance Level (α): The threshold set for rejecting the null hypothesis, often set at 0.05 (5%).
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Decision Rule:
- If p-value ≤ α: Reject H0.
- If p-value > α: Do not reject H0.
Errors in Hypothesis Testing
- Type I Error (α): Rejecting H0 when it is true (false positive). e.g., Concluding a drug is effective when it is not.
- Type II Error (β): Not rejecting H0 when it is false (false negative). e.g., Concluding a drug is not effective when it actually is.
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Description
Explore the fundamental principles of hypothesis testing, a crucial statistical method used in scientific research. This quiz covers the steps involved, from stating hypotheses to collecting and summarizing data, providing a solid foundation for making data-driven decisions in various fields, including pharmacy.
