Significance Test
Definition
A significance test is a statistical method used to determine whether an observed result is statistically significant or simply due to chance. It involves comparing sample data with what would be expected under the null hypothesis.
Analogy
Imagine you are playing darts and trying to determine if your aim is significantly better than random chance. A significance test would help you analyze your dart throws and decide if your accuracy exceeds what would be expected by luck alone.
Related terms
P-value: The p-value represents the probability of obtaining results as extreme as those observed, assuming the null hypothesis is true.
Confidence Interval: A confidence interval provides a range of values within which we can be confident (at a certain level) that the population parameter lies.
One-sample t-test: A one-sample t-test compares the mean of a single sample with a known population mean.
"Significance Test" appears in:
Study guides (3)
Additional resources (1)
Practice Questions (11)
- What is the first step in solving a significance test?
- What information should be included in the conclusion when performing a significance test?
- When performing a significance test for a population mean, what is the test statistic used?
- How do we check the normal condition when conducting a significance test for the difference in two population proportions?
- What conditions must be met to ensure that a significance test for the difference in two population proportions can be appropriately conducted?
- Suppose you conduct a significance test for the difference in two population proportions with the significance level set at 0.10. If the p-value is 0.17, what can you conclude?
- A researcher is using a z-score to perform a significance test for the difference in two population proportions. The calculated z-score is -1.8. What can the researcher conclude?
- Why is it important to check for sampling bias before proceeding to a significance test?
- What does a large p-value suggest in a significance test?
- What are we checking with a significance test?
- An article claims that wearing a specific brand of shoes enhances athletic performance. To investigate this, researchers randomly assigned 100 participants to wear either the brand's shoes or a different brand during physical tests. They found that participants wearing the specific brand of shoes performed better, on average, compared to those wearing the alternative brand. The calculated p-value from the significance test was 0.025. Which is the best interpretation of the p-value?
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