When the x² statistic calculated in a x² test is very high, it means that:
MATLAB: An Introduction with Applications
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Chapter1: Starting With Matlab
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![**Understanding the Chi-Square (χ²) Test**
---
When the **χ² statistic** calculated in a **χ² test** is very high, it means that:
- **[ ]** the results of the test are inconclusive
- **[ ]** the difference between the observed and expected values is likely due to a factor other than chance
- **[ ]** the difference between the observed and expected values is likely due to chance alone
- **[ ]** there is no difference between the observed and expected values
- **[ ]** the experiment was set up incorrectly and should be repeated
---
**Explanation:**
The chi-square (χ²) test is a statistical method used to compare the observed results with the expected results according to a specific hypothesis. If the χ² statistic is very high, it typically suggests that the difference between the observed and expected values is likely due to a factor other than chance. This is because a high χ² value indicates a significant discrepancy between the observed data and what was expected under the null hypothesis. Therefore, it can lead to a rejection of the null hypothesis.
Points to Consider:
- **Null Hypothesis (H₀):** Assumes no significant difference between the observed and expected frequencies.
- **Alternative Hypothesis (H₁):** Assumes a significant difference between the observed and expected frequencies.
**Key Takeaway:**
A very high chi-square statistic generally means that the observed data significantly deviates from the expected data, suggesting the influence of factors other than mere chance.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F54827682-bc2e-453e-8315-80bfd8615b3c%2F9db82d62-b622-47d5-ac81-5f7383313f79%2F7jlsay7_processed.jpeg&w=3840&q=75)
Transcribed Image Text:**Understanding the Chi-Square (χ²) Test**
---
When the **χ² statistic** calculated in a **χ² test** is very high, it means that:
- **[ ]** the results of the test are inconclusive
- **[ ]** the difference between the observed and expected values is likely due to a factor other than chance
- **[ ]** the difference between the observed and expected values is likely due to chance alone
- **[ ]** there is no difference between the observed and expected values
- **[ ]** the experiment was set up incorrectly and should be repeated
---
**Explanation:**
The chi-square (χ²) test is a statistical method used to compare the observed results with the expected results according to a specific hypothesis. If the χ² statistic is very high, it typically suggests that the difference between the observed and expected values is likely due to a factor other than chance. This is because a high χ² value indicates a significant discrepancy between the observed data and what was expected under the null hypothesis. Therefore, it can lead to a rejection of the null hypothesis.
Points to Consider:
- **Null Hypothesis (H₀):** Assumes no significant difference between the observed and expected frequencies.
- **Alternative Hypothesis (H₁):** Assumes a significant difference between the observed and expected frequencies.
**Key Takeaway:**
A very high chi-square statistic generally means that the observed data significantly deviates from the expected data, suggesting the influence of factors other than mere chance.
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