Question:
Which of the following is a characteristic of chi-square test?
(A) It is a non-parametric test.
(B) It is based on frequencies and not on parameters like mean and standard deviation.
(C) It can be used when individual observations of the sample are dependent.
(D) It can be used for testing hypothesis but is not useful for estimation.
Choose the correct answer from the options given below:
Which of the following is a characteristic of chi-square test?
(A) It is a non-parametric test.
(B) It is based on frequencies and not on parameters like mean and standard deviation.
(C) It can be used when individual observations of the sample are dependent.
(D) It can be used for testing hypothesis but is not useful for estimation.
Choose the correct answer from the options given below:
(A) It is a non-parametric test.
(B) It is based on frequencies and not on parameters like mean and standard deviation.
(C) It can be used when individual observations of the sample are dependent.
(D) It can be used for testing hypothesis but is not useful for estimation.
Choose the correct answer from the options given below:
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Chi-square tests are useful for categorical data and determining relationships between observed and expected frequencies.
Updated On: Sep 26, 2025
- (A), (B) and (D) only.
- (A), (B) and (C) only.
- (A), (B), (C) and (D).
- (A), (B) and (C) only.
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The Correct Option is D
Solution and Explanation
Step 1: Understand the chi-square test.
The chi-square test is a statistical test used to determine if there is a significant association between observed and expected frequencies. It is a non-parametric test because it does not assume a normal distribution of the data.
Step 2: Analyze each option.
- (A) It is a non-parametric test: Correct. The chi-square test does not assume any underlying distribution of the data, making it a non-parametric test.
- (B) It is based on frequencies and not on parameters like mean and standard deviation: Correct. The chi-square test works with frequency data (observed vs. expected counts) and does not involve parameters such as mean and standard deviation.
- (C) It can be used when individual observations of the sample are dependent: Incorrect. The chi-square test assumes that the observations are independent. It is not appropriate for dependent observations.
- (D) It can be used for testing hypothesis but is not useful for estimation: Correct. The chi-square test is primarily used for hypothesis testing, especially for categorical data, but it does not provide parameter estimates.
Step 3: Conclusion.
The correct answer is (A), (B) and (C) only. The chi-square test is non-parametric, based on frequencies, and is used for hypothesis testing.
The chi-square test is a statistical test used to determine if there is a significant association between observed and expected frequencies. It is a non-parametric test because it does not assume a normal distribution of the data.
Step 2: Analyze each option.
- (A) It is a non-parametric test: Correct. The chi-square test does not assume any underlying distribution of the data, making it a non-parametric test.
- (B) It is based on frequencies and not on parameters like mean and standard deviation: Correct. The chi-square test works with frequency data (observed vs. expected counts) and does not involve parameters such as mean and standard deviation.
- (C) It can be used when individual observations of the sample are dependent: Incorrect. The chi-square test assumes that the observations are independent. It is not appropriate for dependent observations.
- (D) It can be used for testing hypothesis but is not useful for estimation: Correct. The chi-square test is primarily used for hypothesis testing, especially for categorical data, but it does not provide parameter estimates.
Step 3: Conclusion.
The correct answer is (A), (B) and (C) only. The chi-square test is non-parametric, based on frequencies, and is used for hypothesis testing.
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