Test the following hypotheses for a multinomial probability distribution by using the x² goodness of fit test. Ho: PA=0.40, PB = 0.20, and pc = 0.40 Ha The probabilities are not : A sample of size 200 yielded 50 in category A, 100 in category B, and 50 in category C. Use a = 0.01 and test to see whether the probabilities are as stated in Ho. a. Use the p-value approach. Use Table 3 of Appendix B. x² = 153.75 (to 2 decimals) The p-value is less than 0.005 Conclusion: Conclude the proportions differ from 0.4, 0.2, and 0.4. b. Repeat the test using the critical value approach. X0.01 (to 3 decimals) x² = (to 2 decimals) PA = 0.40, PB=0.20, and pc = 0.40 Conclusion: Conclude the proportions differ from 0.4, 0.2, and 0.4.
Test the following hypotheses for a multinomial probability distribution by using the x² goodness of fit test. Ho: PA=0.40, PB = 0.20, and pc = 0.40 Ha The probabilities are not : A sample of size 200 yielded 50 in category A, 100 in category B, and 50 in category C. Use a = 0.01 and test to see whether the probabilities are as stated in Ho. a. Use the p-value approach. Use Table 3 of Appendix B. x² = 153.75 (to 2 decimals) The p-value is less than 0.005 Conclusion: Conclude the proportions differ from 0.4, 0.2, and 0.4. b. Repeat the test using the critical value approach. X0.01 (to 3 decimals) x² = (to 2 decimals) PA = 0.40, PB=0.20, and pc = 0.40 Conclusion: Conclude the proportions differ from 0.4, 0.2, and 0.4.
MATLAB: An Introduction with Applications
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ISBN:9781119256830
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Chapter1: Starting With Matlab
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![### Exercise 12.01 Algo (Goodness of Fit Test)
#### Question 2 of 2
Test the following hypotheses for a multinomial probability distribution by using the \( \chi^2 \) goodness of fit test.
\[ H_0: p_A = 0.40, \, p_B = 0.20, \, \text{and} \, p_C = 0.40 \]
\[ H_a: \text{The probabilities are not} \, p_A = 0.40, \, p_B = 0.20, \, \text{and} \, p_C = 0.40 \]
A sample of size 200 yielded 50 in category A, 100 in category B, and 50 in category C.
Use \( \alpha = 0.01 \) and test to see whether the probabilities are as stated in \( H_0 \).
##### Part (a):
Use the \( p \)-value approach. Use Table 3 of [Appendix B](#).
\[ \chi^2 = 153.75 \, (\text{to 2 decimals}) \]
The \( p \)-value is less than 0.005.
**Conclusion:**
*Conclude the proportions differ from 0.4, 0.2, and 0.4.*
##### Part (b):
Repeat the test using the critical value approach.
\[ \chi^2_{0.01} = \text{(_) (to 3 decimals)} \]
\[ \chi^2 = \text{(_) (to 2 decimals)} \]
**Conclusion:**
*Conclude the proportions differ from 0.4, 0.2, and 0.4.*
The responses for parts (a) and (b) include a chi-squared value of 153.75 and a p-value less than 0.005, leading to the conclusion that the proportions differ from the stated values. However, for part (b), the specific critical values were not provided, resulting in partial correctness.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F52390996-0048-48b9-99d6-ecc2feddac1b%2F96ac131e-4dbd-479f-9ade-25c9ecb45442%2F97y5x4_processed.png&w=3840&q=75)
Transcribed Image Text:### Exercise 12.01 Algo (Goodness of Fit Test)
#### Question 2 of 2
Test the following hypotheses for a multinomial probability distribution by using the \( \chi^2 \) goodness of fit test.
\[ H_0: p_A = 0.40, \, p_B = 0.20, \, \text{and} \, p_C = 0.40 \]
\[ H_a: \text{The probabilities are not} \, p_A = 0.40, \, p_B = 0.20, \, \text{and} \, p_C = 0.40 \]
A sample of size 200 yielded 50 in category A, 100 in category B, and 50 in category C.
Use \( \alpha = 0.01 \) and test to see whether the probabilities are as stated in \( H_0 \).
##### Part (a):
Use the \( p \)-value approach. Use Table 3 of [Appendix B](#).
\[ \chi^2 = 153.75 \, (\text{to 2 decimals}) \]
The \( p \)-value is less than 0.005.
**Conclusion:**
*Conclude the proportions differ from 0.4, 0.2, and 0.4.*
##### Part (b):
Repeat the test using the critical value approach.
\[ \chi^2_{0.01} = \text{(_) (to 3 decimals)} \]
\[ \chi^2 = \text{(_) (to 2 decimals)} \]
**Conclusion:**
*Conclude the proportions differ from 0.4, 0.2, and 0.4.*
The responses for parts (a) and (b) include a chi-squared value of 153.75 and a p-value less than 0.005, leading to the conclusion that the proportions differ from the stated values. However, for part (b), the specific critical values were not provided, resulting in partial correctness.
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