Checking Assumptions of Anova Flag QuestionUse the exact code below to generate data for 2 samples.import numpy as npfrom scipy.stats import normnp.random.seed(1)sample_1 = np.random.normal(size=1000)sample_2 = sample_1 + np.random.normal(size = 1000)We need to check if can apply ANOVA on these sample or not.Assumptions you need test:Is the data in both samples normally distributed?Does the distributions have the same variances ?Use 95% confidence level to test above assumtions with appropriate test.Select the correct option - Shapiro test for checking Gaussian , Levene test for checking equal varaince, Conclusion : Both Samples follow normal distribution, Both Samples Have different variances Leven test for checking Gaussian ,Shapiro test for checking equal varaince, Conclusion : Both Samples follow normal distribution, Both Samples Have equal variances Leven test for checking Gaussian ,Shapiro test for checking equal varaince, Conclusion : Sample_2 doesn't follow normal distribution, Both samples Have different variances Shapiro test for checking Gaussian , Levene test for checking equal varaince, Conclusion : Both Samples follow normal distribution, Both Samples Have equal variances
Question
Checking Assumptions of Anova Flag QuestionUse the exact code below to generate data for 2 samples.import numpy as npfrom scipy.stats import normnp.random.seed(1)sample_1 = np.random.normal(size=1000)sample_2 = sample_1 + np.random.normal(size = 1000)We need to check if can apply ANOVA on these sample or not.Assumptions you need test:Is the data in both samples normally distributed?Does the distributions have the same variances ?Use 95% confidence level to test above assumtions with appropriate test.Select the correct option - Shapiro test for checking Gaussian , Levene test for checking equal varaince, Conclusion : Both Samples follow normal distribution, Both Samples Have different variances Leven test for checking Gaussian ,Shapiro test for checking equal varaince, Conclusion : Both Samples follow normal distribution, Both Samples Have equal variances Leven test for checking Gaussian ,Shapiro test for checking equal varaince, Conclusion : Sample_2 doesn't follow normal distribution, Both samples Have different variances Shapiro test for checking Gaussian , Levene test for checking equal varaince, Conclusion : Both Samples follow normal distribution, Both Samples Have equal variances
Solution
The correct option is: Shapiro test for checking Gaussian , Levene test for checking equal variance, Conclusion : Both Samples follow normal distribution, Both Samples Have equal variances.
Here's how you can check these assumptions:
- Shapiro-Wilk Test for Normality: This test checks if the data is normally distributed. We can use the
scipy.stats.shapiro()function to perform this test.
from scipy.stats import shapiro
stat, p = shapiro(sample_1)
print('Statistics=%.3f, p=%.3f' % (stat, p))
stat, p = shapiro(sample_2)
print('Statistics=%.3f, p=%.3f' % (stat, p))
If the p-value is greater than 0.05, we can assume that the data is normally distributed.
- Levene's Test for Equality of Variances: This test checks if the variances are equal for all samples. We can use the
scipy.stats.levene()function to perform this test.
from scipy.stats import levene
stat, p = levene(sample_1, sample_2)
print('Statistics=%.3f, p=%.3f' % (stat, p))
If the p-value is greater than 0.05, we can assume that the variances are equal.
After running these tests, you can conclude whether the samples follow a normal distribution and whether they have equal variances.
Similar Questions
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