"Skewness" Example Sentences
1. The distribution had a positive skewness, indicating a longer tail on the right side.
2. The data set showed a significant degree of skewness, with most values clustered around the median.
3. The histogram displayed a clear amount of skewness, with a larger number of data points on one side.
4. It is important to consider the skewness of the data when interpreting the results.
5. The outlier values in the data set were responsible for the skewness in the overall distribution.
6. The skewness in the data set made it difficult to determine the true central tendency of the variables.
7. The distribution of the data was highly skewed, indicating a non-normal distribution.
8. The skewness of the data was corrected using a log transformation to normalize the distribution.
9. The skewness of the histogram suggested that the data set may contain some extreme values.
10. The lack of skewness in the data set indicated a relatively uniform distribution of values.
11. The data set had a negative skewness, with most values clustered around the higher end.
12. The skewness in the data was caused by the presence of a few outlier values.
13. The distribution displayed a moderate degree of skewness, which was accounted for in the analysis.
14. It is important to account for the skewness of the data when performing statistical tests.
15. The skewness of the distribution was corrected using a power transformation.
16. The skewness of the data set made it difficult to compare the results to other studies.
17. The degree of skewness in the data set varied depending on the analysis method used.
18. The skewness in the data set was analyzed using a box plot.
19. The distribution was found to have a high degree of positive skewness, indicating a non-normal distribution.
20. The skewness in the data set was accounted for using a robust regression analysis.
21. The skewness in the variable made it difficult to draw any meaningful conclusions from the data.
22. The presence of skewness in the data set could be due to measurement error or sampling bias.
23. The skewness of the data set was evident in the scatter plot.
24. The skewness of the distribution suggested that normality assumptions may not be met.
25. The degree of skewness in the data set was found to be statistically significant.
26. The skewness in the data set may be due to an underlying asymmetry in the population.
27. The level of skewness in the data set required a non-parametric statistical analysis.
28. The presence of skewness in the data set was accounted for using a robust standard error estimation method.
29. The degree of skewness in the data set was reduced using data transformation techniques.
30. The skewness in the data set was found to be closely related to the presence of extreme values.
Common Phases
1. The data distribution is positively skewed
2. The
skewness measure indicates a negatively skewed distribution
3.
Skewness is a measure of the data's asymmetry
4. The
skewness coefficient is higher than 0, indicating a right-skewed distribution
5. The data is skewed towards the right tail
6. The mean is greater than the mode, indicating positive
skewness
7. The distribution has a longer tail on the left, as indicated by negative
skewness
8.
Skewness can affect the accuracy of certain statistical tests
9. The data is not normally distributed due to significant
skewness
10. Transformation of the data may be necessary to correct
skewness.