"Skewnesses" Example Sentences
1. The asymmetric distribution revealed several skewnesses in the data.
2. Skewnesses in the data were causing problems with the analysis.
3. There were multiple skewnesses in the distribution, making it difficult to interpret.
4. Identifying the skewnesses in the data was an important step in the analysis.
5. The outliers were contributing to the skewnesses in the data.
6. Correcting the skewnesses in the distribution improved the accuracy of the model.
7. The skewnesses in the data were particularly noticeable at the higher end of the range.
8. The researchers found several significant skewnesses in the data set.
9. The skewnesses in the data made the interpretation of results more challenging.
10. It was necessary to address the skewnesses in the data before proceeding with the analysis.
11. The skewnesses in the distribution were caused by a few extreme values.
12. The data had multiple skewnesses, indicating that it was not normally distributed.
13. The skewnesses in the data were particularly problematic for hypothesis testing.
14. Identifying skewed variables was important for detecting potential skewnesses in the analysis.
15. The skewnesses in the data were resolved by transforming the variables.
16. To account for the skewnesses in the data, a non-parametric test was used.
17. The presence of skewnesses in the data made it necessary to use specialized statistical methods.
18. The skewnesses in the data suggested that there were hidden factors influencing the results.
19. The distribution had several skewnesses, indicating that it was not a perfect fit.
20. Correcting the skewnesses in the data improved the reliability of the results.
21. The skewnesses in the data were causing the model to overfit the data.
22. The presence of skewnesses in the data made it necessary to adjust the significance level.
23. The skewnesses in the data were causing the test statistics to be biased.
24. Data with multiple skewnesses can be challenging to analyze.
25. Addressing the skewnesses in the data improved the validity of the analysis.
26. The skewnesses in the data were addressed by removing the outliers.
27. The researchers identified several sources of skewnesses in the dataset.
28. The skewnesses in the sample were different from those in the population.
29. The presence of skewnesses in the data suggested that the sample was not representative.
30. Accurately identifying the skewnesses in the data was a critical step in the analysis.
Common Phases
1. The
skewnesses of the data set are not normal;
2. The extreme value in the data is causing some
skewnesses;
3. The multiple
skewnesses in this distribution suggest a complex relationship between variables;
4. We need to examine the
skewnesses in the data to understand the distribution;
5. The
skewnesses in the sample are not statistically significant;
6. There are some noticeable
skewnesses in the tails of the distribution;
7. The
skewnesses are causing problems with our analysis;
8. The presence of
skewnesses is making it difficult to compare the means of the groups;
9. The
skewnesses in the data are affecting the accuracy of our predictions;
10. The
skewnesses in the data may be due to outliers.