moderate skewed distribution vs Nevertheless,

These two phrases are not comparable as they serve different purposes. 'Moderate skewed distribution' is a term used in statistics to describe a distribution that is not perfectly symmetrical, while 'nevertheless' is a conjunctive adverb used to indicate contrast or concession in a sentence.

Last updated: March 15, 2024 • 912 views

moderate skewed distribution

This phrase is correct in the context of statistics to describe a distribution that is moderately skewed, meaning it is not perfectly symmetrical.

This phrase is used in statistical analysis to describe a distribution that shows some degree of skewness, indicating that the data is not evenly distributed around the mean.

Show examples from the web [+]

Type I error rate estimates of the moderate skewed distribution .......................... 35. 8. Statistical power estimates of the moderate skewed distribution at α = 0.01.
Mar 2, 2006 ... moderate skewed distribution of CDT data in controls, 20 units/liter for males were defined as the upper normal limits (instead of mean + 2 so).

Nevertheless,

This phrase is correct and commonly used in English to indicate a contrast or concession in a sentence.

You can use 'nevertheless' to introduce a contrasting point or to show that something is true despite what has just been said.

Show examples from the web [+]

see definition of nevertheless. Font size. X. Aa. Aa. Aa. Aa. Aa. show. all, adverb. adv however. prev next. still. Ad. Relevance. Relevance ranks synonyms and ...
nonetheless; notwithstanding; however; in spite of that: a small but nevertheless important change. Origin of nevertheless. Expand. Middle English. 1250-1300.
Her date was a bit of a slob, but she had fun nevertheless. It was a predictable, but nevertheless funny, story. I am, nevertheless, a multicellular organism of ...
despite something that you have just mentioned synonym nonetheless There is little chance that we will succeed in changing the law. Nevertheless, it is ...

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moderate skewed distribution vs Nevertheless,