Degrees of Freedom > 10 is not a way to check for the nearly normal condition. the correct answer is option(2).
The quantity of values in a statistic's final calculation that is subject to variation is known as the degree of freedom. Various amounts of data or information can be used to estimate statistical parameters.
Nearly Normal Condition: The data's histogram appears to be symmetric, generally unimodal, and free of outliers. If yes, moving further with a t-model-based inference is acceptable. In order to determine whether raw data is roughly symmetric, graph a histogram and draw the histogram on your paper. If you don't have access to raw data, see if the issue specifies that the distribution is Nearly Normal.
Before doing certain statistical tests or regressions, you should ensure that your data generally matches a bell-shaped curve. This is known as the assumption of normalcy. Independent Samples t-test is one of the tests that needs normally distributed data.
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The complete question is:
Which is not a way to check for the nearly normal condition?
