In R, before running a t-test, you are required to:

Question

BlackTom AI · Accepted Answer

Question restatement: In R, before running a t-test, you are required to:

Option 1: Have a significant level of 0.05. In standard t-tests, the alpha level (significance level) is not a fixed mandatory pre-step in R; you can choose an alpha value or rely on the default for confidence intervals, but the t.test function does not require you to set a strict 0.05 beforehand. Therefore this option is not a required step.

Option 2: Convert the outcome variable to a factor variable. A t-test compares means between groups and requires a numeric outcome variable. Converting to a factor would make the response non-numeric and inappropriate for a t-test, so this is incorrect.

Option 3: Make a visual of the data. While data exploration and visualization are good practices and can help you understand the data before testing, they are not a formal prerequisite for conducting a t-test in R. The test itself can be run without creating plots, so this is not a required step.

Option 4: None of the above. Given that options 1–3 describe steps that are not strictly required before performing a t-test in R, this option aligns with the factual requirement (that none of the previous statements are mandatory prerequisites).

Summary of why the other choices are not required: The t-test requires a numeric outcome and appropriate grouping, but does not mandate a particular alpha before the test, nor does it require the data to be visualized prior to testing. Hence, the statement that none of the above are required best fits standard practice.

In R, before running a t-test, you are required to:

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