Why are missing values significant challenges in quantitative data analysis?
a. They inhibit the practitioner-scholar from using statistical tests for parametric data.
b. Practitioner-scholars will need to use more complex computer software for conducting quantitative data analysis.
c. Inferential statistical procedures were developed for complete datasets.
d. The null hypothesis will always be rejected.
c. Inferential statistical procedures were developed for complete datasets.
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