Question

Nonnormality or Heteroscedasticity can be remedied by _____.

A) Increasing the sample size
B) Transforming the variables
C) Ignoring the issue
D) Using a different statistical test

Answer 1

Nonnormality or heteroscedasticity in statistics can be remedied by increasing the sample size, transforming the variables, or using a different statistical test.

Step-by-step explanation:

Nonnormality or Heteroscedasticity in statistics refer to violations of assumptions made in certain statistical tests. To remedy these issues:

1. Increasing the sample size can help in cases of nonnormality or heteroscedasticity. A larger sample size can make the distribution of the data closer to normal or reduce the variability between groups.
2. Transforming the variables is another approach. For nonnormality, you can try logarithmic, square root, or power transformations. For heteroscedasticity, you can use variance-stabilizing transformations.
3. Using a different statistical test may be necessary if the assumptions cannot be met even after sample size and variable transformations. There are non-parametric tests available that don't rely on normality or equal variances.