Understanding Normal Distribution Testing

Why is it important for data to be normally distributed when conducting hypothesis tests?

• It is a common requirement for many hypothesis tests.

• It guarantees a higher p-value.

• It ensures the data is accurate.

• It makes data collection easier.

Which of the following is NOT an analytical test for normal distribution?

• Chi-square test

• Kolmogorov-Smirnov test

• Anderson-Darling test

• Shapiro-Wilk test

What does a p-value greater than 0.05 typically indicate in normal distribution tests?

• Data is perfectly symmetrical.

• Data is normally distributed.

• Data is not normally distributed.

• Data is skewed.

What is a major limitation of analytical methods for testing normal distribution?

• They are too complex to perform.

• They require a large sample size.

• The p-value is influenced by sample size.

• They are not widely accepted.

How does sample size affect the p-value in normal distribution tests?

• Larger samples always increase the p-value.

• Smaller samples always decrease the p-value.

• Sample size has no effect on the p-value.

• Larger samples can decrease the p-value even if the distribution is normal.

Which graphical method is considered better for checking normal distribution?

• QQ plot

• Pie chart

• Bar chart

• Histogram

In a QQ plot, what indicates that data is perfectly normally distributed?

• All points form a circle.

• All points are scattered randomly.

• All points lie on a line.

• All points lie on a curve.

What does it mean if data points in a QQ plot form an arc away from the line?

• Data is skewed to the left.

• Data is perfectly normally distributed.

• Data is skewed to the right.

• Data is not normally distributed.

What is the first step in testing data for normal distribution using software?

• Select the variable to test.

• Perform a t-test.

• Plot a histogram.

• Calculate the mean.

Which test can be used if data is not normally distributed?

• ANOVA

• T-test

• Chi-square test

• Mann-Whitney U test