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1) In a boxplot, the horizontal line inside the box marks the sample median.
2) The box in a boxplot spans the mean ± one standard deviation.
3) Boxplot whiskers always extend to the minimum and maximum observed values.
4) Points plotted beyond the whiskers are commonly labeled as outliers by the 1.5×IQR rule.
5) A left‑skewed (negatively skewed) distribution often shows a longer left whisker and typically has mean < median.
6) Exactly 50% of the data lie between the two whisker ends.
7) The center of the box (its midpoint) always equals the sample mean.
8) The interquartile range (IQR) used in boxplots equals Q3 − Q1.
9) Scatter plots are primarily for relationships between two categorical variables.
10) The Pearson correlation coefficient measures the strength of linear association.
11) A correlation of 0 guarantees there is no relationship of any kind between the variables.
12) Swapping the x‑ and y‑axes changes the correlation coefficient.
13) A single extreme outlier in a scatter plot can strongly influence the correlation and the fitted regression line.
14) Changing units from inches to centimeters will change the value of the correlation coefficient.
15) A high correlation (e.g., r = 0.9) proves that changes in x cause changes in y.
16) A normal probability (Q–Q) plot compares the sample quantiles to theoretical normal quantiles.
17) If points fall roughly on a straight line in a normal Q–Q plot, the data are broadly consistent with normality.
18) A Q–Q plot requires binning the data into histogram bars first.
19) In a normal probability plot, a systematic S‑shaped deviation from the line indicates possible non‑normality.