7. The only way to infer a causal association between variables statistically is through data obtained from a 8. In an , we need to be wary of confounding variables. 9. A variable can be visualized using side-by-side histograms or side-by-side boxplots. 10. A variable can be summarized using descriptive statistics such as the mean, median. standard deviation. and ve-number summary. 11. A variable can be visualized using a bar chart or pie chart. 12. A variable can be summarized using descriptive statistics such as the proportion, frequency, or relative frequency. 13. A variable can be summarized using a two way table or a difference in proportion. 14. A variable can be visualized using a scatterplot. 15. A variable can be visualized using a dotplot, histogram, or boxplot. 16. A variable can be summarized using the correlation coefcient or the equation of the regression line. 17. A variable can be visualized using a sidebyside or segmented bar chart. 18. A variable can be summarized using a difference in means. 19. We try to collect a sample that is representative of the population and that avoids 20. Some statistics (such as the median and interquartile range) are to the effects of outliers, while others (such as the mean, standard deviation, and correlation) can be strongly inuenced by extreme values