Comparing Distributions
About the Lecture
The lecture Comparing Distributions by David Spade, PhD is from the course Statistics Part 1. It contains the following chapters:
- Comparing Distributions
- Side-by-Side Comparisons
- Data Transformation
Included Quiz Questions
When we compare multiple groups using histograms, what information can we get?
- We can determine whether the distributions have different numbers of modes.
- We can determine the exact distribution of data points.
- We can evaluate categorical variables.
- We cannot evaluate continuous data.
- We can visualize symmetric data but we cannot visualize bimodal data.
When we compare two groups using side-by-side box plots, what information about the two distributions is hidden?
- We cannot tell whether one distribution has more modes than the other.
- We cannot tell whether the distributions are centered in different places.
- We cannot tell whether one distribution has a higher spread than the other.
- We cannot tell whether there are outliers in any distribution.
- We cannot tell the range of data.
What is one problem with skewed data?
- It can be difficult to summarize their distribution using center and spread.
- They cannot be summarized using a box plot.
- They cannot be summarized using a histogram.
- It is not possible to calculate the mean.
- It is not possible to calculate the standard deviation.
What is a common way to make skewed data more symmetric?
- Skewed data are often made more symmetric by transforming them using the natural logarithm.
- Skewed data is often made more symmetric by discarding the observations in the tail.
- Skewed data is often made more symmetric by multiplying each observation by a constant.
- If data is skewed, there is no way to make them more symmetric.
- Skewed data are made more symmetric by adding a constant to each data point.
Which of the following makes comparison of distributions difficult?
- Comparing distributions is more difficult if the two data sets are not on the same scale.
- Comparing distributions is challenging if there are a different number of data points between the data sets.
- Comparing distributions is made more difficult by ignoring outliers altogether
- Comparing distributions is made more difficult when both distributions have the same center and spread
- Comparing distributions is more challenging with smaller data sets.
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Author of lecture Comparing Distributions
David Spade, PhD
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