General Note: Below, where it says ‘define the [statistic] of a data set,’ this means you should know the procedure for computing a given statistic, and be able to express that procedure as a mathematical expression. Generally, you will not be expected to compute sample means, medians, variances, etc., by hand, but I do expect you to know how to compute them by hand.

Section 1.2: Pictorial and Tabular Methods in Descriptive Statistics

1. Construct a frequency, relative frequency, or density histogram given a (small) data set.
2. Compare and contrast frequency, relative frequency, and density histograms in terms of how they represent the distribution of a data set on the real line.

Section 1.3: Measures of Location

1. Define the sample mean of a data set, and specify how we will denote the sample mean.
2. Explain how the sample mean is related to the ‘center of mass’ of a data set.
3. Define the sample median of a data set.
4. Compare and contrast the sample mean and sample median in terms of what sense of ‘center’ of a data set they summarize.

Section 1.4: Measures of Variability

1. Define the sample variance and sample standard deviation of a data set, and specify how we will denote the sample variance and sample standard deviation.
2. Explain why the sample standard deviation is more interpretable than the sample variance.
3. Define the mean absolute deviation of a data set.

R:

1. Construct a vector x in R containing a list of numbers.
2. Compute the mean, median, variance, and standard deviation of a data set using R.