What is Statistics? (Lecture Notes)

1. State examples of statistical questions.
2. State the five main steps in the statistical analysis of data.

Chapter 1

Individuals and variables

1. Define individual and variable in the context of a data set.
2. Identify the individuals and variables given the description of a data set.
3. Explain how the concept of individual and variable relates to the rows and columns of a typical spreadsheet containing a data set.

Identifying categorical and quantitative variables

1. State the characteristics of quantitative and categorical variables.
2. Given a variable, determine whether it is quantitative or categorical.

Quantitative variables: histograms

1. Construct a rug plot by-hand given a (small) data set.
2. Construct a histogram by-hand given a (small) data set and the desired bin width and starting boundary.

Interpreting histograms

1. Identify key characteristics of the shape of a histogram.
2. Identify key characteristicss of the center of a histogram.
3. Identify key characteristics of the spread of a histogram.
4. Identify potential outliers using a histogram in conjunction with a rug plot.
5. Interpret a histogram in the context of the data set it summarizes.

R (Lecture Notes)

1. Use R for basic arithmetic.
2. Load a data frame into RStudio.
3. Load a package (such as mosaic) into RStudio.
4. State the grammar used by functions in mosaic.
5. Generate a rug plot using mosaic’s gf_rugx function.
6. Generate a histogram using mosaic’s gf_histogram function, and specify the bin width and starting boundary by passing arguments to gf_histogram.
7. Add a rug plot to a histogram generated by mosaic using the %>% operator.