A complete summary of the chapters from Moore, McCabe and Craig that are important and are discussed in block 1.3. Also very convenient for block 2.2, as all the chapters you need to know again!
Summary 1.3 MMC Important stuff (except chapter 2)
Chapter 1 – Looking at data: distributions
Categorical or quantitative variable
Categorical variable places a case into one of serveral groups of categories.
Quantitative variable takes numerical values for which arithmetic operations such as
adding and averaging make sense.
Cases, labels and variables
Cases = the objects described by a set of data.
Label = a special variable used in some data sets to distinguish the different cases.
Variable = characteristic of a case.
Displaying distributions with graphs
Categorical variables
Bar graph
Pie chart
Quantitative variables
Stemplot
Back-to-back stemplot
Histogram
Describing distributions with numbers
The mean (average value).
The median (middle value – midpoint of a distribution).
The quartiles (Q1 = median of the observations left from median & Q3 = the median
of the observations right from the median).
The five-number summary (Minimum – Q1 – Median – Q3 – Maximum).
IQR (interquartile range = Q3 – Q1).
When is something an outlier?
IQR x 1.5 above the third quartile & IQR x 1.5 below the first quartile.
Everything outside these values = outlier.
Standarddeviation
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