Download Unit 2 Learning Targets

Integrate 1X Unit 2 Patterns in Data
Target 1: Exploring Distributions
Key terms – you should be able to define and apply each key term:
single variable data – dot plots – histograms – frequency – relative frequency – shape of distribution – center of
distribution – median – mode - approximately normal – symmetric – tail – skewed right – skewed left – summary
statistics - resistant to outliers – range – balance point –

Formulas:
Range = maximum value – minimum value
Mean = Sum of the numbers / the number of numbers
Median is located at the (n+1)/2 data point in an ordered list
 x  xn
Skills:
Construct dot plots, histograms, and relative frequency histograms
Describe the shape of a distribution (SOCS) (MS 9.4.1.4)
Use the mean, median, and mode to describe the center of a data set presented in a graph or in a
table (MS 9.4.1.1)
Estimate the mean and median from a histogram
Calculate the mean and median from a list or frequency table.
Find a missing value in a set of data when given the mean, other values, and the number of
n
values.
Calculate values from a list of data involving 
ia
notation.
Target 2: Measuring Variability
Key Terms – you should be able to define and apply each key term:
Percentile – five number summary – lower (1st) quartile – upper (3rd) quartile – minimum – maximum – box-andwhiskers plot – Interquartile range (IQR) – extreme value – standard deviation – deviation from the mean – outliers
Formulas:
IQR = 3rd quartile – 1st quartile
Percentile = (Part / Whole) * 100
Identifying outliers – More than 1.5 * IQR above the 3rd quartile or less than 1.5 * IQR below the 1 st quartile
Standard Deviation (s) =
s
 ( x  x)
2
n 1
Deviation from the mean = value – mean or x  x
Skills:
Find and interpret percentiles and quartile as measures of the position of a value in a distribution
Find the five-number summary and the interquartile range (IQR) and interpret the IQR as a
measure of variability (MS 9.4.1.1)
Determine if a value is and outlier
Construct and interpret a box plot
Compute and interpret deviations from the mean (MS 9.4.1.1)
Compute or estimate and interpret the standard deviation as a measure of spread form a lsit of
data or a frequency table. (MS 9.4.1.1)
Predict the effect on the shape, center, and spread of a distribution when the same number is
added to each value or when each value is multiplied by the same number. (MS 9.4.1.2)
Integrate 1X Unit 2 Patterns in Data
Previously Learned Material
Vocabulary Developed in this Unit
single variable data
dot plots
histograms
frequency
relative frequency
shape of distribution
center of distribution
median
mode
approximately normal
symmetric
tail
skewed right
skewed left
summary statistics
resistant to outliers
range

Percentile
five number summary
lower (1st) quartile
upper (3rd) quartile
minimum
maximum
box-and-whiskers plot
Interquartile range (IQR)
extreme value
standard deviation
deviation from the mean
outliers