11. Suppose that we have age data including the following numbers in sorted order
3, 15, 16, 16, 19, 20, 20, 21, 22, 22, 25, 25, 25, 25, 30, 33, 33, 35, 35, 35, 35, 36, 40, 45, 46, 52, 70]
2a.) Use smoothing by bin means to smooth the above data, using a bin depth of 3. Illustrate
your steps. Comment on the effect of this technique for the given data.
This technique generalizes our data into groups of 3, increasing our previous minimum and decreasing our
previous maximum.
3b.) How can you determine outliers in the data? s)
Outliers are typically determines by the Interquartile Range (IQR). If a value is outside 1.5 times the IQR we
call it an outlier.
As seen in part a.) l = 27, thus our smallest value, idx 0, and our largest value, idx 27, are shown here. 13 & 17
would generally be accepted as outliers.
4c.) Use min-max normalization to transform the value 35 for age onto the range [0.0, 1.0].
We can see min-max normalization transforms 35 into 0.386 .
\
d.) Use z-score normalization to transform the value 35 for age?
We can see z-score normalization transforms 35 into 0.389 .
e.) Use normalization by decimal scaling to transform the value 35 for age. (
We can see normalization transforms by decimal scaling 35 into 0.35 .
52. Write a function in your preferred language which can take a data vector and do min-max
normalization by transforming data onto a desired range
d
