STAT231 Lecture 3: Week 3 recap slides.pdf
17 Jan 2014
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1 n n i=1 xi n x_ x1 + x2 +xn. 1 n 1 n i=1 (xi )2. Histogram: if#we#have#continuous#data#then#it#is# common#to#summarize#it#by#grouping#it# into#classes#or#bins, we#then#record#the#frequency#and# numbers#in#each#bin, a#bar#chart#of#this#frequency#data#is#called# a#histogram, the#area#of#the#bar#represents#the# proportion##of#obesrvations#which#fall#in# interval#covered#by#the#bar, often#frequencies#are#plotted#on#the#y> axis. #(be#careful)# Histograms: the histogram can look different with different number of bins, consider creating two or three histograms to see whether the aggregation affects my perception of the data. Histogram with kernel density estimate histogram temp, kdensity. 101: this is a form of smoothing, you can versions that are smoother or less smooth depending on the size of the bandwidth. Cumulative distribution of weights lower quartilemedian upper quartile. 80: first prev next last go back full screen close quit n o i t r o p o r. Box plot: definition: upper and lower adjacent values are a multiple of the difference between the quartiles and the median, adjacent values are implemented differently in different software packages.
