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12.1 Expand your knowledge outliers some data sets include values so high or so

ID: 3202786 • Letter: 1

Question

12.1 Expand your knowledge outliers some data sets include values so high or so low that they seem vo stand apart from the rest of the data These data are ealed outliers outliers may represent data collection errors. data entry errors. or sim- ply valid but unusual daa values. is important to identify outliers in the data set and examine the outliers carefully to determine if they are in error. One way to detect outliers is to use a box-and-whisker plot. Data values that fall beyond the limits. Lower limit: Qu 15 x (IOR) Upper limit: e, 1.5 x (IOR) where IOR is the ile range. are suspected outliers. in the computer soft- ware package Minitab. values beyond these limits are plotted with asterisks Pick one of the youth commitment rat data sets for the 50 US states plus the District of Columbia (White, Black, be All) to give a five figure summary box and whisker plot. Determine whether any of the observations would and a considered outliers based on the 1.5 rule described above. would it be good to pay attention outliers lOR Boot Mead he in this specific situation? White min mln ap meol 65 mar 1206 ma Y N13 mar 302 TBR 222 TOR 53 x

Explanation / Answer

Given,

All youth   white   black
20   7   0
34   10   77
36   12   83
41   14   108
41   14   116
44   14   156
52   16   159
54   26   160
66   31   169
68   33   171
72   34   173
73   39   180
78   42   193
79   42   206
84   43   227
87   45   240
90   47   241
95   50   241
99   53   243
99   54   249
105   57   250
106   58   261
107   62   276
108   63   277
108   64   296
109   65   297
119   66   308
120   71   324
122   72   336
126   72   337
127   72   342
128   78   351
131   80   365
133   80   381
134   84   396
134   89   413
135   87   451
136   91   463
142   95   475
145   96   524
146   98   548
168   98   595
170   105   631
178   112   649
186   120   682
186   149   688
231   154   697
245   155   727
264   167   739
302   200   818
302   213   1846

Data from MInitab

Descriptive Statistics: All youth, white, black

Variable Mean StDev Q1 Median Q3 IQR
All youth 120.88 64.18 78.00 109.00 142.00 64.00
white 72.53 47.35 42.00 65.00 95.00 53.00
black 375.2 289.1 193.0 297.0 475.0 282.0

lower limit = Q1 - 1.5* IQR

upper limit = Q3 + 1.5*IQR

for all youth ,

LL = -18

UL = 238

for white,

LL=-37.5

UL=174.5

for black

LL=-230

UL=616

This 1.5 rule is good for finding outliers above the range but not below

hence the formula can be modified for lower limit

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