library(foreign)
library(ggplot2)
library(MASS)
library(openxlsx)## Warning: package 'openxlsx' was built under R version 4.3.1library(readr)
DB_Obesity <- read_csv("ObesityDataSet.csv")## Rows: 2111 Columns: 2
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## dbl (2): family_history_with_overweight, Weight
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.View(DB_Obesity)
DB_O <- DB_Obesity
head(DB_O)## # A tibble: 6 × 2
## family_history_with_overweight Weight
## <dbl> <dbl>
## 1 1 64
## 2 1 56
## 3 1 77
## 4 0 87
## 5 0 89.8
## 6 0 53DB_O$family_history_with_overweight<-factor(DB_O$family_history_with_overweight, levels = c(0,1))
dis=lda(family_history_with_overweight~DB_O$Weight, data= DB_O)
dis## Call:
## lda(family_history_with_overweight ~ DB_O$Weight, data = DB_O)
##
## Prior probabilities of groups:
## 0 1
## 0.182378 0.817622
##
## Group means:
## DB_O$Weight
## 0 59.04114
## 1 92.73020
##
## Coefficients of linear discriminants:
## LD1
## DB_O$Weight 0.04398411#Nueva observación Supongamos que entra un registro nuevo. Y que: weight: 65 family_history_with_overweight: 1
Creamos el perfil:
nuevo.registro=rbind(c(1,65))
colnames(nuevo.registro)=colnames(DB_O)
nuevo.registro=data.frame(DB_O)predict(dis,newdata =nuevo.registro)## $class
## [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 0 1 1 1 1 1 1 1 1 0
## [38] 0 1 1 1 1 1 1 1 1 1 1 1 0 1 0 0 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 0 1 1
## [75] 1 0 0 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 0 1 1 0 0 1 1 1 1 1 1 1 1 1 1 1 1
## [112] 1 0 0 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1
## [149] 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 0 1 0 1 1
## [186] 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 0 1 1 1
## [223] 1 1 1 1 0 1 1 1 1 1 0 1 0 1 1 1 1 1 1 1 1 1 0 0 1 0 1 1 1 1 1 0 1 1 1 1 1
## [260] 1 1 1 1 1 1 0 0 1 1 1 1 0 1 1 1 0 0 1 1 0 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1
## [297] 1 1 1 1 1 1 0 0 1 1 1 0 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 0 1 1
## [334] 1 1 0 1 1 1 0 1 0 1 1 1 1 0 1 1 1 1 1 1 0 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1
## [371] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 0 0 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1
## [408] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1
## [445] 1 0 1 1 1 1 1 1 1 0 1 1 1 0 1 1 1 1 1 1 1 0 1 1 0 0 0 1 1 0 1 1 1 1 1 0 0
## [482] 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0
## [519] 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
## [556] 0 0 0 1 1 1 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 1
## [593] 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 1 0 1
## [630] 1 0 0 0 1 0 0 0 1 1 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## [667] 0 1 1 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 1 1 1
## [704] 1 1 1 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0
## [741] 0 0 0 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [778] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [815] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [852] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [889] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [926] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [963] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [1000] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [1037] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [1074] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [1111] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [1148] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [1185] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [1222] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [1259] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [1296] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [1333] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [1370] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [1407] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [1444] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [1481] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [1518] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [1555] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [1592] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [1629] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [1666] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [1703] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [1740] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [1777] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [1814] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [1851] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [1888] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [1925] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [1962] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [1999] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [2036] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [2073] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [2110] 1 1
## Levels: 0 1
##
## $posterior
## 0 1
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## 1867 0.0057723938 0.9942276
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## 1869 0.0221619387 0.9778381
## 1870 0.0217465167 0.9782535
## 1871 0.0236046741 0.9763953
## 1872 0.0056690359 0.9943310
## 1873 0.0053967842 0.9946032
## 1874 0.0177101969 0.9822898
## 1875 0.0191274075 0.9808726
## 1876 0.0072902383 0.9927098
## 1877 0.0067882622 0.9932117
## 1878 0.0025749069 0.9974251
## 1879 0.0018614967 0.9981385
## 1880 0.0055118999 0.9944881
## 1881 0.0050444949 0.9949555
## 1882 0.0197494552 0.9802505
## 1883 0.0196198506 0.9803801
## 1884 0.0209799658 0.9790200
## 1885 0.0209277767 0.9790722
## 1886 0.0213723493 0.9786277
## 1887 0.0208672731 0.9791327
## 1888 0.0322979058 0.9677021
## 1889 0.0322894185 0.9677106
## 1890 0.0287455456 0.9712545
## 1891 0.0263214129 0.9736786
## 1892 0.0052037364 0.9947963
## 1893 0.0059980582 0.9940019
## 1894 0.0053842828 0.9946157
## 1895 0.0051974260 0.9948026
## 1896 0.0390783034 0.9609217
## 1897 0.0387503972 0.9612496
## 1898 0.0013161597 0.9986838
## 1899 0.0008723703 0.9991276
## 1900 0.0207547344 0.9792453
## 1901 0.0208117507 0.9791882
## 1902 0.0332053478 0.9667947
## 1903 0.0326770755 0.9673229
## 1904 0.0075881246 0.9924119
## 1905 0.0087612282 0.9912388
## 1906 0.0223790945 0.9776209
## 1907 0.0223978144 0.9776022
## 1908 0.0042696823 0.9957303
## 1909 0.0039150332 0.9960850
## 1910 0.0015211138 0.9984789
## 1911 0.0008893450 0.9991107
## 1912 0.0051741562 0.9948258
## 1913 0.0050783155 0.9949217
## 1914 0.0213054780 0.9786945
## 1915 0.0213293401 0.9786707
## 1916 0.0326783096 0.9673217
## 1917 0.0325254754 0.9674745
## 1918 0.0050633229 0.9949367
## 1919 0.0050471803 0.9949528
## 1920 0.0388736249 0.9611264
## 1921 0.0386526629 0.9613473
## 1922 0.0323899347 0.9676101
## 1923 0.0323872998 0.9676127
## 1924 0.0038690698 0.9961309
## 1925 0.0039136010 0.9960864
## 1926 0.0016210074 0.9983790
## 1927 0.0015040915 0.9984959
## 1928 0.0208335958 0.9791664
## 1929 0.0208608901 0.9791391
## 1930 0.0321146684 0.9678853
## 1931 0.0314994768 0.9685005
## 1932 0.0328271234 0.9671729
## 1933 0.0324308819 0.9675691
## 1934 0.0236782574 0.9763217
## 1935 0.0237102519 0.9762897
## 1936 0.0111809575 0.9888190
## 1937 0.0118415248 0.9881585
## 1938 0.0051137201 0.9948863
## 1939 0.0050641760 0.9949358
## 1940 0.0236008486 0.9763992
## 1941 0.0229809168 0.9770191
## 1942 0.0224363007 0.9775637
## 1943 0.0234626902 0.9765373
## 1944 0.0057589972 0.9942410
## 1945 0.0057683466 0.9942317
## 1946 0.0177217814 0.9822782
## 1947 0.0183748111 0.9816252
## 1948 0.0073600179 0.9926400
## 1949 0.0070570321 0.9929430
## 1950 0.0015170714 0.9984829
## 1951 0.0015387962 0.9984612
## 1952 0.0052666739 0.9947333
## 1953 0.0050476182 0.9949524
## 1954 0.0190110256 0.9809890
## 1955 0.0189159980 0.9810840
## 1956 0.0208504477 0.9791496
## 1957 0.0208422648 0.9791577
## 1958 0.0209444733 0.9790555
## 1959 0.0208940986 0.9791059
## 1960 0.0327931939 0.9672068
## 1961 0.0327921893 0.9672078
## 1962 0.0284985127 0.9715015
## 1963 0.0290848281 0.9709152
## 1964 0.0058094160 0.9941906
## 1965 0.0060891127 0.9939109
## 1966 0.0054311007 0.9945689
## 1967 0.0053059962 0.9946940
## 1968 0.0385112552 0.9614887
## 1969 0.0384044399 0.9615956
## 1970 0.0369935615 0.9630064
## 1971 0.0383370993 0.9616629
## 1972 0.0030065326 0.9969935
## 1973 0.0033414732 0.9966585
## 1974 0.0015233751 0.9984766
## 1975 0.0016357096 0.9983643
## 1976 0.0208199046 0.9791801
## 1977 0.0208197173 0.9791803
## 1978 0.0218175385 0.9781825
## 1979 0.0220683467 0.9779317
## 1980 0.0328571431 0.9671429
## 1981 0.0332020903 0.9667979
## 1982 0.0329711115 0.9670289
## 1983 0.0328391811 0.9671608
## 1984 0.0081749955 0.9918250
## 1985 0.0089332003 0.9910668
## 1986 0.0061112159 0.9938888
## 1987 0.0061569933 0.9938430
## 1988 0.0221133466 0.9778867
## 1989 0.0226322006 0.9773678
## 1990 0.0223772451 0.9776228
## 1991 0.0223995555 0.9776004
## 1992 0.0047595334 0.9952405
## 1993 0.0046064336 0.9953936
## 1994 0.0050665370 0.9949335
## 1995 0.0051380846 0.9948619
## 1996 0.0039322499 0.9960678
## 1997 0.0045039755 0.9954960
## 1998 0.0013737966 0.9986262
## 1999 0.0012637541 0.9987362
## 2000 0.0051440421 0.9948560
## 2001 0.0050584059 0.9949416
## 2002 0.0051527230 0.9948473
## 2003 0.0050584528 0.9949415
## 2004 0.0209080790 0.9790919
## 2005 0.0208455265 0.9791545
## 2006 0.0209786713 0.9790213
## 2007 0.0209642434 0.9790358
## 2008 0.0327529590 0.9672470
## 2009 0.0326046839 0.9673953
## 2010 0.0324930643 0.9675069
## 2011 0.0323346066 0.9676654
## 2012 0.0052085542 0.9947914
## 2013 0.0051997406 0.9948003
## 2014 0.0051100332 0.9948900
## 2015 0.0051333959 0.9948666
## 2016 0.0381994580 0.9618005
## 2017 0.0383018653 0.9616981
## 2018 0.0374317129 0.9625683
## 2019 0.0377410703 0.9622589
## 2020 0.0324737301 0.9675263
## 2021 0.0326603699 0.9673396
## 2022 0.0317282581 0.9682717
## 2023 0.0323641849 0.9676358
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## 2033 0.0208257304 0.9791743
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##
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## 1761 1.4789063070
## 1762 1.3934002816
## 1763 1.3980158857
## 1764 1.6930276199
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## 1766 1.6875259559
## 1767 1.7519905130
## 1768 1.1648578559
## 1769 1.1545448147
## 1770 1.2087658253
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## 1773 1.3750879829
## 1774 1.3963593563
## 1775 1.3983225868
## 1776 1.3993843192
## 1777 1.4345595082
## 1778 1.3725772382
## 1779 1.3876475124
## 1780 0.6356673089
## 1781 0.7299100732
## 1782 0.7340959966
## 1783 0.7124899922
## 1784 1.5155014789
## 1785 1.5245760597
## 1786 1.4292963261
## 1787 1.4008985160
## 1788 1.5273128388
## 1789 1.5343863627
## 1790 1.5037893472
## 1791 1.4845342053
## 1792 0.6007896283
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## 1794 0.6401982876
## 1795 0.7036505504
## 1796 0.8354531460
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## 1798 0.7800759252
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## 1800 0.6820687812
## 1801 0.8123661528
## 1802 2.2552269188
## 1803 2.7863838633
## 1804 1.1148630141
## 1805 0.8296372597
## 1806 0.8079341823
## 1807 1.0254636476
## 1808 1.5226907250
## 1809 2.0751116975
## 1810 1.0280693540
## 1811 1.0538292614
## 1812 1.9767868563
## 1813 1.2262490236
## 1814 1.8172818832
## 1815 2.8813241715
## 1816 2.0766686908
## 1817 1.2282772186
## 1818 1.1154631773
## 1819 1.1120110407
## 1820 0.7993079755
## 1821 0.9191184366
## 1822 1.9503027506
## 1823 2.0206717340
## 1824 0.6781170292
## 1825 0.7231338819
## 1826 2.4418396482
## 1827 2.9088662709
## 1828 1.1175039958
## 1829 1.0830164543
## 1830 0.7917018041
## 1831 0.7991428152
## 1832 1.6766179417
## 1833 1.8993692880
## 1834 1.0595896398
## 1835 1.0661149018
## 1836 2.1525293098
## 1837 2.0667132404
## 1838 2.2935318849
## 1839 3.0474842917
## 1840 2.0707509813
## 1841 2.0789691915
## 1842 1.1128221956
## 1843 1.1098195766
## 1844 0.8014996595
## 1845 0.8067821946
## 1846 2.0575340654
## 1847 2.0833782903
## 1848 0.6950100927
## 1849 0.7123627461
## 1850 0.8054936802
## 1851 0.8094336445
## 1852 2.2193896370
## 1853 2.2511825803
## 1854 2.4006615964
## 1855 2.8761121430
## 1856 1.1152823586
## 1857 1.1002401903
## 1858 0.8115685450
## 1859 0.8285494448
## 1860 0.8028423183
## 1861 0.8020553107
## 1862 1.0704021206
## 1863 1.0394008033
## 1864 1.6810641630
## 1865 1.5516830683
## 1866 2.0759572919
## 1867 1.9916300405
## 1868 1.0302211444
## 1869 1.0725269488
## 1870 1.0855838505
## 1871 1.0289679933
## 1872 2.0038934690
## 1873 2.0372921400
## 1874 1.2269207048
## 1875 1.1739942784
## 1876 1.8330527362
## 1877 1.8815394510
## 1878 2.5385955764
## 1879 2.7580254629
## 1880 2.0229702994
## 1881 2.0830882151
## 1882 1.1519680938
## 1883 1.1565006559
## 1884 1.1103303201
## 1885 1.1120471517
## 1886 1.0975545647
## 1887 1.1140427546
## 1888 0.8113242133
## 1889 0.8115074951
## 1890 0.8924317402
## 1891 0.9535694274
## 1892 2.0620058854
## 1893 1.9655965960
## 1894 2.0388657154
## 1895 2.0628290480
## 1896 0.6779738170
## 1897 0.6838907348
## 1898 2.9923437494
## 1899 3.2701871675
## 1900 1.1177697478
## 1901 1.1158790470
## 1902 0.7919916154
## 1903 0.8031831512
## 1904 1.8058231439
## 1905 1.7080123450
## 1906 1.0657965449
## 1907 1.0652193414
## 1908 2.1961523501
## 1909 2.2549137960
## 1910 2.8945359853
## 1911 3.2571702473
## 1912 2.0658730999
## 1913 2.0785557849
## 1914 1.0997155479
## 1915 1.0989436708
## 1916 0.8031568047
## 1917 0.8064271109
## 1918 2.0805612842
## 1919 2.0827272375
## 1920 0.6816615324
## 1921 0.6856636022
## 1922 0.8093398264
## 1923 0.8093965659
## 1924 2.2629148567
## 1925 2.2551616904
## 1926 2.8515438530
## 1927 2.9021422447
## 1928 1.1151559923
## 1929 1.1142536144
## 1930 0.8152916236
## 1931 0.8287735878
## 1932 0.7999866942
## 1933 0.8084586488
## 1934 1.0268166427
## 1935 1.0258832560
## 1936 1.5417801348
## 1937 1.5025918360
## 1938 2.0738431519
## 1939 2.0804470135
## 1940 1.0290800208
## 1941 1.0474721946
## 1942 1.0640341457
## 1943 1.0331377305
## 1944 1.9932071786
## 1945 1.9921061245
## 1946 1.2264714512
## 1947 1.2016018701
## 1948 1.8265764725
## 1949 1.8551521543
## 1950 2.8963345394
## 1951 2.8867242322
## 1952 2.0538499127
## 1953 2.0826683868
## 1954 1.1781931331
## 1955 1.1816402994
## 1956 1.1145987137
## 1957 1.1148692599
## 1958 1.1114974383
## 1959 1.1131572665
## 1960 0.8007082535
## 1961 0.8007296298
## 1962 0.8984280494
## 1963 0.8842772189
## 1964 1.9872903927
## 1965 1.9553669046
## 1966 2.0329911982
## 1967 2.0488032643
## 1968 0.6882363205
## 1969 0.6901856961
## 1970 0.7164347067
## 1971 0.6914173390
## 1972 2.4337172793
## 1973 2.3622086238
## 1974 2.8935319161
## 1975 2.8454406185
## 1976 1.1156090725
## 1977 1.1156152743
## 1978 1.0833344154
## 1979 1.0754475814
## 1980 0.7993488807
## 1981 0.7920600986
## 1982 0.7969325699
## 1983 0.7997304428
## 1984 1.7551495834
## 1985 1.6947768677
## 1986 1.9529066097
## 1987 1.9478391568
## 1988 1.0740418053
## 1989 1.0580319867
## 1990 1.0658535922
## 1991 1.0651656808
## 1992 2.1225233088
## 1993 2.1446922218
## 1994 2.0801308557
## 1995 2.0706188530
## 1996 2.2519408663
## 1997 2.1599416872
## 1998 2.9633801717
## 1999 3.0197997718
## 2000 2.0698327691
## 2001 2.0812202981
## 2002 2.0686889624
## 2003 2.0812140083
## 2004 1.1126962251
## 2005 1.1147614109
## 2006 1.1103728527
## 2007 1.1108470893
## 2008 0.8015648440
## 2009 0.8047303801
## 2010 0.8071225436
## 2011 0.8105321915
## 2012 2.0613781003
## 2013 2.0625270091
## 2014 2.0743323871
## 2015 2.0712381492
## 2016 0.6939412350
## 2017 0.6920625858
## 2018 0.7081814851
## 2019 0.7024100227
## 2020 0.8075377096
## 2021 0.8035399063
## 2022 0.8237303262
## 2023 0.8098945099
## 2024 2.2703192730
## 2025 2.2676931140
## 2026 2.2540251411
## 2027 2.2522911117
## 2028 2.4285107488
## 2029 2.4613120716
## 2030 2.9277330772
## 2031 2.8980079147
## 2032 1.1154484866
## 2033 1.1154162462
## 2034 1.1055044280
## 2035 1.1038530447
## 2036 0.8076205317
## 2037 0.8115271560
## 2038 0.8278360666
## 2039 0.8257413235
## 2040 0.8026786095
## 2041 0.8028140366
## 2042 0.8014443275
## 2043 0.7998996057
## 2044 1.0707689040
## 2045 1.0571872279
## 2046 1.0344987747
## 2047 1.0330969572
## 2048 1.7963724550
## 2049 1.7374708318
## 2050 1.5528036514
## 2051 1.5934110974
## 2052 2.0797639403
## 2053 2.0528690671
## 2054 1.9784676649
## 2055 1.9944000715
## 2056 1.0296979975
## 2057 1.0288913290
## 2058 1.0807665793
## 2059 1.0702911047
## 2060 1.0859494464
## 2061 1.0971901124
## 2062 1.0291491198
## 2063 1.0372379288
## 2064 2.0026153788
## 2065 1.9999016475
## 2066 2.0090400052
## 2067 2.0462088618
## 2068 1.2268662965
## 2069 1.2269950380
## 2070 1.1958460220
## 2071 1.1610260486
## 2072 1.8525974695
## 2073 1.7686939170
## 2074 1.8280696009
## 2075 1.8860596975
## 2076 2.6702806905
## 2077 2.4619268815
## 2078 2.8119224426
## 2079 2.8058126105
## 2080 2.0757797721
## 2081 2.0422280803
## 2082 2.0786451166
## 2083 2.0834845559
## 2084 1.1651886164
## 2085 1.1422407449
## 2086 1.1287922966
## 2087 1.1221470460
## 2088 1.1099722895
## 2089 1.1117918679
## 2090 1.1124492544
## 2091 1.1151697153
## 2092 1.0982791149
## 2093 1.0895304563
## 2094 1.1144003453
## 2095 1.1127308846
## 2096 0.8077556948
## 2097 0.8046251701
## 2098 0.8115571091
## 2099 0.8079102990
## 2100 0.9458319194
## 2101 0.9145458490
## 2102 0.9075192561
## 2103 0.9465952196
## 2104 2.0429502114
## 2105 2.0434084378
## 2106 1.9682767675
## 2107 1.9714762593
## 2108 2.0741534158
## 2109 2.0717962635
## 2110 2.0567224266
## 2111 2.0622644240Analisis Realizamos el siguiente análisis LDA tomando en cuanta 2 variables, si cuenta con sobrepeso la persona a analizar y el peso de la persona, con el objetivo de encontrar si el peso de la persona resulta en sobrepeso o no. Para realizar esto utilizamos el método LDA el cual calcula la probabilidad de que una variable esté presente en la otra, por lo tanto buscando en este caso, cuanto es peso de una persona dependiendo de si tienen sobre peso o no.