Control estadistico
Enviado por DAYANA GIANINA ARQUE PACCORI • 18 de Febrero de 2022 • Apuntes • 2.761 Palabras (12 Páginas) • 148 Visitas
ESTADÍSTICA COMPUTACIONAL
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TRABAJO FINAL
REALIZADO POR:
ALEX SANDRO CAYLLAHUA CHIRE
DAYANA GIANINA ARQUE PACCORI
DOCENTE:
DRA. Yheni Farfan Machaca
2022
SALIDAS DE LA CONSOLA
> #analisis de la data
> library(Ecdat)
> library(Ecfun)
> library(datasets)
> library(base)
> library(knitr)
> library(nycflights13)
> library(dplyr)
> library(base)
> library(stats)
> library(ggplot2)
> library(dplyr)
> library(janitor)
> library(qcc)
> library(forecast)
> library(tseries)
> library(ggfortify)
> TranspEq
state va capital labor nfirm
1 Alabama 126.148 3.804 31.551 68
2 California 3201.486 185.446 452.844 1372
3 Connecticut 690.670 39.712 124.074 154
4 Florida 56.296 6.547 19.181 292
5 Georgia 304.531 11.530 45.534 71
6 Illinois 723.028 58.987 88.391 275
7 Indiana 992.169 112.884 148.530 260
8 Iowa 35.796 2.698 8.017 75
9 Kansas 494.515 10.360 86.189 76
10 Kentucky 124.948 5.213 12.000 31
11 Louisiana 73.328 3.763 15.900 115
12 Maine 29.467 1.967 6.470 81
13 Maryland 415.262 17.546 69.342 129
14 Massachusetts 241.530 15.347 39.416 172
15 Michigan 4079.554 435.105 490.384 568
16 Missouri 652.085 32.840 84.831 125
17 NewJersey 667.113 33.292 83.033 247
18 NewYork 940.430 72.974 190.094 461
19 Ohio 1611.899 157.978 259.916 363
20 Pennsylvania 617.579 34.324 98.152 233
21 Texas 527.413 22.736 109.728 308
22 Virginia 174.394 7.173 31.301 85
23 Washington 636.948 30.807 87.963 179
24 WestVirginia 22.700 1.543 4.063 15
25 Wisconsin 349.711 22.001 52.818 142
> #para ver ayuda y descripción de la data
> ?TranspEq
> # Datos estatales sobre la fabricación de equipos de transporte
> # número de observaciones : 25
> # observación : regional
> # país : Estados Unidos
> # Uso: data(TranspEq)
> # Una base de datos que contiene :
> # state = nombre del estado
> # va = salida
> # capital = entrada de capital
> # labor = insumo de mano de obra
> # nfirm = número de empresas
>
> #estructura de la data
> str(TranspEq)
'data.frame': 25 obs. of 5 variables:
$ state : Factor w/ 25 levels "Alabama","California",..: 1 2 3 4 5 6 7 8 9 10 ...
$ va : num 126.1 3201.5 690.7 56.3 304.5 ...
$ capital: num 3.8 185.45 39.71 6.55 11.53 ...
$ labor : num 31.6 452.8 124.1 19.2 45.5 ...
$ nfirm : int 68 1372 154 292 71 275 260 75 76 31 ...
>
> View(TranspEq)
>
> ##################SEMANA 1#
> TranspEq$state
[1] Alabama California Connecticut Florida Georgia Illinois Indiana
[8] Iowa Kansas Kentucky Louisiana Maine Maryland Massachusetts
[15] Michigan Missouri NewJersey NewYork Ohio Pennsylvania Texas
[22] Virginia Washington WestVirginia Wisconsin
25 Levels: Alabama California Connecticut Florida Georgia Illinois Indiana Iowa Kansas ... Wisconsin
> TranspEq$va
[1] 126.148 3201.486 690.670 56.296 304.531 723.028 992.169 35.796 494.515 124.948 73.328
[12] 29.467 415.262 241.530 4079.554 652.085 667.113 940.430 1611.899 617.579 527.413 174.394
[23] 636.948 22.700 349.711
> TranspEq$capital
[1] 3.804 185.446 39.712 6.547 11.530 58.987 112.884 2.698 10.360 5.213 3.763 1.967
[13] 17.546 15.347 435.105 32.840 33.292 72.974 157.978 34.324 22.736 7.173 30.807 1.543
[25] 22.001
> TranspEq$labor
[1] 31.551 452.844 124.074 19.181 45.534 88.391 148.530 8.017 86.189 12.000 15.900 6.470
[13] 69.342 39.416 490.384 84.831 83.033 190.094 259.916 98.152 109.728 31.301 87.963 4.063
[25] 52.818
> TranspEq$nfirm
[1] 68 1372 154 292 71 275 260 75 76 31 115 81 129 172 568 125 247 461 363 233
[21] 308 85 179 15 142
>
> estado <- TranspEq$state
> salida <- TranspEq$va
> entrada <- TranspEq$capital
> insumo <- TranspEq$labor
> empresa <- TranspEq$nfirm
>
> estado
[1] Alabama California Connecticut Florida Georgia Illinois Indiana
[8] Iowa Kansas Kentucky Louisiana Maine Maryland Massachusetts
[15] Michigan Missouri NewJersey NewYork Ohio Pennsylvania Texas
[22] Virginia Washington WestVirginia Wisconsin
25 Levels: Alabama California Connecticut Florida Georgia Illinois Indiana Iowa Kansas ... Wisconsin
> salida
[1] 126.148 3201.486 690.670 56.296 304.531 723.028 992.169 35.796 494.515 124.948 73.328
[12] 29.467 415.262 241.530 4079.554 652.085 667.113 940.430 1611.899 617.579 527.413 174.394
...