Calidad del aire en Hermosillo sonora
Introducción
En este analisis miraremos de forma grafica el comportamiento de la calidad del aire en cuestion a una fechas establecidas, compararemos como era la contaminacion en enero del 2019, enero de 2020 y en la fecha actual octubre del 2020.
## -- Attaching packages ---------------------------------------------------------------------------- tidyverse 1.3.0 --## v ggplot2 3.3.2 v purrr 0.3.4
## v tibble 3.0.3 v dplyr 1.0.2
## v tidyr 1.1.1 v stringr 1.4.0
## v readr 1.3.1 v forcats 0.5.0## -- Conflicts ------------------------------------------------------------------------------- tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()library(ggplot2)
library(pacman)
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summarytools, ggpubr, kableExtra, reshape2,
sf, tmap, readr, devtools, plotly, gganimate, gifski, ggplotly)## Installing package into 'C:/Users/progr/OneDrive/Documentos/R/win-library/3.6'
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## Please use `install.packages('BiocManager')` and then retry.## Warning in p_install(package, character.only = TRUE, ...):## Warning in library(package, lib.loc = lib.loc, character.only = TRUE,
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## Please use `install.packages('BiocManager')` and then retry.## Warning in p_install(package, character.only = TRUE, ...):## Warning in library(package, lib.loc = lib.loc, character.only = TRUE,
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## hashmap, ggplotly1.- ¿Qué es la estadística y que aplicaciones tiene en ingeniería (según su ingeniería)? R= La estadística es una de las herramientas más importantes en el mundo de la ingeniería, esto se debe a que esta es una herramienta lo suficientemente capaz para modelar y predecir comportamientos de la forma más exacta a problemáticas del día a día como por ejemplo en el 2019 un grupo de programadores y matemáticos hicieron un modelo de cómo sería el impacto de un terremoto a través de la estadística y a que usaron modelos de inteligencia artificial la cual de permitía modelar de una forma muy exacta el comportamiento de las ondas en el momento de la dispersión, ahora no solo sirve para eso también sirve mucho en el campo de la banca y los negocios haciendo sistemas basados en formulas de la estadística para su funcionamiento.
2.- Enliste y define los tipos de variables usados en estadística, de 2 ejemplos de cada uno. Defina distribución de frecuencia y explique que es la distribución normal. 1. Cuantitativa y cualitativa 2. Discreta y continua
un ejemplo de la cuantitativa es a la hora de recolectar muchas temperaturas que te arroja una fecha en una ciudad determinada, otro ejemplo serio el número de libros que lee un mexicano
2 ejemplo de una variable cualitativa seria el sexo y la nacionalidad de una persona
2 ejemplos de las tipas de variables discretas seria el número de páginas de un libro 210 o 211 pero no puede ser 210.5, ahora un ejemplo de una variable continua seria el peso de un recién nacido.
Importamos datos
library(readr)
library(DT)
CalidadDelAireEnero2019 <- read_csv("~/Probabilidad y Estadistica/CalidadDelAireEnero2019.csv")## Parsed with column specification:
## cols(
## Time = col_datetime(format = ""),
## O3 = col_double(),
## O3_flag = col_character(),
## SO2 = col_double(),
## SO2_flag = col_character(),
## NO2 = col_character(),
## NO2_flag = col_character(),
## NO = col_character(),
## NO_flag = col_character(),
## CO = col_double(),
## CO_flag = col_character(),
## PM10 = col_double(),
## PM10_flag = col_character(),
## PM2.5 = col_double(),
## PM2.5_flag = col_character()
## )## Parsed with column specification:
## cols(
## Time = col_datetime(format = ""),
## O3 = col_double(),
## O3_flag = col_character(),
## SO2 = col_double(),
## SO2_flag = col_character(),
## NO2 = col_character(),
## NO2_flag = col_character(),
## NO = col_character(),
## NO_flag = col_character(),
## CO = col_character(),
## CO_flag = col_character(),
## PM10 = col_double(),
## PM10_flag = col_character(),
## PM2.5 = col_character(),
## PM2.5_flag = col_character()
## )## Parsed with column specification:
## cols(
## Time = col_datetime(format = ""),
## O3 = col_double(),
## O3_flag = col_character(),
## SO2 = col_double(),
## SO2_flag = col_character(),
## NO2 = col_character(),
## NO2_flag = col_character(),
## NO = col_character(),
## NO_flag = col_character(),
## CO = col_double(),
## CO_flag = col_character(),
## PM10 = col_double(),
## PM10_flag = col_character(),
## PM2.5 = col_character(),
## PM2.5_flag = col_character()
## )Transformamos los datos
# Datos de O3
o3Enero2019 <-CalidadDelAireEnero2019$O3
o3Enero2020 <-CalidadDelAireEnero2020$O3
o3Octubre2020 <-CalidadDelAireOctubre2020$O3
# Datos de mp10
mpEnero2019 <-CalidadDelAireEnero2019$PM10
mpEnero2020 <-CalidadDelAireEnero2020$PM10
mpOctubre2020 <-CalidadDelAireOctubre2020$PM10
# Visualizando los datos
# o3
o3Enero2019## [1] 12.68 12.86 17.58 20.26 19.56 22.37 16.69 21.55 32.49 39.83 43.85 45.64
## [13] 46.01 42.69 41.83 40.96 37.71 32.25 29.74 22.83 20.83 24.56 20.35 20.62
## [25] 25.34 28.66 29.54 27.71 22.67 19.58 23.47 21.90 27.19 36.26 39.18 40.88
## [37] 40.55 40.95 41.68 40.14 35.04 31.44 24.46 32.27 33.28 27.52 4.07 16.48
## [49] 19.34 22.17 27.75 30.36 26.34 23.06 12.29 20.80 33.10 37.69 37.03 42.88
## [61] 41.62 46.39 41.54 34.02 15.79 4.32 0.81 2.72 1.65 1.26 2.14 3.30
## [73] 16.03 13.06 17.62 18.43 16.51 5.43 0.71 3.62 15.31 33.05 35.90 37.88
## [85] 38.76 42.50 44.07 33.55 16.61 1.04 0.59 1.18 1.51 2.91 5.04 4.71
## [97] 4.50 6.03 8.08 12.89 14.92 14.17 7.75 5.17 9.96 14.37 26.38 27.98
## [109] 25.21 30.11 27.31 30.06 27.16 21.17 14.13 5.97 1.32 1.36 0.74 0.83
## [121] 0.97 2.20 0.12 5.46 14.71 13.11 11.54 9.83 14.02 13.50 10.64 15.62
## [133] 22.42 20.05 19.64 18.28 19.58 9.53 6.67 6.24 0.10 0.34 0.61 0.52
## [145] 0.33 2.36 7.14 6.37 7.95 4.39 0.91 2.99 17.55 20.97 26.06 30.66
## [157] 34.58 36.82 32.44 20.56 11.14 3.49 0.36 -0.06 0.46 0.19 5.26 7.19
## [169] 2.14 15.36 6.42 0.02 0.44 0.07 0.52 0.86 2.92 5.31 3.09 7.14
## [181] 13.36 19.85 20.14 15.88 4.92 0.21 0.05 0.14 3.33 1.37 -0.04 -0.05
## [193] -0.17 0.39 -0.16 0.60 0.67 -0.10 0.23 1.11 5.65 13.59 24.99 31.47
## [205] 36.48 41.82 46.94 39.12 27.51 13.03 4.22 1.34 5.66 11.04 1.39 3.70
## [217] 11.29 5.94 8.88 3.94 0.14 -0.17 -0.15 0.07 1.78 3.00 4.67 1.91
## [229] 5.89 9.05 8.71 15.07 14.96 16.71 16.44 10.32 7.62 -0.10 1.45 0.57
## [241] -0.10 -0.31 1.35 3.49 0.77 0.02 0.02 2.11 5.38 15.25 21.79 29.86
## [253] 34.43 41.73 39.92 34.59 26.22 8.65 1.22 1.06 0.12 0.15 0.26 6.90
## [265] 6.67 6.10 6.07 9.93 13.28 6.92 1.51 5.72 15.18 23.67 26.94 32.32
## [277] 33.13 34.88 35.31 34.58 26.35 12.92 5.82 3.86 5.81 0.55 0.28 0.03
## [289] 0.41 1.27 3.59 5.89 3.61 2.69 3.44 7.75 14.38 22.69 26.36 26.29
## [301] 32.22 32.45 30.33 30.07 25.67 11.53 3.81 0.10 0.38 4.43 14.68 19.25
## [313] 18.64 9.48 4.84 6.50 5.18 2.43 1.00 6.19 13.43 17.90 21.96 21.11
## [325] 23.08 26.33 20.55 14.80 1.34 1.05 1.34 1.04 -0.21 0.12 0.04 2.93
## [337] 1.18 3.80 5.23 6.94 2.25 0.13 0.12 2.75 15.89 22.07 23.29 26.99
## [349] 25.21 28.69 29.10 23.04 18.56 8.75 3.93 0.42 2.31 0.64 -0.03 -0.40
## [361] -0.23 -0.19 0.68 0.42 0.08 -0.36 -0.06 0.57 2.76 4.88 13.00 22.75
## [373] 32.40 33.53 28.34 23.87 12.10 2.53 0.42 -0.07 0.05 1.76 -0.01 -0.05
## [385] 0.17 0.28 -0.20 -0.09 3.60 1.84 0.26 1.20 6.80 10.60 20.66 26.00
## [397] 29.04 32.02 28.39 27.12 18.41 11.66 8.09 3.96 0.38 0.46 0.46 0.54
## [409] 6.84 14.27 18.09 18.97 20.15 1.73 0.99 7.64 11.42 18.72 24.99 32.24
## [421] 34.66 33.88 25.69 25.01 14.85 6.37 1.90 0.60 0.38 0.44 0.33 0.16
## [433] 0.15 0.63 0.15 1.94 14.59 8.31 1.62 16.50 34.40 38.02 39.39 42.78
## [445] 46.95 48.83 49.37 47.99 37.70 3.84 1.26 2.71 37.29 26.79 9.12 15.40
## [457] 19.41 12.91 7.81 10.74 15.95 16.19 14.05 16.11 27.50 33.17 40.56 42.93
## [469] 45.46 51.44 54.10 50.40 34.46 11.02 13.12 19.16 3.62 0.71 0.34 7.92
## [481] 15.09 14.31 9.15 10.00 9.84 7.96 1.56 6.30 13.18 21.25 30.90 36.51
## [493] 39.39 41.35 40.40 35.01 28.10 13.04 21.49 19.22 17.24 14.49 18.25 18.29
## [505] 17.46 17.63 19.47 17.94 18.77 4.70 1.00 4.12 6.74 22.78 42.21 42.56
## [517] 42.72 39.45 39.20 35.29 28.83 23.74 15.59 21.42 4.90 14.58 10.72 9.32
## [529] 3.55 7.44 2.83 11.43 26.32 5.83 9.67 16.38 30.06 34.47 36.41 41.64
## [541] 44.89 46.74 46.12 44.30 32.17 10.43 1.57 0.85 2.15 6.89 2.28 0.45
## [553] 1.05 10.81 8.40 2.43 8.57 3.51 0.76 5.16 10.46 18.64 26.90 32.58
## [565] 41.95 45.71 46.73 27.68 19.80 13.79 5.45 12.03 3.23 18.05 16.59 9.07
## [577] 4.50 1.00 7.50 14.42 12.95 4.03 3.28 7.38 13.58 29.87 38.42 40.74
## [589] 42.93 44.23 34.22 32.82 29.67 24.61 21.45 14.20 10.55 9.58 7.47 4.90
## [601] 4.40 3.73 16.56 10.80 2.33 3.16 0.67 6.33 13.60 25.02 30.81 37.69
## [613] 44.49 49.21 53.94 54.36 38.97 11.78 9.16 5.44 9.17 4.32 1.39 6.86
## [625] 15.51 21.57 26.47 29.79 27.46 27.08 25.94 24.03 22.90 30.94 43.27 49.46
## [637] 51.24 58.26 61.06 50.95 39.19 23.68 16.15 17.09 11.04 2.00 0.52 0.51
## [649] 9.26 22.75 19.01 13.84 17.18 12.71 3.91 8.23 17.83 22.40 35.59 38.09
## [661] 43.86 44.90 45.23 42.89 23.00 9.78 7.97 4.52 5.16 1.45 0.34 3.53
## [673] 3.19 3.87 8.32 9.87 12.04 6.52 1.24 3.08 8.55 15.85 29.46 31.07
## [685] 32.22 40.49 38.22 37.38 27.08 17.29 3.31 4.76 1.33 4.45 9.24 2.94
## [697] 4.78 19.09 20.49 3.39 5.70 2.40 1.03 3.56 16.26 31.00 35.02 41.40
## [709] 39.53 40.28 39.57 38.49 34.62 22.41 9.05 2.37 0.38 0.55 1.99 12.47
## [721] 11.66 10.01 13.37 19.85 16.11 18.45 3.40 10.09 34.73 38.65 39.19 43.69
## [733] 43.20 42.76 41.09 38.10 35.06 27.00 20.94 16.71 16.69 12.59 5.38 3.13## [1] 7.87 16.03 16.61 15.84 13.78 18.14 15.41 18.71 23.47 25.82 29.98 36.60
## [13] 41.31 41.97 39.05 37.55 32.83 18.80 22.65 17.69 15.29 10.69 7.96 12.72
## [25] 17.24 19.78 18.15 10.58 7.48 7.94 6.23 9.74 13.34 22.80 30.89 36.24
## [37] 38.07 37.94 36.42 36.33 31.02 22.35 18.26 16.55 6.91 1.00 11.10 14.98
## [49] 20.57 14.26 18.25 25.83 22.78 12.00 6.81 7.54 13.82 21.36 31.12 34.99
## [61] 40.23 41.01 41.60 38.30 19.92 2.11 1.50 2.05 1.66 0.59 3.20 3.27
## [73] 9.56 13.69 16.01 16.45 18.05 17.28 7.72 8.37 12.30 18.54 24.58 31.56
## [85] 37.20 41.28 43.48 47.69 22.42 1.05 1.88 2.56 1.74 6.39 9.05 12.59
## [97] 15.41 15.28 4.88 10.53 10.57 9.58 7.74 12.56 20.13 21.14 28.43 34.02
## [109] 41.31 43.67 43.11 41.08 28.51 2.74 2.34 0.55 1.10 0.72 1.08 4.46
## [121] 8.80 9.38 9.22 10.77 0.47 3.12 4.04 2.13 6.47 14.13 18.67 28.06
## [133] 37.44 42.57 34.13 28.37 12.21 4.43 4.74 1.01 0.62 0.72 0.68 2.01
## [145] 10.70 11.43 14.14 12.89 11.98 7.47 2.91 6.49 10.84 15.34 22.41 30.87
## [157] 40.23 39.41 38.43 42.15 16.36 1.33 0.53 1.02 2.39 4.16 0.67 5.79
## [169] 8.70 8.39 8.71 10.66 10.25 4.85 2.55 4.77 10.03 22.01 21.99 24.68
## [181] 26.36 24.19 29.80 26.49 12.18 0.91 1.35 1.36 0.86 0.58 0.41 0.76
## [193] 2.01 5.44 6.01 10.26 11.46 7.49 3.64 8.36 13.87 24.94 26.79 34.46
## [205] 37.50 38.08 37.01 36.85 29.12 25.24 23.74 18.02 17.16 10.52 13.69 17.21
## [217] 25.10 25.43 21.89 20.83 18.67 11.08 1.50 4.70 19.22 29.31 34.45 36.15
## [229] 35.25 35.52 36.76 34.09 22.74 16.77 2.13 1.59 1.76 1.39 7.56 10.07
## [241] 17.40 24.85 14.52 13.29 13.13 10.99 10.62 14.39 25.94 30.11 33.59 39.06
## [253] 39.80 48.49 43.65 41.85 28.78 6.00 0.99 1.41 3.22 1.94 0.10 0.52
## [265] 1.53 9.13 13.52 17.37 16.55 19.67 16.28 23.81 28.14 27.02 33.84 38.14
## [277] 47.92 46.40 41.67 35.63 21.64 5.37 1.23 1.54 1.35 1.56 0.94 2.25
## [289] 9.38 10.96 12.42 10.12 13.40 9.20 1.79 4.39 10.74 18.99 29.59 30.93
## [301] 35.23 41.49 38.88 35.34 15.48 1.01 1.96 2.44 0.52 3.43 9.01 17.92
## [313] 18.50 12.80 15.10 18.63 21.11 11.93 5.14 9.56 14.59 19.97 21.98 26.32
## [325] 33.12 38.51 37.12 29.66 9.16 3.72 14.27 8.46 0.89 0.87 0.79 1.10
## [337] 6.82 7.85 7.29 6.50 5.88 2.47 2.97 4.48 10.06 11.77 15.64 21.71
## [349] 21.83 18.85 16.59 16.64 6.10 1.03 1.54 1.82 0.28 0.74 4.41 4.81
## [361] 0.55 0.31 5.09 12.35 11.62 2.56 0.43 0.72 0.86 3.12 4.84 2.79
## [373] 3.40 3.24 7.85 4.18 0.30 0.38 2.06 2.63 2.72 2.54 0.11 0.09
## [385] 2.14 2.46 3.67 4.53 3.18 1.06 0.63 4.35 10.45 20.71 21.15 26.68
## [397] 33.05 29.85 29.66 24.75 11.80 5.48 5.69 4.37 5.90 7.65 12.67 5.17
## [409] 3.41 1.04 0.46 3.71 11.21 1.60 0.69 2.15 9.96 13.73 20.57 27.64
## [421] 33.90 35.00 31.89 28.32 21.59 15.99 8.63 13.53 5.58 7.50 12.06 17.96
## [433] 5.87 10.54 10.94 0.81 0.78 0.33 8.45 15.04 17.73 19.83 30.04 37.40
## [445] 44.58 47.23 38.45 37.45 27.40 6.64 19.39 4.91 1.34 1.81 8.73 10.59
## [457] 10.79 11.11 12.63 10.58 7.07 1.70 1.38 2.59 7.52 13.01 22.14 30.84
## [469] 35.19 36.59 38.95 32.95 26.27 8.86 4.20 1.48 15.91 9.86 10.41 5.86
## [481] 6.81 4.02 1.03 1.09 2.85 2.34 0.21 6.66 15.19 15.15 21.14 25.05
## [493] 25.93 23.07 22.89 20.52 15.38 8.87 9.77 15.69 18.21 18.96 17.98 13.20
## [505] 3.42 16.14 8.53 3.39 1.00 0.00 0.12 0.83 4.67 13.59 20.72 29.43
## [517] 31.23 29.84 28.39 27.71 25.78 8.30 16.51 8.95 7.33 10.00 6.87 14.94
## [529] 15.82 13.32 2.18 0.05 0.04 0.18 0.22 3.56 7.49 15.32 21.71 29.55
## [541] 37.17 40.07 39.01 37.75 22.02 5.79 8.07 7.50 13.09 9.53 5.09 4.29
## [553] 13.00 10.23 6.21 8.69 5.28 2.32 1.48 4.37 9.33 19.79 25.85 25.76
## [565] 29.95 31.14 34.14 33.54 25.52 6.87 3.86 5.48 4.13 0.36 0.62 0.23
## [577] 1.92 4.52 3.54 0.95 4.45 5.41 2.83 7.45 14.51 20.03 29.85 37.09
## [589] 37.98 37.87 39.28 37.93 33.93 20.75 4.67 3.15 6.45 8.87 2.62 0.44
## [601] 9.00 15.14 12.00 11.81 10.64 9.20 8.61 16.11 21.61 29.53 36.25 43.15
## [613] 47.64 46.20 46.15 44.21 37.95 24.98 27.99 22.60 7.82 3.61 1.94 2.89
## [625] 5.12 4.81 3.07 5.67 3.80 3.16 2.50 6.28 7.95 17.89 32.35 36.81
## [637] 36.18 36.02 35.57 32.32 25.83 16.42 17.34 10.78 6.36 3.37 9.63 21.19
## [649] 18.10 19.50 25.47 22.42 18.02 10.65 1.87 8.68 14.86 28.01 28.36 42.92
## [661] 45.04 45.23 41.77 38.24 29.00 6.97 7.83 1.90 0.58 0.74 1.09 10.82
## [673] 17.08 18.92 19.49 12.60 6.89 3.64 3.72 7.74 16.00 18.32 27.57 35.39
## [685] 36.98 39.85 38.82 39.40 33.76 21.12 20.29 18.29 24.15 30.03 26.66 26.92
## [697] 33.74 32.23 26.92 22.65 29.33 6.06 1.36 6.12 23.77 33.16 35.23 38.64
## [709] 42.43 48.58 45.33 40.36 31.68 28.29 20.77 11.06 10.80 7.93 6.96 2.35
## [721] 3.18 3.34 10.87 8.95 12.39 11.23 9.01 7.09 15.76 29.92 36.22 41.64
## [733] 45.48 47.00 46.02 43.56 33.70 2.74 0.94 2.01 1.95 0.49 2.16 1.63## [1] 17.42 21.01 24.53 19.04 19.26 14.05 14.85 14.33 16.49 18.82 23.97 32.80
## [13] 37.03 31.26 27.53 25.94 27.12 20.63 18.98 19.87 20.20 19.30 18.29 15.81
## [25] 13.35 14.51 17.49 18.04 8.23 7.81 11.55 15.35 14.57 18.40 20.81 25.51
## [37] 31.40 31.18 24.80 22.37 21.66 18.42 14.75 12.61 9.40 10.72 12.97 12.36
## [49] 14.20 17.11 16.52 12.17 3.24 2.99 6.62 10.94 12.46 18.24 23.73 30.44
## [61] 35.72 34.36 31.75 27.52 29.53 19.68 15.78 11.67 10.59 8.99 1.20 2.55
## [73] 6.96 8.51 8.12 5.72 9.04 8.49 7.92 13.18 19.42 25.90 27.36 31.49
## [85] 38.20 46.63 53.99 49.76 35.33 21.91 17.87 16.08 14.89 9.09 5.05 3.20
## [97] 7.60 5.95 5.82 11.96 10.67 9.56 7.27 14.30 21.65 23.69 29.27 33.82
## [109] 37.37 36.07 36.61 31.80 31.64 22.61 20.31 19.37 15.39 16.19 7.70 3.88
## [121] 6.29 9.66 11.74 10.42 7.41 5.85 7.60 12.43 18.84 23.54 29.59 36.24
## [133] 38.02 49.01 53.77 45.44 32.59 23.03 17.53 17.33 15.15 15.18 13.69 8.73
## [145] 8.59 10.94 10.24 11.11 10.44 6.30 6.51 15.55 19.14 22.59 26.49 32.31
## [157] 36.74 34.08 34.74 37.64 29.71 21.70 18.62 13.62 15.34 12.99 17.31 19.50
## [169] 19.89 8.16 6.10 7.01 6.70 3.55 6.79 7.91 20.35 28.12 30.90 38.77
## [181] 34.19 34.88 29.76 30.90 22.57 17.33 12.03 4.91 6.09 2.81 4.70 2.99
## [193] 4.26 8.27 11.00 10.81 10.35 8.84 8.99 11.36 19.70 26.03 32.77 37.31
## [205] 37.88 38.80 33.71 32.62 28.52 20.09 7.18 7.61 13.75 13.00 11.31 10.20
## [217] 9.73 0.88 4.83 8.42 8.40 4.82 6.00 10.81 15.93 20.82 25.70 26.30
## [229] 28.15 29.74 29.06 28.39 27.18 20.69 18.16 17.38 14.83 13.97 14.51 12.49
## [241] 11.57 9.73 6.45 3.34 4.94 3.77 5.18 9.62 17.55 20.32 26.72 29.05
## [253] 21.26 20.59 20.24 19.06 19.75 15.26 15.41 10.84 9.38 2.55 1.86 2.80
## [265] 6.25 6.02 7.61 9.50 9.42 6.63 5.50 8.06 13.58 22.00 34.79 47.94
## [277] 32.75 33.76 37.04 34.06 22.38 17.68 16.36 16.59 15.38 15.15 15.20 14.86
## [289] 15.51 17.24 14.93 8.44 7.40 3.58 2.90 2.92 6.75 17.12 22.18 25.62
## [301] 33.59 36.06 31.39 27.72 24.08 21.24 20.49 20.70 19.78 18.31 18.47 16.91
## [313] 13.64 15.24 13.90 13.29 11.13 6.86 2.72 12.85 20.29 24.44 28.37 29.51
## [325] 30.25 30.08 25.37 22.64 20.68 14.85 14.65 13.38 10.59 11.59 8.41 3.26
## [337] 4.51 8.69 6.61 3.86 1.54 1.38 4.19 10.77 17.86 25.64 35.45 30.25
## [349] 27.28 27.90 26.22 24.53 19.16 14.59 11.30 6.73 6.85 6.35 1.63 5.87
## [361] 3.53 7.02 9.64 11.05 7.44 9.98 8.58 9.48 13.99 27.29 38.79 48.01
## [373] 47.37 39.45 34.02 30.18 23.82 16.12 16.61 15.80 13.34 9.91 10.44 5.64
## [385] 2.22 6.14 9.88 5.59 8.12 3.61 7.99 15.82 14.95 24.38 29.29 31.30
## [397] 31.84 31.28 32.11 32.07 29.07 21.77 19.22 19.09 16.55 18.43 13.14 11.83
## [409] 11.63 12.65 4.45 2.88 4.86 7.39 9.21 18.30 23.76 26.05 31.09 34.80
## [421] 37.80 40.98 40.66 41.22 37.71 25.38 20.07 16.96 15.74 15.92 14.18 11.50
## [433] 9.20 4.88 6.50 6.89 8.19 5.89 7.54 7.83 17.38 22.92 27.59 32.88
## [445] 35.59 35.00 35.02 28.87 21.51 12.18 12.13 8.82 11.77 11.49 2.32 4.79
## [457] 10.85 9.40 7.96 6.98 9.51 7.01 10.86 14.22 21.85 27.91 32.33 37.60
## [469] 35.96 36.38 32.78 29.62 26.05 17.29 15.24 15.09 13.61 7.41 7.75 5.61
## [481] 9.72 10.90 10.49 11.08 10.53 9.04 9.56 14.93 22.74 28.13 27.16 29.84
## [493] 31.70 32.35 29.18 28.31 24.83 19.08 13.53 10.90 11.78 11.82 10.36 10.65
## [505] 5.98 5.33 2.29 4.50 5.97 5.40 4.66 10.27 15.80 22.91 25.48 26.87
## [517] 28.06 25.97 25.84 21.29 16.86 14.63 15.16 13.86 14.55 13.02 9.52 4.26
## [529] 3.20 4.69 7.84 7.74 4.97 5.69 8.16 15.35 17.42 21.63 22.95 22.94
## [541] 23.66 23.42 24.28 22.65 18.83 14.43 11.01## [1] 68.53 71.08 33.51 26.12 18.38 19.56 14.85 17.86 32.69 27.18
## [11] 20.96 14.17 16.69 12.93 7.67 13.61 19.74 6.95 11.84 26.60
## [21] 29.23 29.66 3.39 4.19 16.80 -5.30 1.03 4.87 0.09 6.86
## [31] 8.37 2.19 5.87 41.87 17.55 9.16 7.03 10.54 3.63 -0.77
## [41] 23.82 18.75 11.66 6.41 4.52 2.33 33.90 22.67 -10.93 -9.72
## [51] -2.94 -9.44 3.80 11.93 11.51 7.43 19.65 56.77 36.75 17.64
## [61] 15.52 20.87 21.30 32.14 23.85 49.39 58.86 89.53 87.66 91.96
## [71] 55.34 39.78 18.74 7.02 -2.34 -14.64 1.67 3.37 29.31 18.93
## [81] 80.92 75.89 24.64 22.36 12.32 28.33 37.80 40.44 31.32 72.53
## [91] 120.03 124.46 142.37 108.45 63.15 58.35 33.25 10.57 3.60 3.65
## [101] 5.91 10.89 19.64 35.53 43.88 45.24 43.49 29.12 25.77 43.55
## [111] 37.59 29.94 35.01 39.52 47.16 59.68 62.19 57.29 59.83 76.96
## [121] 75.03 59.41 39.48 34.13 19.70 17.92 19.44 11.22 1.37 7.63
## [131] 8.26 -11.10 4.73 11.86 12.68 5.13 18.92 13.19 15.49 22.46
## [141] 19.40 44.36 62.68 59.45 41.63 19.94 8.40 2.29 -1.84 -1.56
## [151] 1.57 23.84 22.92 13.00 5.17 4.81 4.93 14.82 2.35 21.58
## [161] 39.77 47.55 64.24 101.68 82.15 100.87 55.50 34.57 26.20 15.44
## [171] 10.68 26.79 43.63 35.66 42.14 24.95 26.26 27.23 83.71 113.52
## [181] 121.46 88.35 38.09 28.96 40.71 110.62 134.68 90.23 45.77 36.34
## [191] 32.18 43.23 47.86 23.93 7.38 16.89 19.74 0.88 46.58 86.59
## [201] 56.82 50.70 50.14 41.25 16.63 32.63 41.45 37.57 39.56 31.55
## [211] 42.34 62.39 58.31 38.78 33.12 49.96 13.68 22.92 16.72 16.04
## [221] 24.31 39.02 47.36 56.43 38.37 27.20 18.35 27.56 34.05 15.31
## [231] 7.43 -1.68 6.94 6.86 8.57 0.23 15.01 16.88 25.04 2.37
## [241] 26.36 32.58 16.16 5.40 -0.26 5.83 5.90 -1.70 17.51 27.55
## [251] 7.38 12.21 19.95 33.62 26.28 35.64 34.54 47.23 62.25 86.81
## [261] 80.19 77.39 60.40 38.30 20.86 17.02 12.60 7.53 7.16 6.90
## [271] 19.44 26.70 33.84 23.84 12.12 16.92 23.57 15.57 11.50 22.28
## [281] 14.53 36.08 41.66 65.87 56.45 62.19 77.34 58.27 51.29 32.66
## [291] 20.19 9.00 4.79 6.27 8.21 0.46 22.14 22.61 22.21 17.11
## [301] 15.97 10.62 9.54 5.23 10.81 30.62 45.73 82.29 76.24 34.52
## [311] 24.47 4.86 11.92 10.26 24.47 16.59 7.78 16.24 27.28 26.33
## [321] 22.17 24.91 10.63 21.74 20.18 18.99 26.20 49.26 51.52 99.85
## [331] 205.20 270.03 153.94 63.96 82.64 40.52 11.77 20.71 17.92 8.85
## [341] 10.46 9.74 32.46 30.39 22.52 11.69 19.47 18.53 24.19 19.91
## [351] 17.47 21.44 26.19 37.68 51.04 48.67 51.12 51.07 41.65 51.70
## [361] 40.67 56.83 26.91 26.33 17.01 23.62 30.38 31.94 39.16 34.92
## [371] 38.12 76.88 68.78 48.09 34.88 35.95 22.97 54.72 50.89 74.79
## [381] 92.12 57.47 43.39 44.60 40.34 31.02 33.91 21.01 25.03 22.84
## [391] 34.27 23.98 47.23 49.68 71.44 43.79 26.96 19.32 24.00 17.57
## [401] 26.13 34.19 39.54 43.50 70.56 114.62 108.33 59.08 43.45 13.54
## [411] 11.71 13.58 20.68 25.42 81.23 37.42 34.65 36.02 29.32 44.54
## [421] 59.66 37.77 26.38 20.27 25.32 35.00 50.36 99.47 141.70 114.99
## [431] 150.00 106.82 77.71 65.04 48.04 51.32 27.05 14.73 30.08 31.39
## [441] 23.93 38.47 24.26 13.38 20.05 3.07 17.74 32.63 36.10 41.49
## [451] 72.66 73.60 44.53 12.10 33.79 36.16 25.78 33.68 53.19 34.66
## [461] 20.26 11.56 9.50 -1.43 25.48 18.34 11.94 21.84 8.93 31.25
## [471] 22.45 19.57 20.00 47.80 61.68 61.67 60.44 63.09 74.51 56.06
## [481] 33.60 27.97 31.03 11.22 8.89 8.39 29.91 31.62 50.71 50.52
## [491] 52.43 33.03 40.81 29.61 21.00 19.21 25.59 55.59 48.29 39.40
## [501] 28.97 26.41 29.70 19.29 27.88 11.67 16.29 21.03 21.67 39.59
## [511] 59.10 45.12 112.99 114.31 61.47 19.96 15.71 15.82 16.50 34.26
## [521] 41.88 42.35 30.23 53.94 50.05 61.24 50.40 46.23 33.23 36.44
## [531] 22.77 22.50 2.07 7.64 50.02 27.94 41.47 35.34 17.34 15.69
## [541] 9.82 7.52 16.13 23.10 23.03 27.01 50.23 128.85 142.59 126.33
## [551] 58.10 59.69 67.41 44.93 22.97 19.08 27.66 10.26 89.52 103.09
## [561] 56.04 61.32 52.72 58.09 49.06 48.66 50.59 32.98 22.69 35.79
## [571] 48.39 65.35 76.20 65.06 46.08 53.90 52.60 47.00 36.39 11.06
## [581] 7.42 21.41 22.18 31.43 71.87 66.05 32.25 10.49 49.02 31.63
## [591] 29.97 31.63 40.27 47.74 44.82 43.90 66.10 64.71 68.14 78.74
## [601] 67.50 62.41 22.40 4.72 17.70 16.56 19.40 32.67 50.12 78.43
## [611] 63.83 55.18 42.37 45.01 40.25 46.54 39.57 46.66 56.35 67.80
## [621] 96.57 91.30 116.81 66.16 51.32 15.93 9.75 8.98 9.09 12.28
## [631] 9.87 7.66 27.15 36.22 32.84 23.11 1.54 22.16 21.01 21.09
## [641] 16.25 28.67 40.36 49.88 69.20 74.29 114.97 119.80 91.38 28.75
## [651] 13.59 19.15 11.42 18.17 27.17 32.22 70.80 61.66 62.29 67.85
## [661] 51.72 36.78 26.67 31.43 34.62 77.73 89.22 100.79 64.11 51.06
## [671] 58.05 64.57 51.05 43.50 32.12 28.23 20.08 24.72 42.25 50.29
## [681] 50.90 60.98 59.08 26.06 38.06 31.01 27.55 9.68 32.21 40.38
## [691] 80.95 101.45 75.86 74.07 59.62 63.18 63.35 40.79 18.92 30.70
## [701] 40.31 33.70 34.18 48.21 53.32 36.42 32.86 31.96 18.33 11.07
## [711] 21.47 9.06 30.43 46.13 56.97 64.05 107.56 131.43 90.90 59.36
## [721] 33.14 34.58 23.55 19.91 16.68 16.18 45.26 49.94 37.56 22.86
## [731] 28.77 36.36 24.59 29.15 16.71 11.33 27.87 40.67 43.51 38.10
## [741] 42.49 35.26 46.81 49.16## [1] 26.47 26.94 13.08 13.10 2.19 5.77 4.42 -18.70 27.19 48.48
## [11] 14.25 26.25 22.30 16.80 8.73 22.55 25.50 41.81 26.69 24.60
## [21] 35.22 37.33 38.55 20.86 22.71 11.90 16.60 18.29 4.50 4.94
## [31] 9.48 1.96 25.18 58.60 45.75 27.79 19.75 20.65 15.40 14.62
## [41] 31.08 32.05 46.08 43.78 50.71 56.03 39.11 2.41 4.60 19.22
## [51] 14.27 -10.18 -3.25 0.29 14.49 -3.99 32.33 73.24 59.65 15.03
## [61] 11.87 13.82 26.20 19.15 50.07 72.17 167.00 322.14 255.97 109.57
## [71] 33.47 18.02 1.54 -6.45 -3.63 -7.74 -2.50 3.01 5.95 10.46
## [81] 59.16 83.50 51.05 20.27 36.05 33.51 51.13 61.37 87.62 113.14
## [91] 219.67 226.70 197.89 25.89 28.93 4.89 2.39 3.81 11.30 15.37
## [101] 1.71 -3.63 -5.49 -20.12 32.48 75.51 48.48 28.52 22.85 45.64
## [111] 26.97 21.22 37.66 72.48 129.61 122.14 100.61 97.16 76.17 35.81
## [121] -4.72 1.86 -7.28 -6.56 10.45 16.42 11.15 37.56 112.86 102.51
## [131] 93.18 68.29 55.19 41.81 37.52 40.51 55.42 124.23 67.09 131.63
## [141] 125.00 84.45 90.97 77.72 12.11 -2.57 -1.90 3.60 1.32 8.39
## [151] 9.89 19.89 56.69 99.26 64.93 77.69 35.92 8.30 29.91 54.60
## [161] 80.72 122.09 129.25 197.19 189.36 79.76 92.94 37.46 6.30 -2.56
## [171] -10.26 -1.96 -10.95 5.62 18.49 38.12 40.44 47.40 67.89 45.34
## [181] 74.93 57.82 41.25 34.45 69.33 156.57 228.34 237.55 168.81 135.13
## [191] 82.93 45.19 18.96 7.74 0.93 4.60 5.79 6.49 11.34 8.79
## [201] 43.91 80.46 41.87 42.54 46.25 27.17 32.23 44.97 31.21 59.39
## [211] 50.08 46.97 29.28 20.10 29.39 19.66 13.41 8.85 0.57 16.46
## [221] 17.67 14.82 26.74 59.74 79.58 63.97 44.60 30.83 31.84 32.65
## [231] 31.47 37.34 43.50 69.71 136.47 104.16 123.26 73.68 70.27 19.46
## [241] 16.91 -2.07 6.28 23.14 3.62 2.39 -0.07 -7.14 49.28 68.43
## [251] 75.33 41.63 21.48 45.63 31.07 27.30 42.24 58.45 83.57 150.68
## [261] 202.03 217.92 133.89 75.69 37.24 13.68 -12.62 -9.59 7.93 5.91
## [271] -0.47 0.39 16.65 51.11 62.65 25.43 39.30 50.78 18.94 38.63
## [281] 47.63 72.34 157.03 161.22 115.81 99.93 113.71 48.90 7.83 -5.90
## [291] -7.62 -15.79 -18.06 5.67 40.22 24.69 74.51 99.93 72.41 45.93
## [301] 24.28 42.73 55.87 53.40 61.45 130.52 222.32 325.17 186.36 67.83
## [311] 60.33 24.27 10.99 10.47 3.69 -2.60 -5.78 16.27 25.82 39.67
## [321] 63.87 81.16 58.29 53.93 32.08 35.88 77.58 62.64 87.09 203.51
## [331] 138.05 66.27 85.54 150.15 144.94 92.82 41.02 11.02 16.94 6.42
## [341] 2.91 5.71 30.05 21.79 71.35 80.31 73.76 61.15 32.69 66.24
## [351] 116.70 70.80 73.68 157.42 305.38 355.60 199.50 206.65 139.13 37.92
## [361] 77.16 90.38 77.42 35.75 28.97 34.11 55.56 94.26 254.36 162.34
## [371] 52.39 59.00 54.96 74.38 42.86 43.93 96.86 92.25 111.25 26.40
## [381] 43.18 20.61 26.13 11.27 -3.91 -1.87 -17.42 -8.62 -5.53 -2.13
## [391] 3.98 2.82 35.82 41.26 21.70 29.66 41.61 29.97 18.64 27.09
## [401] 29.46 65.87 61.06 95.04 70.39 58.09 41.69 35.75 24.76 8.30
## [411] 13.82 13.07 1.80 -1.09 14.24 22.97 68.36 84.03 80.23 71.31
## [421] 54.29 40.45 24.19 25.54 27.18 45.39 65.20 49.66 49.04 61.29
## [431] 45.20 40.06 24.88 28.17 17.53 30.34 65.24 78.92 35.25 -13.23
## [441] 41.98 70.21 42.10 40.03 31.67 38.10 20.48 13.01 29.66 76.17
## [451] 49.22 88.98 97.20 87.12 51.35 41.37 18.91 4.01 4.72 -3.80
## [461] 14.86 35.03 46.02 28.63 41.06 80.70 76.01 66.10 67.06 6.39
## [471] 47.69 65.57 40.55 65.62 101.57 131.04 82.78 48.86 39.21 66.22
## [481] 69.05 57.37 53.03 48.83 23.40 29.42 58.46 91.30 7.47 19.74
## [491] 4.33 11.92 12.61 1.88 8.38 12.65 5.41 30.48 34.43 23.74
## [501] 12.09 2.37 12.63 10.41 17.41 13.89 7.58 12.10 2.07 5.98
## [511] 20.02 23.92 44.58 53.58 23.61 28.74 32.20 19.43 20.48 30.16
## [521] 27.89 45.80 44.57 31.22 46.58 35.87 32.21 14.57 8.20 6.33
## [531] 22.39 16.57 15.54 16.08 62.66 34.09 48.88 57.70 58.65 42.04
## [541] 53.60 47.30 40.45 51.86 42.74 68.30 59.50 56.64 32.67 36.09
## [551] 73.33 35.90 32.48 6.83 11.33 -0.36 -0.89 13.63 17.25 29.41
## [561] 62.25 66.29 27.75 34.61 27.12 61.97 45.88 43.65 54.70 88.19
## [571] 100.80 88.92 71.31 98.28 119.67 84.01 43.36 27.64 8.66 9.62
## [581] 5.58 8.99 8.55 13.42 33.48 48.04 31.64 26.83 20.46 24.25
## [591] 18.82 23.43 29.53 43.95 74.77 118.88 112.93 69.00 72.10 62.26
## [601] 47.28 17.26 9.91 15.16 6.40 3.33 11.29 4.46 35.86 24.97
## [611] 30.52 28.05 42.64 29.01 16.67 28.03 14.37 38.65 42.73 38.70
## [621] 44.05 89.03 87.93 65.48 40.55 36.14 25.24 10.07 10.37 -4.90
## [631] 20.19 28.21 120.78 152.09 87.97 55.42 27.23 33.40 33.72 20.98
## [641] 30.69 53.94 47.66 90.79 94.36 77.02 66.38 27.20 12.14 11.15
## [651] 4.76 -0.18 6.88 3.80 46.50 22.28 59.63 87.37 106.97 54.80
## [661] 22.08 49.66 21.62 41.98 36.24 75.86 118.65 102.60 120.82 131.61
## [671] 77.38 39.81 8.60 -0.46 -0.15 -5.27 0.76 14.54 32.37 10.98
## [681] 49.87 70.99 50.28 36.29 42.05 32.51 37.18 32.85 36.62 63.40
## [691] 79.20 72.11 63.82 33.90 13.62 19.69 19.25 7.86 5.37 6.84
## [701] -5.26 21.76 65.34 34.88 84.15 31.96 28.18 32.29 45.85 36.95
## [711] 33.29 29.50 30.93 49.28 58.10 80.99 91.71 75.66 79.47 54.58
## [721] 45.71 46.04 18.25 0.64 0.12 -5.96 8.99 18.53 89.97 74.59
## [731] 43.15 22.79 18.26 17.76 21.00 11.04 15.92 73.68 127.12 249.39
## [741] 281.16 198.56 70.62 44.19## [1] 82.02 46.24 48.98 43.83 40.21 50.43 39.21 35.89 36.35 43.73
## [11] 35.03 59.20 72.76 67.89 47.19 39.97 58.65 64.00 59.27 48.44
## [21] 49.77 37.87 47.94 45.07 61.63 44.74 39.04 34.78 43.87 41.75
## [31] 26.65 27.33 49.33 46.04 46.73 41.46 52.97 67.50 40.14 46.15
## [41] 41.82 46.68 54.82 46.45 50.99 61.78 41.48 47.14 41.05 35.53
## [51] 36.58 35.41 50.59 37.44 37.16 44.06 43.24 48.17 34.46 38.34
## [61] 64.44 39.94 36.92 20.38 28.03 34.23 44.19 47.56 55.59 37.73
## [71] 58.83 81.32 65.85 40.04 38.13 40.57 41.47 13.80 8.55 55.83
## [81] 11.89 42.74 58.55 26.91 26.84 35.12 53.52 45.19 35.13 54.73
## [91] 16.06 37.73 30.41 36.50 42.76 51.75 63.55 47.98 52.55 25.68
## [101] 29.36 36.20 41.55 66.88 28.48 37.15 38.61 40.21 38.08 45.49
## [111] 32.89 52.43 52.69 58.49 55.16 33.85 38.54 30.92 38.25 54.94
## [121] 56.61 25.99 30.28 37.36 36.88 39.30 36.06 60.99 38.75 28.84
## [131] 42.79 35.97 38.39 51.17 43.64 55.02 58.95 65.18 64.96 45.50
## [141] 47.94 39.37 33.57 38.41 50.38 37.09 25.01 28.28 22.43 32.40
## [151] 45.68 69.25 62.11 52.95 40.36 68.58 44.48 42.76 16.00 33.81
## [161] 61.21 86.63 47.99 50.29 52.70 53.70 43.01 34.25 22.79 39.22
## [171] 40.99 42.02 24.49 31.03 72.01 77.74 79.13 77.42 60.41 33.75
## [181] 31.78 25.07 24.82 23.62 28.96 38.38 75.74 171.98 93.30 107.50
## [191] 87.49 67.16 66.30 47.05 29.54 35.07 26.91 31.49 50.14 71.33
## [201] 67.84 52.32 36.30 34.55 -5.27 22.82 46.52 56.59 34.56 40.29
## [211] 126.40 105.36 77.54 40.73 59.43 57.65 60.00 65.52 55.28 37.19
## [221] 30.03 36.12 33.91 56.69 41.67 44.42 45.13 29.97 31.93 22.58
## [231] -4.96 42.61 29.26 27.90 25.51 36.74 37.54 32.68 34.34 34.68
## [241] 38.82 33.24 52.71 38.58 33.88 39.69 68.99 43.02 44.27 13.19
## [251] 46.48 36.91 18.94 11.03 -23.10 16.87 10.30 41.08 38.22 16.06
## [261] 27.39 49.79 65.52 57.63 38.75 37.83 25.09 26.50 18.86 27.67
## [271] 85.04 57.52 72.56 64.19 55.48 71.38 50.10 37.43 40.23 34.39
## [281] 42.67 47.32 58.29 57.30 46.06 31.23 16.80 34.85 28.67 14.94
## [291] 26.81 32.53 31.36 34.31 57.57 87.48 131.35 74.84 67.48 56.91
## [301] 54.26 48.78 65.32 59.88 62.00 23.00 43.68 25.01 43.53 38.06
## [311] 42.66 46.27 57.73 25.73 24.49 29.44 30.63 44.53 62.69 109.15
## [321] 25.41 61.10 49.15 48.19 72.54 54.95 47.36 50.81 30.74 44.76
## [331] 64.99 59.49 66.07 53.85 47.71 72.44 72.62 46.24 43.69 53.08
## [341] 54.16 54.39 67.18 74.66 51.13 31.75 49.99 51.95 34.08 26.86
## [351] 29.80 9.59 28.08 67.36 44.33 50.11 71.14 65.00 63.37 54.81
## [361] 41.69 44.54 36.65 28.22 34.84 39.40 40.48 73.04 72.64 73.87
## [371] 69.79 68.07 72.45 51.04 32.13 15.21 33.16 39.20 34.74 40.38
## [381] 37.74 69.33 83.59 65.31 86.27 83.58 37.35 47.87 48.77 53.36
## [391] 60.14 81.40 49.63 47.46 36.61 27.04 50.63 23.17 44.78 47.14
## [401] 54.04 57.95 44.44 37.48 39.20 34.41 26.35 41.41 60.09 47.30
## [411] 49.57 69.35 52.64 38.35 56.25 42.31 34.22 34.42 54.10 48.43
## [421] 45.61 20.68 25.91 24.04 36.10 33.54 30.18 44.50 48.68 31.91
## [431] 30.92 28.16 37.91 57.72 43.01 30.12 16.09 35.80 58.61 75.66
## [441] 62.03 67.97 42.42 41.09 55.80 61.46 33.66 30.47 34.46 53.88
## [451] 76.11 61.27 42.67 52.40 83.16 59.40 54.04 35.54 47.70 35.94
## [461] 44.82 42.72 59.00 118.80 57.97 76.83 60.71 46.46 52.42 49.96
## [471] 45.30 41.62 50.82 65.74 71.82 76.43 57.63 61.59 68.69 50.95
## [481] 68.69 45.54 51.35 29.89 32.07 34.99 44.53 90.19 57.46 43.27
## [491] 41.81 51.87 51.82 37.83 25.37 57.82 64.23 41.40 47.48 50.78
## [501] 57.23 35.77 43.01 38.78 54.99 45.17 50.38 39.44 38.93 31.29
## [511] 34.67 61.57 40.79 47.12 36.04 36.95 46.95 38.53 31.51 62.45
## [521] 52.01 42.93 35.16 27.14 32.69 32.40 18.54 39.29 46.15 38.07
## [531] 32.18 23.71 34.56 26.44 24.77 33.23 28.35 29.59 34.29 30.35
## [541] 32.10 25.20 21.53 11.52 36.02 40.77 46.11Visualizamos los datos
Medidas de dispercion
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## -0.400 3.325 13.085 16.391 27.090 61.060
## [1] 0.12 0.38## Min. 1st Qu. Median Mean 3rd Qu. Max.
## -14.64 17.62 31.43 37.23 50.12 270.03
## [1] 6.86 7.38 7.43 10.26 11.22 17.92 18.92 19.40 19.44 19.74 19.91 21.01
## [13] 22.92 22.97 23.84 23.93 24.47 26.20 26.33 27.55 31.43 31.63 32.63 40.67
## [25] 43.50 47.23 51.32 59.08 62.19## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.000 4.425 12.370 16.045 25.835 48.580
## [1] 0.12 0.38## Min. 1st Qu. Median Mean 3rd Qu. Max.
## -20.12 15.32 35.81 47.27 65.27 355.60
## [1] 73.68## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.88 9.04 15.35 17.66 25.43 53.99
## [1] 2.55 2.99 3.20 4.26 7.01 7.41 7.60 7.61 8.12 8.16 8.99 9.04
## [13] 9.40 9.56 9.73 10.44 10.59 10.81 10.90 10.94 14.51 14.85 14.93 15.15
## [25] 15.24 15.35 15.80 17.33 17.38 17.42 24.53 26.05 30.25 30.90## Min. 1st Qu. Median Mean 3rd Qu. Max.
## -23.10 34.51 43.24 45.85 55.22 171.98
## [1] 43.01Podemos observar como el nivel de O3 de enero del 2019 es mayor al nivel de O3 de enero del 2020.
## [1] 14.59937## [1] 213.1417
## [1] 13.28159## [1] 176.4007
### Miremos esta otra grafica Esto es vastante interesante, en octubre del 2020 es mucho menor el nivel de O3 en el aire que en enero del 2020 y en enero del 2019, la pregunta es porque?, es muy sencillo de explicar esto pasa por que el momento en el que nos encontramos esa crucial, las personas dejaron de salir, los carros dejaron de circular y por ende el O3 dejo de producirse dando paso a que el O3 que existia se dispersara a travez del tiempo y los niveles O3 disminuyeran.
## [1] 10.66746## [1] 113.7947
Niveles de MP10
Al igual que el analisis de O3, analisaremos como es el nivel de MP10 en el aire en cuestion a las fechas de enero del 2019, enero del 2020 y octubre del 2020
## [1] 29.3919## [1] 863.8836
## [1] 49.37823## [1] 2438.209
Interesantes datos, podemos observar como el nivel de MP10 en el aire eran mucho mayor en enero del 2020 que en enero del 2019 esto es deducible ya que hay una tendencia a crecimiento en contaminantes a travez del tiempo pero… y si analizamos esta otra grafica. __________________________________________________________________________________________________ Ahora surge una pregunta, se suponia que el nivel de contaminacion en el aire iba en crecimiento a travez del tiempo…poque esta grafica no respeta esa tendencia.
## [1] 18.44385## [1] 340.1758
Podemos observar como el nivel de MP10 es mucho menor al nivel de MP10 de enero del 2019 y literalmente enero del 2020 tenia el doble de MP10 en el aire, esto es un claro ejemplo de como esta impactando la pandemia en el medio ambiente, esto es un punto bueno poder decir que tenemos un aire mas limpio….y eso es todo lo bueno.
Tablas de distribucion de frecuancia nivel de O3 de enero del 2019, enero del 2020, octubre del 2020
## Class limits f rf rf(%) cf cf(%)
## [-0.404,5.2391) 241 0.32 32.39 241 32.39
## [5.2391,10.882) 102 0.14 13.71 343 46.10
## [10.882,16.525) 87 0.12 11.69 430 57.80
## [16.525,22.169) 74 0.10 9.95 504 67.74
## [22.169,27.812) 65 0.09 8.74 569 76.48
## [27.812,33.455) 49 0.07 6.59 618 83.06
## [33.455,39.098) 46 0.06 6.18 664 89.25
## [39.098,44.741) 53 0.07 7.12 717 96.37
## [44.741,50.384) 18 0.02 2.42 735 98.79
## [50.384,56.027) 7 0.01 0.94 742 99.73
## [56.027,61.671) 2 0.00 0.27 744 100.00## Class limits f rf rf(%) cf cf(%)
## [0,4.4605) 189 0.25 25.40 189 25.40
## [4.4605,8.9211) 105 0.14 14.11 294 39.52
## [8.9211,13.382) 96 0.13 12.90 390 52.42
## [13.382,17.842) 67 0.09 9.01 457 61.42
## [17.842,22.303) 66 0.09 8.87 523 70.30
## [22.303,26.763) 44 0.06 5.91 567 76.21
## [26.763,31.224) 47 0.06 6.32 614 82.53
## [31.224,35.684) 37 0.05 4.97 651 87.50
## [35.684,40.145) 51 0.07 6.85 702 94.35
## [40.145,44.605) 27 0.04 3.63 729 97.98
## [44.605,49.066) 15 0.02 2.02 744 100.00## Class limits f rf rf(%) cf cf(%)
## [0.8712,5.7493) 58 0.11 10.60 58 10.60
## [5.7493,10.627) 114 0.21 20.84 172 31.44
## [10.627,15.505) 105 0.19 19.20 277 50.64
## [15.505,20.383) 80 0.15 14.63 357 65.27
## [20.383,25.262) 51 0.09 9.32 408 74.59
## [25.262,30.14) 55 0.10 10.05 463 84.64
## [30.14,35.018) 45 0.08 8.23 508 92.87
## [35.018,39.896) 27 0.05 4.94 535 97.81
## [39.896,44.774) 3 0.01 0.55 538 98.35
## [44.774,49.652) 6 0.01 1.10 544 99.45
## [49.652,54.53) 3 0.01 0.55 547 100.00Tablas de distribucion de frecuancia nivel de MP10 de enero del 2019, enero del 2020, octubre del 2020
## Class limits f rf rf(%) cf cf(%)
## [-14.7864,11.3515) 113 0.15 15.19 113 15.19
## [11.3515,37.4894) 333 0.45 44.76 446 59.95
## [37.4894,63.6272) 195 0.26 26.21 641 86.16
## [63.6272,89.7651) 62 0.08 8.33 703 94.49
## [89.7651,115.903) 25 0.03 3.36 728 97.85
## [115.903,142.041) 10 0.01 1.34 738 99.19
## [142.041,168.179) 4 0.01 0.54 742 99.73
## [168.179,194.317) 0 0.00 0.00 742 99.73
## [194.317,220.455) 1 0.00 0.13 743 99.87
## [220.455,246.592) 0 0.00 0.00 743 99.87
## [246.592,272.73) 1 0.00 0.13 744 100.00## Class limits f rf rf(%) cf cf(%)
## [-20.3212,14.1767) 174 0.23 23.39 174 23.39
## [14.1767,48.6747) 306 0.41 41.13 480 64.52
## [48.6747,83.1726) 156 0.21 20.97 636 85.48
## [83.1726,117.671) 52 0.07 6.99 688 92.47
## [117.671,152.168) 26 0.03 3.49 714 95.97
## [152.168,186.666) 8 0.01 1.08 722 97.04
## [186.666,221.164) 10 0.01 1.34 732 98.39
## [221.164,255.662) 6 0.01 0.81 738 99.19
## [255.662,290.16) 2 0.00 0.27 740 99.46
## [290.16,324.658) 2 0.00 0.27 742 99.73
## [324.658,359.156) 2 0.00 0.27 744 100.00## Class limits f rf rf(%) cf cf(%)
## [-23.331,-5.4191) 1 0.00 0.18 1 0.18
## [-5.4191,12.493) 8 0.01 1.46 9 1.65
## [12.493,30.405) 79 0.14 14.44 88 16.09
## [30.405,48.317) 254 0.46 46.44 342 62.52
## [48.317,66.228) 141 0.26 25.78 483 88.30
## [66.228,84.14) 50 0.09 9.14 533 97.44
## [84.14,102.05) 7 0.01 1.28 540 98.72
## [102.05,119.96) 4 0.01 0.73 544 99.45
## [119.96,137.88) 2 0.00 0.37 546 99.82
## [137.88,155.79) 0 0.00 0.00 546 99.82
## [155.79,173.7) 1 0.00 0.18 547 100.00Histogramas y políginos de distribución de frecuencia de nivel de O3 en enero del 2019
Histogramas y políginos de distribución de frecuencia de nivel de O3 en enero del 2020
Crecimiento de contaminacion a en el mes de enero del año 2019
Podemos observar como se comporta el crecimiento de O3 en el aire en el mes de enero del 2019a travez del tiempo.
ggplot(data = CalidadDelAireEnero2019) +
geom_point(mapping = aes(x = CalidadDelAireEnero2019$Time, y =o3Enero2019 , color = "Magenta"))
ggplot(data = CalidadDelAireEnero2019) +
geom_point(mapping = aes(x = CalidadDelAireEnero2019$Time, y =mpEnero2019 , color = "Magenta"))
Crecimiento de contaminacion a en el mes de enero del año 2020
Podemos observar como se comporta el crecimiento de O3 en el aire en el mes de enero del 2020a travez del tiempo.
ggplot(data = CalidadDelAireEnero2020) +
geom_point(mapping = aes(x = CalidadDelAireEnero2020$Time, y =o3Enero2020 , color = "Magenta"))
ggplot(data = CalidadDelAireEnero2019) +
geom_point(mapping = aes(x = CalidadDelAireEnero2020$Time, y =mpEnero2020 , color = "Magenta"))
Crecimiento de contaminacion a en el mes de octubre del año 2020
Podemos observar como se comporta el crecimiento de O3 en el aire en el mes de octubre del 2020 a travez del tiempo.
ggplot(data = CalidadDelAireOctubre2020) +
geom_point(mapping = aes(x = CalidadDelAireOctubre2020$Time, y =o3Octubre2020 , color = "Magenta"))
ggplot(data = CalidadDelAireOctubre2020) +
geom_point(mapping = aes(x = CalidadDelAireOctubre2020$Time, y =mpOctubre2020 , color = "Magenta"))
Matriz de dispercion
o3 <- CalidadDelAireEnero2019$O3
mp <- CalidadDelAireEnero2019$PM10
tiempo <- CalidadDelAireEnero2019$Time
matriz <- data.frame(o3, tiempo,mp)
pairs(matriz)
## Puntos a aclarar Como pudimos observar este análisis se hizo a cabo con la ayuda de 3 fechas importantes, enero del 2019, enero del 2020 y octubre del 2020 esto con la finalidad de hacer una comparativa cuando el crecimiento de los contaminantes es continuo y como una pandemia viene y afecta todas las áreas posibles, economía, trabajo, tecnología y como analizamos en este caso el medio ambiente. Este análisis son con los datos de la cuidad de Hermosillo sonora.
Preguntas
¿Este año tiene menor cantidad de contaminantes atmosféricos que el año pasado?
R = Es totalmente correcto, este año tiene un medio ambiente más limpio que el año pasado, esto pasa porque el mundo se paró por causa de esta pandemia, el mundo dio una vuelta de 360 grados, dejamos de circular en las calles y el aire comenzó a dispersar los contaminantes a través del tiempo
¿Cuál es la influencia de la pandemia sobre la calidad del aire? R= Este es un ejemplo de como el hombre está matando a la tierra, los ríos, mares, bosques se empezaron a purificar y el aire no sería una excepción, esto es un punto sumamente importante de analizar y de cuestionar, la diferencia radica en el hecho de la reducción masiva de tráfico en las calles por causa de la pandemia, se dejaron de visitar parques, ríos, playas y por ende el vehículo dejo de estar en circulación dando paso a una purificación del medio ambiente. ¿Qué periodos de este año están más contaminados que el año pasado? R= enero de este año 2020 está más contaminado que enero del 2020.
¿Por qué un año está más contaminado que otro en ciertos periodos? Esto se debe al que las personas comenzaron a salir a través del tiempo generando nuevas oleadas de contaminación un ejemplo muy sencillo es la fecha del 16 de septiembre el cual fue el día con más tráfico en las calles en lo que lleva del año y ese día era más que obvio las personas decidieron salir a festejar el día al igual que el día de la madre y el día del padre fueron fechas donde la circulación de vehículos aumento demasiado.
Pregunta de rescate (opcional):
Mini ensayo de mínimo media y máximo una cuartilla contestando a la pregunta: ¿la gente realmente quiere ser feliz o es una fabricada que nos vendieron? (Use datos para fundamentarse)
La gente es un ser sumamente complicado que vive de una manera muy sencilla, esta pregunta la han debatido demasiado filosos y grandes pensantes de nuestra era, el ser humano actualmente compra el termino felicidad ya que en zonas de áfrica donde las personas no están tristes por un teléfono, en ocasiones uno mismo se da el termino de infelicidad o de ser una persona triste, con el tiempo el hombre adopta modas y criterios los cuales están implantados por el lugar o zona donde residen, hay una tribuí llamada centinel la cual jamás ha tenido contacto con otros seres humanos, esas personas viven dentro de su ideología, religión y costumbres ahora viene de nuevo la pregunta, usted….. compra la felicidad? la verdad es que si la compramos y es algo inevitable.