mon\u00f3tono<\/span><\/strong><\/h2>\n A fun\u00e7\u00e3o dnorm<\/strong> retorna o valor da fun\u00e7\u00e3o de densidade de probabilidade (pdf) da distribui\u00e7\u00e3o normal dada alguma vari\u00e1vel aleat\u00f3ria x<\/em> , uma m\u00e9dia populacional \u03bc<\/em> e um desvio padr\u00e3o populacional \u03c3<\/em> . A sintaxe para usar dnorm \u00e9 a seguinte:<\/span><\/p>\n dnorm(x, m\u00e9dia, sd)<\/span><\/strong><\/p>\n O c\u00f3digo a seguir demonstra alguns exemplos de dnorm<\/strong> em a\u00e7\u00e3o:<\/span><\/p>\n #find the value of the standard normal distribution pdf at x=0<\/span>\ndnorm(x=0, mean=0, sd=1)\n#[1]0.3989423\n\n#by default, R uses mean=0 and sd=1<\/span>\ndnorm(x=0)\n#[1]0.3989423\n\n#find the value of the normal distribution pdf at x=10 with mean=20 and sd=5\ndnorm(x=10, mean=20, sd=5)<\/span>\n#[1]0.01079819<\/span><\/span>\n<\/strong><\/pre>\n Normalmente, ao tentar resolver quest\u00f5es sobre probabilidade usando a distribui\u00e7\u00e3o normal, voc\u00ea usar\u00e1 frequentemente pnorm<\/strong> em vez de dnorm<\/strong> . Uma aplica\u00e7\u00e3o \u00fatil de dnorm<\/strong> , entretanto, \u00e9 criar um gr\u00e1fico de distribui\u00e7\u00e3o normal em R. O c\u00f3digo a seguir ilustra como fazer isso:<\/span><\/p>\n #Create a sequence of 100 equally spaced numbers between -4 and 4<\/span>\nx <- seq(-4, 4, length=100)\n\n#create a vector of values that shows the height of the probability distribution<\/span>\n#for each value in x<\/span>\ny <- dnorm(x)\n\n#plot x and y as a scatterplot with connected lines (type = \"l\") and add<\/span>\n#an x-axis with custom labels<\/span>\nplot(x,y, type = \"l\", lwd = 2, axes = FALSE, xlab = \"\", ylab = \"\")\naxis(1, at = -3:3, labels = c(\"-3s\", \"-2s\", \"-1s\", \"mean\", \"1s\", \"2s\", \"3s\"))<\/strong><\/pre>\n Isso gera o seguinte gr\u00e1fico:<\/span><\/p>\n norma<\/span><\/strong><\/h2>\n A fun\u00e7\u00e3o pnorm<\/strong> retorna o valor da fun\u00e7\u00e3o de densidade cumulativa (cdf) da distribui\u00e7\u00e3o normal dada alguma vari\u00e1vel aleat\u00f3ria q<\/em> , uma m\u00e9dia populacional \u03bc<\/em> e um desvio padr\u00e3o populacional \u03c3<\/em> . A sintaxe para usar pnorm \u00e9 a seguinte:<\/span><\/p>\n norma(q, m\u00e9dia, sd)<\/span><\/strong><\/p>\n Em termos simples, pnorm<\/strong> retorna a \u00e1rea \u00e0 esquerda de um determinado valor x<\/em> na distribui\u00e7\u00e3o normal. Se voc\u00ea estiver interessado na \u00e1rea \u00e0 direita de um determinado valor q<\/em> , voc\u00ea pode simplesmente adicionar o argumento lower.tail = FALSE<\/strong><\/span><\/p>\n pnorm(q, m\u00e9dia, sd, lower.tail = FALSE)<\/span><\/strong><\/p>\n Os exemplos a seguir ilustram como resolver algumas quest\u00f5es de probabilidade usando pnorm.<\/span><\/p>\n Exemplo 1:<\/strong> Suponha que a altura dos homens em uma determinada escola seja normalmente distribu\u00edda com m\u00e9dia de \u03bc<\/span> = 70 polegadas e<\/span><\/span><\/span><\/span><\/span> desvio padr\u00e3o de \u03c3 = 2 polegadas.<\/span><\/span><\/span><\/span><\/span><\/em> Aproximadamente que porcentagem de homens nesta escola tem mais de 74 polegadas de altura?<\/span><\/span><\/span><\/span><\/span><\/em><\/span><\/p>\n #find percentage of males that are taller than 74 inches in a population with<\/span>\n#mean = 70 and sd = 2<\/span>\npnorm(74, mean=70, sd=2, lower.tail=FALSE)\n\n# [1]0.02275013<\/span><\/span><\/strong><\/pre>\n Nesta escola, 2.275% dos homens t\u00eam mais de 74 cent\u00edmetros de altura.<\/span><\/p>\n Exemplo 2:<\/strong> Suponha que o peso de uma certa esp\u00e9cie de lontra seja normalmente distribu\u00eddo com m\u00e9dia \u03bc<\/span> = 30 lb e<\/span><\/span><\/span><\/span><\/span> desvio padr\u00e3o de \u03c3 = 5 lb. Aproximadamente que porcentagem desta esp\u00e9cie de lontra pesa menos de 22 libras?<\/span><\/span><\/span><\/span><\/span><\/em><\/span><\/p>\n #find percentage of otters that weight less than 22 lbs in a population with<\/span>\n#mean = 30 and sd = 5<\/span>\npnorm(22, mean=30, sd=5)\n\n# [1]0.05479929<\/span><\/span><\/strong><\/pre>\n Cerca de 5,4799% desta esp\u00e9cie de lontra pesa menos de 22 libras.<\/span><\/p>\n Exemplo 3:<\/strong> Suponha que a altura das plantas em uma determinada regi\u00e3o seja normalmente distribu\u00edda com m\u00e9dia de \u03bc<\/span> = 13 polegadas e<\/span><\/span><\/span><\/span><\/span> desvio padr\u00e3o de \u03c3 = 2 polegadas. Aproximadamente que porcentagem de plantas nesta regi\u00e3o tem entre 25 e 35 cent\u00edmetros de altura?<\/span><\/span><\/span><\/span><\/span><\/em><\/span><\/p>\n #find percentage of plants that are less than 14 inches tall, then subtract the\n#percentage of plants that are less than 10 inches tall, based on a population\n#with mean = 13 and sd = 2<\/span>\npnorm(14, mean=13, sd=2) - pnorm(10, mean=13, sd=2)\n\n# [1]0.6246553<\/span><\/span><\/strong><\/pre>\n Cerca de 62,4655% das plantas desta regi\u00e3o t\u00eam entre 25 e 35 cent\u00edmetros de altura.<\/span><\/p>\n norma<\/span><\/strong><\/h2>\n A fun\u00e7\u00e3o qnorm<\/strong> retorna o valor da fun\u00e7\u00e3o de densidade cumulativa inversa (cdf) da distribui\u00e7\u00e3o normal dada alguma vari\u00e1vel aleat\u00f3ria p<\/em> , uma m\u00e9dia populacional \u03bc<\/em> e um desvio padr\u00e3o populacional \u03c3<\/em> . A sintaxe para usar qnorm \u00e9 a seguinte:<\/span><\/p>\n qnorm (p, m\u00e9dia, sd)<\/span><\/strong><\/p>\n Em termos simples, voc\u00ea pode usar qnorm<\/strong> para descobrir qual \u00e9 o escore Z do p-\u00e9simo<\/sup> quantil da distribui\u00e7\u00e3o normal.<\/span><\/p>\n O c\u00f3digo a seguir demonstra alguns exemplos de qnorm<\/strong> em a\u00e7\u00e3o:<\/span><\/p>\n #find the Z-score of the 99th quantile of the standard normal distribution<\/span> \nqnorm(.99, mean=0, sd=1)\n#[1]2.326348\n\n#by default, R uses mean=0 and sd=1\nqnorm(.99)<\/span>\n#[1]2.326348\n\n#find the Z-score of the 95th quantile of the standard normal distribution<\/span>\nqnorm(.95)\n#[1]1.644854\n\n#find the Z-score of the 10th quantile of the standard normal distribution<\/span>\nqnorm(.10)\n#[1]-1.281552<\/span>\n<\/span><\/strong><\/pre>\n norma<\/span><\/strong><\/h2>\n A fun\u00e7\u00e3o rnorm<\/strong> gera um vetor de vari\u00e1veis aleat\u00f3rias normalmente distribu\u00eddas dado um comprimento de vetor n<\/em> , uma m\u00e9dia populacional \u03bc<\/em> e um desvio padr\u00e3o populacional \u03c3<\/em> . A sintaxe para usar rnorm \u00e9 a seguinte:<\/span><\/p>\n norma (n, m\u00e9dia, sd)<\/span><\/strong><\/p>\n O c\u00f3digo a seguir demonstra alguns exemplos de rnorm<\/strong> em a\u00e7\u00e3o:<\/span><\/p>\n #generate a vector of 5 normally distributed random variables with mean=10 and sd=2<\/span>\nfive <- rnorm(5, mean = 10, sd = 2)\nfive\n# [1] 10.658117 8.613495 10.561760 11.123492 10.802768\n\n#generate a vector of 1000 normally distributed random variables with mean=50 and sd=5\n<\/span>narrowDistribution <- rnorm(1000, mean = 50, sd = 15)\n\n<\/span>#generate a vector of 1000 normally distributed random variables with mean=50 and sd=25<\/span>\nwideDistribution <- rnorm(1000, mean = 50, sd = 25)\n\n<\/span>#generate two histograms to view these two distributions side by side, specify\n#50 bars in histogram and x-axis limits of -50 to 150\npar(mfrow=c(1, 2)) #one row, two columns<\/span>\nhist(narrowDistribution, breaks=50, xlim=c(-50, 150))<\/span>\nhist(wideDistribution, breaks=50, xlim=c(-50, 150))<\/span>\n<\/span><\/span><\/span><\/strong><\/pre>\n Isso gera os seguintes histogramas:<\/span><\/p>\n Observe como a distribui\u00e7\u00e3o ampla \u00e9 muito mais ampla do que a distribui\u00e7\u00e3o estreita. Na verdade, especific\u00e1mos que o desvio padr\u00e3o na distribui\u00e7\u00e3o ampla era de 25, em compara\u00e7\u00e3o com apenas 15 na distribui\u00e7\u00e3o estreita. Observe tamb\u00e9m que ambos os histogramas est\u00e3o centrados na m\u00e9dia de 50.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"A distribui\u00e7\u00e3o normal \u00e9 a distribui\u00e7\u00e3o mais comumente usada em estat\u00edsticas. Este tutorial explica como usar a distribui\u00e7\u00e3o normal em R usando as fun\u00e7\u00f5es dnorm , pnorm , rnorm e qnorm . mon\u00f3tono A fun\u00e7\u00e3o dnorm retorna o valor da fun\u00e7\u00e3o de densidade de probabilidade (pdf) da distribui\u00e7\u00e3o normal dada alguma vari\u00e1vel aleat\u00f3ria x , […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[],"class_list":["post-458","post","type-post","status-publish","format-standard","hentry","category-guia"],"yoast_head":"\n
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