{"id":611,"date":"2025-07-28T15:29:38","date_gmt":"2025-07-28T19:29:38","guid":{"rendered":"https:\/\/literaciadigital.ufms.br\/?page_id=611"},"modified":"2025-07-28T15:29:38","modified_gmt":"2025-07-28T19:29:38","slug":"10-0","status":"publish","type":"page","link":"https:\/\/literaciadigital.ufms.br\/en\/data8\/10-0\/","title":{"rendered":"Cap\u00edtulo 10"},"content":{"rendered":"<div style=\"position: relative\">\n<div style=\"float: left;width: 300px;background-color: #f5f5f5;border: 1px solid #ddd;border-radius: 5px;padding: 15px;margin-right: 20px;margin-bottom: 5px;overflow: hidden\">\n<h3 style=\"margin: 0 0 10px 0;padding-bottom: 8px;border-bottom: 1px solid #ddd\">\u00cdndice<\/h3>\n<ol style=\"margin: 0;padding-left: 0;list-style-type: none\">\n<li style=\"margin-bottom: 5px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/1-0\/\">1. O que \u00e9 Ci\u00eancia de Dados?<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/1-0\/1-1\/\">1.1. Introdu\u00e7\u00e3o<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/1-0\/1-1\/1-1\/\">1.1.1. Ferramentas Computacionais<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/1-0\/1-1\/1-2\/\">1.1.2. T\u00e9cnicas Estat\u00edsticas<\/a><\/li>\n<\/ul>\n<\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/1-0\/1-2\/\">1.2. Por que Ci\u00eancia de Dados?<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/1-0\/1-3\/\">1.3. Tra\u00e7ando os Cl\u00e1ssicos<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/1-0\/1-3\/3-1\/\">1.3.1. Personagens Liter\u00e1rios<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/1-0\/1-3\/3-2\/\">1.3.2. Outro Tipo de Personagem<\/a><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<li style=\"margin-bottom: 5px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/2-0\/\">2. Causalidade e Experimentos<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/2-0\/2-1\/\">2.1. John Snow e a Bomba da Broad Street<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/2-0\/2-2\/\">2.2. O &#8220;Grande Experimento&#8221; de Snow<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/2-0\/2-3\/\">2.3. Estabelecendo Causalidade<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/2-0\/2-4\/\">2.4. Randomiza\u00e7\u00e3o<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/2-0\/2-5\/\">2.5. Notas Finais<\/a><\/li>\n<\/ul>\n<\/li>\n<li style=\"margin-bottom: 5px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/3-0\/\">3. Progamando em Python<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/3-0\/3-1\/\">3.1. Express\u00f5es<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/3-0\/3-2\/\">3.2. Nomes<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/3-0\/3-2\/2-1\/\">3.2.1. Exemplo: Taxas de Crescimento<\/a><\/li>\n<\/ul>\n<\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/3-0\/3-3\/\">3.3. Chamadas<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/3-0\/3-4\/\">3.4. Introdu\u00e7\u00e3o \u00e0s Tabelas<\/a><\/li>\n<\/ul>\n<\/li>\n<li style=\"margin-bottom: 5px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/4-0\/\">4. Tipos de Dados<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/4-0\/4-1\/\">4.1. N\u00fameros<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/4-0\/4-2\/\">4.2. Strings<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/4-0\/4-2\/2-1\/\">4.2.1. M\u00e9todos de Strings<\/a><\/li>\n<\/ul>\n<\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/4-0\/4-3\/\">4.3. Compara\u00e7\u00f5es<\/a><\/li>\n<\/ul>\n<\/li>\n<li style=\"margin-bottom: 5px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/5-0\/\">5. Sequ\u00eancias<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/5-0\/5-1\/\">5.1. Arrays<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/5-0\/5-2\/\">5.2. Ranges<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/5-0\/5-3\/\">5.3. Mais sobre Arrays<\/a><\/li>\n<\/ul>\n<\/li>\n<li style=\"margin-bottom: 5px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/6-0\/\">6. Tabelas<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/6-0\/6-1\/\">6.1. Ordenando Linhas<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/6-0\/6-2\/\">6.2. Selecionando Linhas<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/6-0\/6-3\/\">6.3. Exemplo: Tend\u00eancias Populacionais<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/6-0\/6-4\/\">6.4. Examplo: Propor\u00e7\u00f5es de Sexos<\/a><\/li>\n<\/ul>\n<\/li>\n<li style=\"margin-bottom: 5px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/7-0\/\">7. Visualiza\u00e7\u00e3o<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/7-0\/7-1\/\">7.1. Visualizando Distribui\u00e7\u00f5es<br \/>\nCateg\u00f3ricas<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/7-0\/7-2\/\">7.2. Visualizando Distribui\u00e7\u00f5es Num\u00e9ricas<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/7-0\/7-3\/\">7.3. Gr\u00e1ficos Sobrepostos<\/a><\/li>\n<\/ul>\n<\/li>\n<li style=\"margin-bottom: 5px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/8-0\/\">8. Fun\u00e7\u00f5es e Tabelas<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/8-0\/8-1\/\">8.1. Aplicando Fun\u00e7\u00e3o a uma Coluna<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/8-0\/8-2\/\">8.2. Classificando por uma Vari\u00e1vel<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/8-0\/8-3\/\">8.3. Classifica\u00e7\u00e3o Cruzada<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/8-0\/8-4\/\">8.4. Unindo Tabelas por Colunas<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/8-0\/8-5\/\">8.5. Compartilhamento de Bicicletas<\/a><\/li>\n<\/ul>\n<\/li>\n<li style=\"margin-bottom: 5px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/9-0\/\">9. Aleatoriedade<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/9-0\/9-1\/\">9.1. Declara\u00e7\u00f5es Condicionais<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/9-0\/9-2\/\">9.2. Itera\u00e7\u00e3o<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/9-0\/9-3\/\">9.3. Simula\u00e7\u00e3o<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/9-0\/9-4\/\">9.4. O Problema de Monty Hall<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/9-0\/9-5\/\">9.5. Encontrando Probabilidades<\/a><\/li>\n<\/ul>\n<\/li>\n<li style=\"margin-bottom: 5px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/10-0\/\">10. Amostragem e Distribui\u00e7\u00f5es Emp\u00edricas<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/10-0\/10-1\/\">10.1. Distribui\u00e7\u00f5es Emp\u00edricas<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/10-0\/10-2\/\">10.2. Amostragem de uma Popula\u00e7\u00e3o<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/10-0\/10-3\/\">10.3. Distribui\u00e7\u00e3o Emp\u00edrica de uma<br \/>\nEstat\u00edstica<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/10-0\/10-4\/\">10.4. Amostragem Aleat\u00f3ria em Python <\/a><\/li>\n<\/ul>\n<\/li>\n<li style=\"margin-bottom: 5px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/11-0\/\">11. Testando Hip\u00f3teses<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/11-0\/11-1\/\">11.1. Avaliando um Modelo<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/11-0\/11-2\/\">11.2. M\u00faltiplas Categorias<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/11-0\/11-3\/\">11.3. Decis\u00f5es e Incertezas<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/11-0\/11-4\/\">11.4. Probabilidades de Erro<\/a><\/li>\n<\/ul>\n<\/li>\n<li style=\"margin-bottom: 5px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/12-0\/\">12. Comparando Duas Amostras<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/12-0\/12-1\/\">12.1. Teste A\/B<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/12-0\/12-2\/\">12.2. Causalidade<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/12-0\/12-3\/\">12.3. Esvaziar<\/a><\/li>\n<\/ul>\n<\/li>\n<li style=\"margin-bottom: 5px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/13-0\/\">13. Estima\u00e7\u00e3o<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/13-0\/13-1\/\">13.1. Percentis<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/13-0\/13-2\/\">13.2. O Bootstrap<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/13-0\/13-3\/\">13.3. Intervalos de Confian\u00e7a<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/13-0\/13-4\/\">13.4. Usando Intervalos de Confian\u00e7a<\/a><\/li>\n<\/ul>\n<\/li>\n<li style=\"margin-bottom: 5px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/14-0\/\">14. Por que a M\u00e9dia \u00e9 Importante<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/14-0\/14-1\/\">14.1. Propriedades da M\u00e9dia<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/14-0\/14-2\/\">14.2. Variabilidade<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/14-0\/14-3\/\">14.3. O DP e a Curva Normal<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/14-0\/14-4\/\">14.4. Teorema Central do Limite<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/14-0\/14-5\/\">14.5. Variabilidade da M\u00e9dia da Amostra<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/14-0\/14-6\/\">14.6. Escolhendo um Tamanho de Amostra<\/a><\/li>\n<\/ul>\n<\/li>\n<li style=\"margin-bottom: 5px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/15-0\/\">15. Previs\u00e3o<\/a>\n<ul style=\"margin: 5px 0 5px 15px;padding-left: 10px;list-style-type: none;border-left: 1px solid #ddd\">\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/15-0\/15-1\/\">15.1. Correla\u00e7\u00e3o<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/15-0\/15-2\/\">15.2. Linha de Regress\u00e3o<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/15-0\/15-3\/\">15.3. M\u00e9todo dos M\u00ednimos Quadrados<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/15-0\/15-4\/\">15.4. Regress\u00e3o de M\u00ednimos Quadrados<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/15-0\/15-5\/\">15.5. Diagn\u00f3sticos Visuais<\/a><\/li>\n<li style=\"margin-bottom: 3px\"><a style=\"padding: 2px 0\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/15-0\/15-6\/\">15.6. Diagn\u00f3stico Num\u00e9rico<\/a><\/li>\n<\/ul>\n<\/li>\n<\/ol>\n<\/div>\n<p><!-- Main Content --><\/p>\n<div style=\"overflow: hidden\">\n<p><!--###########################################################################################################################################################--><\/p>\n<pre><code><span style=\"color: black\">from datascience import *\r\npath_data = '..\/..\/assets\/data\/'\r\nimport numpy as np\r\nimport matplotlib.pyplot as plots\r\nplots.style.use('fivethirtyeight')\r\n%matplotlib inline<\/span><\/code><\/pre>\n<p>&nbsp;<\/p>\n<h1 id=\"amostragem-e-distribuicoes-empiricas\" style=\"text-align: center\">Amostragem e Distribui\u00e7\u00f5es Emp\u00edricas<\/h1>\n<p style=\"text-align: justify\">Uma parte importante da ci\u00eancia de dados consiste em tirar conclus\u00f5es baseadas nos dados de amostras aleat\u00f3rias. Para interpretar corretamente seus resultados, os cientistas de dados precisam primeiro entender exatamente o que s\u00e3o amostras aleat\u00f3rias.<\/p>\n<p style=\"text-align: justify\">Neste cap\u00edtulo, vamos examinar mais atentamente a amostragem, com aten\u00e7\u00e3o especial \u00e0s propriedades de grandes amostras aleat\u00f3rias.<\/p>\n<p style=\"text-align: justify\">Vamos come\u00e7ar tirando algumas amostras. Nossos exemplos s\u00e3o baseados no conjunto de dados <a href=\"https:\/\/inferentialthinking.com\/chapters\/07\/1\/Visualizing_Categorical_Distributions.html#grouping-categorical-data\">top_movies_2017.csv<\/a>.<\/p>\n<pre><code><span style=\"color: black\">top1 = Table.read_table(path_data + 'top_movies_2017.csv')\r\ntop2 = top1.with_column('Row Index', np.arange(top1.num_rows))\r\ntop = top2.move_to_start('Row Index')\r\n\r\ntop.set_format(make_array(3, 4), NumberFormatter)<\/span><\/code><\/pre>\n<table style=\"font-family: monospace;border-collapse: collapse;width: auto;margin-left: 1em\" border=\"1\">\n<thead>\n<tr style=\"background-color: #f0f0f0;border-bottom: 2px solid #ddd\">\n<th style=\"text-align: left;padding: 4px 8px\">Row Index<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">Title<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">Studio<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">Gross<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">Gross (Adjusted)<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">Year<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">0<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Gone with the Wind<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">MGM<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">198,676,459<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1,796,176,700<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1939<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Star Wars<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Fox<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">460,998,007<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1,583,483,200<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1977<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">The Sound of Music<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Fox<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">158,671,368<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1,266,072,700<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1965<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">3<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">E.T.: The Extra-Terrestrial<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Universal<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">435,110,554<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1,261,085,000<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1982<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">4<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Titanic<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Paramount<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">658,672,302<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1,204,368,000<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1997<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">5<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">The Ten Commandments<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Paramount<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">65,500,000<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1,164,590,000<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1956<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">6<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Jaws<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Universal<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">260,000,000<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1,138,620,700<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1975<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">7<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Doctor Zhivago<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">MGM<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">111,721,910<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1,103,564,200<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1965<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">8<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">The Exorcist<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Warner Brothers<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">232,906,145<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">983,226,600<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1973<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">9<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Snow White and the Seven Dwarves<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Disney<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">184,925,486<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">969,010,000<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1937<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<\/p>\n<h2>Amostragem de Linhas de uma Tabela<\/h2>\n<p style=\"text-align: justify\">Cada linha de uma tabela de dados representa um indiv\u00edduo; em <code>top<\/code>, cada indiv\u00edduo \u00e9 um filme. A amostragem de indiv\u00edduos pode, portanto, ser realizada pela amostragem das linhas de uma tabela.<\/p>\n<p style=\"text-align: justify\">O conte\u00fado de uma linha s\u00e3o os valores de diferentes vari\u00e1veis medidas no mesmo indiv\u00edduo. Portanto, os conte\u00fados das linhas amostradas formam amostras de valores de cada uma das vari\u00e1veis.<\/p>\n<h2>Amostras Determin\u00edsticas<\/h2>\n<p style=\"text-align: justify\">Quando voc\u00ea simplesmente especifica quais elementos de um conjunto deseja escolher, sem envolver quaisquer chances, voc\u00ea cria uma <em>amostra determin\u00edstica<\/em>.<\/p>\n<p style=\"text-align: justify\">Voc\u00ea j\u00e1 fez isso muitas vezes, por exemplo, usando <code>take<\/code>:<\/p>\n<pre><code><span style=\"color: black\">top.take(make_array(3, 18, 100))<\/span><\/code><\/pre>\n<table style=\"font-family: monospace;border-collapse: collapse;width: auto;margin-left: 1em\" border=\"1\">\n<thead>\n<tr style=\"background-color: #f0f0f0;border-bottom: 2px solid #ddd\">\n<th style=\"text-align: left;padding: 4px 8px\">Row Index<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">Title<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">Studio<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">Gross<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">Gross (Adjusted)<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">Year<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">3<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">E.T.: The Extra-Terrestrial<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Universal<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">435,110,554<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1,261,085,000<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1982<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">18<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">The Lion King<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Buena Vista<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">422,783,777<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">792,511,700<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1994<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">100<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">The Hunger Games<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Lionsgate<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">408,010,692<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">452,174,400<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2012<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<\/p>\n<p style=\"text-align: justify\">Voc\u00ea tamb\u00e9m usou <code>where<\/code>:<\/p>\n<pre><code><span style=\"color: black\">top.where('Title', are.containing('Harry Potter'))<\/span><\/code><\/pre>\n<table style=\"font-family: monospace;border-collapse: collapse;width: auto;margin-left: 1em\" border=\"1\">\n<thead>\n<tr style=\"background-color: #f0f0f0;border-bottom: 2px solid #ddd\">\n<th style=\"text-align: left;padding: 4px 8px\">Row Index<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">Title<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">Studio<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">Gross<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">Gross (Adjusted)<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">Year<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">74<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Harry Potter and the Sorcerer&#8217;s Stone<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Warner Brothers<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">317,575,550<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">497,066,400<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2001<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">114<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Harry Potter and the Deathly Hallows Part 2<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Warner Brothers<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">381,011,219<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">426,630,300<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2011<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">131<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Harry Potter and the Goblet of Fire<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Warner Brothers<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">290,013,036<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">401,608,200<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2005<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">133<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Harry Potter and the Chamber of Secrets<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Warner Brothers<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">261,988,482<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">399,302,200<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2002<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">154<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Harry Potter and the Order of the Phoenix<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Warner Brothers<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">292,004,738<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">377,314,200<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2007<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">175<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Harry Potter and the Half-Blood Prince<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Warner Brothers<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">301,959,197<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">359,788,300<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2009<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">177<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Harry Potter and the Prisoner of Azkaban<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Warner Brothers<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">249,541,069<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">357,233,500<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2004<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<\/p>\n<p style=\"text-align: justify\">Embora sejam amostras, n\u00e3o s\u00e3o amostras aleat\u00f3rias. N\u00e3o envolvem acaso.<\/p>\n<h2>Amostras de Probabilidade<\/h2>\n<p>Para descrever amostras aleat\u00f3rias, alguma terminologia ser\u00e1 \u00fatil.<\/p>\n<p>Uma <em>popula\u00e7\u00e3o<\/em> \u00e9 o conjunto de todos os elementos dos quais uma amostra ser\u00e1 retirada.<\/p>\n<p>Uma <em>amostra probabil\u00edstica<\/em> \u00e9 aquela para a qual \u00e9 poss\u00edvel calcular, antes de ser retirada, a probabilidade com que qualquer subconjunto de elementos entrar\u00e1 na amostra.<\/p>\n<p>Em uma amostra probabil\u00edstica, todos os elementos n\u00e3o precisam ter a mesma chance de serem escolhidos.<\/p>\n<h2>Um Esquema de Amostragem Aleat\u00f3ria<\/h2>\n<p>Por exemplo, suponha que voc\u00ea escolha duas pessoas de uma popula\u00e7\u00e3o que consiste em tr\u00eas pessoas A, B e C, de acordo com o seguinte esquema:<\/p>\n<ul>\n<li>A pessoa A \u00e9 escolhida com probabilidade 1.<\/li>\n<li>Uma das pessoas B ou C \u00e9 escolhida de acordo com o lan\u00e7amento de uma moeda: se a moeda cair em cara, voc\u00ea escolhe B, e se cair em coroa voc\u00ea escolhe C.<\/li>\n<\/ul>\n<p>Esta \u00e9 uma amostra probabil\u00edstica de tamanho 2. Aqui est\u00e3o as chances de entrada para todos os subconjuntos n\u00e3o vazios:<\/p>\n<pre><code><span class=\"hljs-symbol\">A:<\/span> <span class=\"hljs-number\">1<\/span>\r\n<span class=\"hljs-symbol\">B:<\/span> <span class=\"hljs-number\">1<\/span>\/<span class=\"hljs-number\">2<\/span>\r\n<span class=\"hljs-symbol\">C:<\/span> <span class=\"hljs-number\">1<\/span>\/<span class=\"hljs-number\">2<\/span>\r\n<span class=\"hljs-symbol\">AB:<\/span> <span class=\"hljs-number\">1<\/span>\/<span class=\"hljs-number\">2<\/span>\r\n<span class=\"hljs-symbol\">AC:<\/span> <span class=\"hljs-number\">1<\/span>\/<span class=\"hljs-number\">2<\/span>\r\n<span class=\"hljs-symbol\">BC:<\/span> <span class=\"hljs-number\">0<\/span>\r\n<span class=\"hljs-symbol\">ABC:<\/span> <span class=\"hljs-number\">0<\/span>\r\n<\/code><\/pre>\n<p>&nbsp;<\/p>\n<p>A pessoa A tem uma chance maior de ser selecionada do que as pessoas B ou C; de fato, a pessoa A certamente ser\u00e1 selecionada. Como essas diferen\u00e7as s\u00e3o conhecidas e quantificadas, elas podem ser levadas em conta ao trabalhar com a amostra.<\/p>\n<h2>Uma Amostra Sistem\u00e1tica<\/h2>\n<p>Imagine todos os elementos da popula\u00e7\u00e3o listados em uma sequ\u00eancia. Um m\u00e9todo de amostragem come\u00e7a escolhendo uma posi\u00e7\u00e3o aleat\u00f3ria no in\u00edcio da lista e, em seguida, posi\u00e7\u00f5es uniformemente espa\u00e7adas depois disso. A amostra consiste nos elementos dessas posi\u00e7\u00f5es. Tal amostra \u00e9 chamada de <em>amostra sistem\u00e1tica<\/em>.<\/p>\n<p>Aqui escolheremos uma amostra sistem\u00e1tica das linhas de <code>top<\/code>. Come\u00e7aremos escolhendo uma das primeiras 10 linhas aleatoriamente e, em seguida, escolheremos a cada 10\u00aa linha ap\u00f3s isso.<\/p>\n<pre><code><span style=\"color: black\">\"\"\"Escolha um in\u00edcio aleat\u00f3rio entre as linhas 0 a 9;\r\nent\u00e3o pegue cada 10\u00aa linha.\"\"\"\r\n\r\nstart = np.random.choice(np.arange(10))\r\ntop.take(np.arange(start, top.num_rows, 10))<\/span><\/code><\/pre>\n<table style=\"font-family: monospace;border-collapse: collapse;width: auto;margin-left: 1em\" border=\"1\">\n<thead>\n<tr style=\"background-color: #f0f0f0;border-bottom: 2px solid #ddd\">\n<th style=\"text-align: left;padding: 4px 8px\">Row Index<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">Title<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">Studio<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">Gross<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">Gross (Adjusted)<\/th>\n<th style=\"text-align: left;padding: 4px 8px\">Year<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">6<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Jaws<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Universal<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">260,000,000<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1,138,620,700<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1975<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">16<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Jurassic Park<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Universal<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">402,453,882<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">817,186,200<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1993<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">26<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Mary Poppins<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Disney<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">102,272,727<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">695,036,400<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1964<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">36<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Love Story<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Paramount<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">106,397,186<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">622,283,500<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1970<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">46<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">The Robe<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Fox<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">36,000,000<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">581,890,900<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1953<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">56<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Rogue One: A Star Wars Story<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Buena Vista<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">532,177,324<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">537,326,000<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2016<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">66<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">The Dark Knight Rises<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Warner Brothers<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">448,139,099<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">511,902,300<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2012<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">76<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Close Encounters of the Third Kind<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Columbia<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">132,088,635<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">494,066,600<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">1977<\/td>\n<\/tr>\n<tr>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">86<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Transformers: Revenge of the Fallen<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Paramount\/Dreamworks<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">402,111,870<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">479,179,200<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2009<\/td>\n<\/tr>\n<tr style=\"background-color: #f8f8f8\">\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">96<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Toy Story 3<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">Buena Vista<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">415,004,880<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">464,074,600<\/td>\n<td style=\"padding: 4px 8px;border: 1px solid #ddd\">2010<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<\/p>\n<p>Execute a c\u00e9lula algumas vezes para ver como a sa\u00edda varia.<\/p>\n<p>Esta amostra sistem\u00e1tica \u00e9 uma amostra probabil\u00edstica. Neste esquema, todas as linhas t\u00eam chance $1\/10$ de serem escolhidas. Por exemplo, a Linha 23 \u00e9 escolhida se e somente se a Linha 3 for escolhida, e a chance disso \u00e9 $1\/10$.<\/p>\n<p>Mas nem todos os subconjuntos t\u00eam a mesma chance de serem escolhidos. Como as linhas selecionadas est\u00e3o espa\u00e7adas uniformemente, a maioria dos subconjuntos de linhas n\u00e3o tem chance de serem escolhidos. Os \u00fanicos subconjuntos que s\u00e3o poss\u00edveis s\u00e3o aqueles que consistem em linhas separadas por m\u00faltiplos de 10. Qualquer um desses subconjuntos \u00e9 selecionado com chance de 1\/10. Outros subconjuntos, como um subconjunto contendo tanto a 15\u00aa quanto a 16\u00aa linha da tabela, ou qualquer<br \/>\nsubconjunto de tamanho superior a 10, s\u00e3o selecionados com chance 0.<\/p>\n<h2>Amostras Aleat\u00f3rias Com ou Sem Reposi\u00e7\u00e3o<\/h2>\n<p>Neste curso, lidaremos principalmente com os dois m\u00e9todos mais diretos de amostragem.<\/p>\n<p>O primeiro \u00e9 a amostragem aleat\u00f3ria com reposi\u00e7\u00e3o, que (como vimos anteriormente) \u00e9 o comportamento padr\u00e3o de <code>np.random.choice<\/code> ao amostrar de uma matriz.<\/p>\n<p>O outro, chamado de &#8220;amostra aleat\u00f3ria simples&#8221;, \u00e9 uma amostra retirada aleatoriamente <em>sem<\/em> reposi\u00e7\u00e3o. Indiv\u00edduos amostrados n\u00e3o s\u00e3o substitu\u00eddos na popula\u00e7\u00e3o antes que o pr\u00f3ximo indiv\u00edduo seja selecionado. Este \u00e9 o tipo de amostragem que ocorre ao lidar uma m\u00e3o de um baralho de cartas, por exemplo. Para usar <code>np.random.choice<\/code> para amostragem aleat\u00f3ria simples, voc\u00ea deve incluir o argumento <code>replace=False<\/code>.<\/p>\n<p>Neste cap\u00edtulo, usaremos simula\u00e7\u00e3o para estudar o comportamento de amostras grandes retiradas aleatoriamente com ou sem reposi\u00e7\u00e3o.<\/p>\n<h2>Amostras de Conveni\u00eancia<\/h2>\n<p>Desenhar uma amostra aleat\u00f3ria requer cuidado e precis\u00e3o. N\u00e3o \u00e9 aleat\u00f3rio, embora esse seja um significado coloquial da palavra &#8220;aleat\u00f3rio&#8221;. Se voc\u00ea ficar em uma esquina e tomar como amostra as primeiras dez pessoas que passam, voc\u00ea pode pensar que est\u00e1 fazendo uma amostragem aleat\u00f3ria porque n\u00e3o escolheu quem passou por ali. Mas n\u00e3o \u00e9 uma amostra aleat\u00f3ria \u2013 \u00e9 uma <em>amostra de conveni\u00eancia<\/em>. Voc\u00ea n\u00e3o sabia antecipadamente a probabilidade de cada pessoa entrar na amostra;<br \/>\ntalvez voc\u00ea nem tenha especificado exatamente quem estava na popula\u00e7\u00e3o.<\/p>\n<p><!--###########################################################################################################################################################--><\/p>\n<table width=\"100%\">\n<tbody>\n<tr>\n<td align=\"left\"><a class=\"next-page-link\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/9-0\/9-5\/\">\u2190 Cap\u00edtulo 9.5 &#8211; Encontrando Probabilidades<\/a><\/td>\n<td align=\"right\"><a class=\"next-page-link\" href=\"https:\/\/literaciadigital.ufms.br\/data8\/10-0\/10-1\/\">Cap\u00edtulo 10.1 &#8211; Distribui\u00e7\u00f5es Emp\u00edricas \u2192<\/a><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p><!--###########################################################################################################################################################--><\/p>\n<\/div>\n<\/div>\n<div style=\"clear: both;height: 1px;margin-top: -1px\"><\/div>\n","protected":false},"excerpt":{"rendered":"<p>\u00cdndice 1. O que \u00e9 Ci\u00eancia de Dados? 1.1. Introdu\u00e7\u00e3o 1.1.1. Ferramentas Computacionais 1.1.2. T\u00e9cnicas Estat\u00edsticas 1.2. Por que Ci\u00eancia de Dados? 1.3. Tra\u00e7ando os Cl\u00e1ssicos 1.3.1. Personagens Liter\u00e1rios 1.3.2. Outro Tipo de Personagem 2. Causalidade e Experimentos 2.1. John Snow e a Bomba da Broad Street 2.2. O &#8220;Grande Experimento&#8221; de Snow 2.3. Estabelecendo [&hellip;]<\/p>\n","protected":false},"author":21894,"featured_media":0,"parent":141,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"page-templates\/full-width.php","meta":{"footnotes":""},"coauthors":[14],"class_list":["post-611","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/literaciadigital.ufms.br\/en\/wp-json\/wp\/v2\/pages\/611","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/literaciadigital.ufms.br\/en\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/literaciadigital.ufms.br\/en\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/literaciadigital.ufms.br\/en\/wp-json\/wp\/v2\/users\/21894"}],"replies":[{"embeddable":true,"href":"https:\/\/literaciadigital.ufms.br\/en\/wp-json\/wp\/v2\/comments?post=611"}],"version-history":[{"count":1,"href":"https:\/\/literaciadigital.ufms.br\/en\/wp-json\/wp\/v2\/pages\/611\/revisions"}],"predecessor-version":[{"id":612,"href":"https:\/\/literaciadigital.ufms.br\/en\/wp-json\/wp\/v2\/pages\/611\/revisions\/612"}],"up":[{"embeddable":true,"href":"https:\/\/literaciadigital.ufms.br\/en\/wp-json\/wp\/v2\/pages\/141"}],"wp:attachment":[{"href":"https:\/\/literaciadigital.ufms.br\/en\/wp-json\/wp\/v2\/media?parent=611"}],"wp:term":[{"taxonomy":"author","embeddable":true,"href":"https:\/\/literaciadigital.ufms.br\/en\/wp-json\/wp\/v2\/coauthors?post=611"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}