{"id":8618,"date":"2022-04-28T21:15:15","date_gmt":"2022-04-28T21:15:15","guid":{"rendered":"https:\/\/www.tun.com\/courses\/2019\/12\/23\/inferential-statistical-analysis-with-python\/"},"modified":"2022-04-28T21:15:15","modified_gmt":"2022-04-28T21:15:15","slug":"inferential-statistical-analysis-with-python","status":"publish","type":"post","link":"https:\/\/www.tun.com\/courses\/inferential-statistical-analysis-with-python\/university-of-michigan\/","title":{"rendered":"Inferential Statistical Analysis with Python"},"content":{"rendered":"
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Description<\/h2>\n

In this course, we will explore basic principles behind using data for estimation and for assessing theories. We will analyze both categorical data and quantitative data, starting with one population techniques and expanding to handle comparisons of two populations. We will learn how to construct confidence intervals. We will also use sample data to assess whether or not a theory about the value of a parameter is consistent with the data. A major focus will be on interpreting inferential results appropriately. <\/p>\n

At the end of each week, learners will apply what they\u2019ve learned using Python within the course environment. During these lab-based sessions, learners will work through tutorials focusing on specific case studies to help solidify the week\u2019s statistical concepts, which will include further deep dives into Python libraries including Statsmodels, Pandas, and Seaborn. This course utilizes the Jupyter Notebook environment within Coursera.<\/p>\n

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Price: Enroll For Free!<\/h2>\n
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View Class<\/a><\/div>\n
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Language:<\/strong> <\/em>English<\/p>\n<\/div>\n

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Subtitles<\/strong>: <\/em>English, Korean<\/p>\n<\/div>\n<\/div>\n

Inferential Statistical Analysis with Python – University of Michigan<\/strong><\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

Description In this course, we will explore basic principles behind using data for estimation and for assessing theories. We will analyze both categorical data and quantitative data, starting with one population techniques and expanding to handle comparisons of two populations. We will learn how to construct confidence intervals. We will also use sample data to […]<\/p>\n","protected":false},"author":1,"featured_media":19411,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"om_disable_all_campaigns":false,"_uag_custom_page_level_css":"","_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_uf_show_specific_survey":0,"_uf_disable_surveys":false,"footnotes":""},"categories":[262],"tags":[],"class_list":["post-8618","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-university-of-michigan"],"aioseo_notices":[],"uagb_featured_image_src":{"full":["https:\/\/www.tun.com\/courses\/wp-content\/uploads\/2019\/12\/University-of-Michiganonline-education.png",378,224,false],"thumbnail":["https:\/\/www.tun.com\/courses\/wp-content\/uploads\/2019\/12\/University-of-Michiganonline-education-150x150.png",150,150,true],"medium":["https:\/\/www.tun.com\/courses\/wp-content\/uploads\/2019\/12\/University-of-Michiganonline-education-300x178.png",300,178,true],"medium_large":["https:\/\/www.tun.com\/courses\/wp-content\/uploads\/2019\/12\/University-of-Michiganonline-education.png",378,224,false],"large":["https:\/\/www.tun.com\/courses\/wp-content\/uploads\/2019\/12\/University-of-Michiganonline-education.png",378,224,false],"1536x1536":["https:\/\/www.tun.com\/courses\/wp-content\/uploads\/2019\/12\/University-of-Michiganonline-education.png",378,224,false],"2048x2048":["https:\/\/www.tun.com\/courses\/wp-content\/uploads\/2019\/12\/University-of-Michiganonline-education.png",378,224,false]},"uagb_author_info":{"display_name":"Axiom Pegasus","author_link":"https:\/\/www.tun.com\/courses\/author\/magic\/"},"uagb_comment_info":0,"uagb_excerpt":"Description In this course, we will explore basic principles behind using data for estimation and for assessing theories. We will analyze both categorical data and quantitative data, starting with one population techniques and expanding to handle comparisons of two populations. We will learn how to construct confidence intervals. We will also use sample data to…","featured_media_src_url":"https:\/\/www.tun.com\/courses\/wp-content\/uploads\/2019\/12\/University-of-Michiganonline-education.png","_links":{"self":[{"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/posts\/8618","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/comments?post=8618"}],"version-history":[{"count":0,"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/posts\/8618\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/media\/19411"}],"wp:attachment":[{"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/media?parent=8618"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/categories?post=8618"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/tags?post=8618"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}