{"id":35492,"date":"2025-04-12T19:51:45","date_gmt":"2025-04-12T17:51:45","guid":{"rendered":"https:\/\/mead.upatras.gr\/?post_type=courses&p=35492"},"modified":"2025-04-12T19:51:45","modified_gmt":"2025-04-12T17:51:45","slug":"experimental-data-analysis","status":"publish","type":"courses","link":"https:\/\/mead.upatras.gr\/en\/courses\/experimental-data-analysis\/","title":{"rendered":"\u0395xperimental Data Analysis"},"content":{"rendered":"

COURSE CONTENT<\/strong><\/p>\n

    \n
  1. Multivariate random variables<\/strong><\/li>\n
  2. Chi-square test<\/strong><\/li>\n<\/ol>\n

    Goodness of fit test, test of independence, test of Homogeneity, test for equality of several proportions<\/p>\n

      \n
    1. Simple and Multiple regression<\/strong><\/li>\n
    2. One way ANOVA and more<\/strong><\/li>\n
    3. Non parametric tests<\/strong><\/li>\n<\/ol>\n

      (Wilcoxon, Mann- Whitney, Kruskall \u2013 Wallis, Friedman tests)<\/p>\n

      LEARNING OUTCOMES<\/strong><\/p>\n

      In this course advanced statistical techniques for the analysis of experimental data are presented analytically. Moreover, the statistical package SpSS 21.0 is also presented.<\/p>\n

      The main purpose of the course is to familiarize students with statistical methods such as simple and multiple regression, analysis of variance and non-parametric tests which are very useful tools for engineers.<\/p>\n

      Upon successful completion of the course the student will be able to:<\/p>\n

        \n
      • Use regression models in order to describe the linear relationship between one dependent variable and one or more independent variables and also to predict the dependent variable based on the observations of the independent variables.<\/li>\n
      • Test for normality of the data and select the proper statistical test (parametric or non-parametric tests)<\/li>\n
      • Select and apply the proper statistical technique in order to extract useful results and conclusions<\/li>\n<\/ul>\n

        Use statistical package SpSS .<\/p>\n","protected":false},"featured_media":11551,"template":"","meta":{"_acf_changed":false},"msc_category":[],"courses_cat":[1691,1670],"class_list":["post-35492","courses","type-courses","status-publish","has-post-thumbnail","hentry","courses_cat-aeronautics-engineering-9th-semester-optional","courses_cat-mechanical-engineering-7th-semester-optional"],"acf":[],"yoast_head":"\n\u0395xperimental Data Analysis - MEAD<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/mead.upatras.gr\/en\/courses\/experimental-data-analysis\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\u0395xperimental Data Analysis - MEAD\" \/>\n<meta property=\"og:description\" content=\"COURSE CONTENT Multivariate random variables Chi-square test Goodness of fit [...]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/mead.upatras.gr\/en\/courses\/experimental-data-analysis\/\" \/>\n<meta property=\"og:site_name\" content=\"MEAD\" \/>\n<meta property=\"og:image\" content=\"https:\/\/mead.upatras.gr\/wp-content\/uploads\/2018\/10\/courses.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"1374\" \/>\n\t<meta property=\"og:image:height\" content=\"776\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/mead.upatras.gr\/en\/courses\/experimental-data-analysis\/\",\"url\":\"https:\/\/mead.upatras.gr\/en\/courses\/experimental-data-analysis\/\",\"name\":\"\u0395xperimental Data Analysis - 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