{"id":3098,"date":"2023-06-08T13:07:42","date_gmt":"2023-06-08T10:07:42","guid":{"rendered":"https:\/\/www.ba.ihu.gr\/?post_type=course&#038;p=3098"},"modified":"2024-06-09T22:47:44","modified_gmt":"2024-06-09T19:47:44","slug":"%ce%b112","status":"publish","type":"course","link":"https:\/\/www.ba.ihu.gr\/en\/courses\/%ce%b112\/","title":{"rendered":"Topics in Applied Statistics"},"author":6,"template":"","meta":[],"semester":[68],"course_type":[14],"acf":{"code":"\u039112","semester":[68],"level":"1","teaching_activities":{"activity_1":{"description":"Lectures","weekly_hrs":3,"ects":5},"activity_2":{"description":"","weekly_hrs":"","ects":""},"activity_3":{"description":"","weekly_hrs":"","ects":""},"activity_4":{"description":"","weekly_hrs":"","ects":""},"activity_5":{"description":"","weekly_hrs":"","ects":""}},"type":14,"language":"Greek","erasmus":"\u038c\u03c7\u03b9","url":"https:\/\/elearning.cm.ihu.gr\/course\/view.php?id=883","prerequisites":"","instructors":[1478],"coordinator":"","content":"<ul>\r\n \t<li>Empirical models of behavior analysis in management and economics: Simple and multiple linear models. Least squares method. Rate estimation. Properties of estimated coefficients, hypothesis testing, data variance estimation. Expected prices. R^2, F test. Applications using statistical packages.<\/li>\r\n \t<li>Analysis of variance-covariance: Analysis of variance by a ranking criterion (factor)-Conditions for its application. Testing for equality of pairwise means (multiple comparisons of means) in one-criterion analysis of variance. Variation analysis according to two classification criteria (factors) - Conditions for its application. Testing for equality of pairwise means (multiple comparisons of means) in two-criteria analysis of variance. Choosing the best regression, forward, backward, stepwise methods, all possible regressions.<\/li>\r\n \t<li>Categorical data analysis: Types of categorical variables, 2x2 correlation matrices, measures of correlation in 2x2 and (rxc) correlation matrices. Linear regression with categorical independent variables.<\/li>\r\n \t<li>Nonparametric controls: Selection criteria and tradeoffs between parametric and nonparametric procedures. Hypothesis tests for 1 or 2 independent samples, hypothesis tests for 2 dependent samples, correlation tables. Basic non-parametric tests (the Wilcoxon test, the Mann-Whitney test, the Kruskal-Wallis test, etc.). Case studies and analysis of real data sets from various disciplines (Finance, Marketing, Social Sciences).<\/li>\r\n \t<li>Indicators and Official Statistics: Introduction, indicators, indicators, simple and complex figures, base, change of base, selection of items, applied indexes in Greece, consumer price indexes, wholesale sales, deflation, National Accounts-Sources of Statistics, Statistics of employment, unemployment and wages, family budget surveys.<\/li>\r\n<\/ul>","goals":"The course aims to acquaint the students with specific topics of statistical analysis. Upon successful completion of the course, the student should be able to:\r\n<ul>\r\n \t<li>estimate models with more than one independent variable,<\/li>\r\n \t<li>collect and analyze a set of quantitative or qualitative data,<\/li>\r\n \t<li>perform qualitative and quantitative analysis of primary or secondary data using statistical packages,<\/li>\r\n \t<li>estimate with the use of real statistical data any relationship that exists between these data,<\/li>\r\n \t<li>manage a large amount of data to investigate and solve economic, demographic, business problems,<\/li>\r\n \t<li>search and study the Greek and foreign literature regarding the topics they have been taught and to be able to write a comprehensive statistical paper.<\/li>\r\n<\/ul>","skills":"to be filled","teaching_methods":"<ul>\r\n \t<li>Face to face.<\/li>\r\n<\/ul>","ict_usage":"<ul>\r\n \t<li>Online guidance.<\/li>\r\n \t<li>Slides Projection in the classroom.<\/li>\r\n \t<li>Use of E-mail and onlne communication systems.<\/li>\r\n \t<li>Use of e-learning system (moodle).<\/li>\r\n<\/ul>","teaching_organization":{"activity_1":{"description":"Lectures \/ Exercises","workload":39},"activity_2":{"description":"Assignment(s)","workload":30},"activity_3":{"description":"Personal Study","workload":56},"activity_4":{"description":"","workload":""},"activity_5":{"description":"","workload":""},"activity_6":{"description":"","workload":""}},"students_evaluation":"to be filled","bib_textbooks":"<ol>\r\n \t<li>\u0393\u03bd\u03b1\u03c1\u03b4\u03ad\u03bb\u03b7\u03c2, X. (2019). \u00ab\u0395\u03c6\u03b1\u03c1\u03bc\u03bf\u03c3\u03bc\u03ad\u03bd\u03b7 \u03a3\u03c4\u03b1\u03c4\u03b9\u03c3\u03c4\u03b9\u03ba\u03ae\u00bb, \u0391\u03b8\u03ae\u03bd\u03b1: \u0395\u03ba\u03b4\u03cc\u03c3\u03b5\u03b9\u03c2 \u03a0\u03b1\u03c0\u03b1\u03b6\u03ae\u03c3\u03b7.<\/li>\r\n \t<li>\u0394\u03b7\u03bc\u03b7\u03c4\u03c1\u03b9\u03ac\u03b4\u03b7\u03c2, E. (2017). \u00ab\u03a3\u03a4\u0391\u03a4\u0399\u03a3\u03a4\u0399\u039a\u0397 \u0395\u03a0\u0399\u03a7\u0395\u0399\u03a1\u0397\u03a3\u0395\u03a9\u039d \u039c\u0395 \u0395\u03a6\u0391\u03a1\u039c\u039f\u0393\u0395\u03a3 \u03a3\u0395 SPSS \u039a\u0391\u0399 LISREL\u00bb. \u0391\u03b8\u03ae\u03bd\u03b1: \u0395\u03ba\u03b4\u03cc\u03c3\u03b5\u03b9\u03c2 \u039a\u03c1\u03b9\u03c4\u03b9\u03ba\u03ae.<\/li>\r\n \t<li>\u03a4\u03b6\u03c9\u03c1\u03c4\u03b6\u03cc\u03c0\u03bf\u03c5\u03bb\u03bf\u03c2, \u03a0. \u03ba\u03b1\u03b9 \u0391. \u039b\u03b5\u03b9\u03b2\u03b1\u03b4\u03ac (2012). \u00ab\u0391\u03a1\u0399\u0398\u039c\u039f\u0394\u0395\u0399\u039a\u03a4\u0395\u03a3 \u039a\u0391\u0399 \u0395\u03a0\u0399\u03a3\u0397\u039c\u0395\u03a3 \u03a3\u03a4\u0391\u03a4\u0399\u03a3\u03a4\u0399\u039a\u0395\u03a3\u00bb. \u0391\u03b8\u03ae\u03bd\u03b1: \u0395\u03ba\u03b4\u03cc\u03c3\u03b5\u03b9\u03c2 \u039f\u03b9\u03ba\u03bf\u03bd\u03bf\u03bc\u03b9\u03ba\u03cc \u03a0\u03b1\u03bd\u03b5\u03c0\u03b9\u03c3\u03c4\u03ae\u03bc\u03b9\u03bf \u0391\u03b8\u03b7\u03bd\u03ce\u03bd.<\/li>\r\n \t<li>Aczel, \u0391. \u03ba\u03b1\u03b9 Sounderpandian (2013). \u00ab\u03a3\u03c4\u03b1\u03c4\u03b9\u03c3\u03c4\u03b9\u03ba\u03ae \u03c3\u03ba\u03ad\u03c8\u03b7 \u03c3\u03c4\u03bf\u03bd \u03ba\u03cc\u03c3\u03bc\u03bf \u03c4\u03c9\u03bd \u03b5\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03ae\u03c3\u03b5\u03c9\u03bd\u00bb. \u039b\u03b5\u03c5\u03ba\u03c9\u03c3\u03af\u03b1: \u0395\u03ba\u03b4\u03cc\u03c3\u03b5\u03b9\u03c2 \u03b3\u03b9\u03b1 \u03c4\u03b7\u03bd \u03b5\u03bb\u03bb\u03b7\u03bd\u03b9\u03ba\u03ae \u03b3\u03bb\u03ce\u03c3\u03c3\u03b1 Broken Hill Publishers LTD.<\/li>\r\n \t<li>Field, A. (2016). \u00ab\u0397 \u0394\u03b9\u03b5\u03c1\u03b5\u03cd\u03bd\u03b7\u03c3\u03b7 \u03c4\u03b7\u03c2 \u03a3\u03c4\u03b1\u03c4\u03b9\u03c3\u03c4\u03b9\u03ba\u03ae\u03c2 \u03bc\u03b5 \u03c4\u03b7 \u03a7\u03c1\u03ae\u03c3\u03b7 \u03c4\u03bf\u03c5 SPSS \u03c4\u03b7\u03c2 IBM\u00bb. 1\u03b7 \u0395\u03bb\u03bb\u03b7\u03bd\u03b9\u03ba\u03ae \u03ad\u03ba\u03b4\u03bf\u03c3\u03b7 \u03b1\u03c0\u03cc \u03c4\u03b7\u03bd 4\u03b7 \u0391\u03b3\u03b3\u03bb\u03b9\u03ba\u03ae. \u0391\u03b8\u03ae\u03bd\u03b1: \u0395\u03ba\u03b4\u03cc\u03c3\u03b5\u03b9\u03c2 \u03a0\u03c1\u03bf\u03c0\u03bf\u03bc\u03c0\u03cc\u03c2.<\/li>\r\n \t<li>Keller, G. (2010). \u00ab\u03a3\u03c4\u03b1\u03c4\u03b9\u03c3\u03c4\u03b9\u03ba\u03ae \u03b3\u03b9\u03b1 \u039f\u03b9\u03ba\u03bf\u03bd\u03bf\u03bc\u03af\u03b1 &amp; \u0394\u03b9\u03bf\u03af\u03ba\u03b7\u03c3\u03b7 \u0395\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03ae\u03c3\u03b5\u03c9\u03bd\u00bb. 8<sup>\u03b7<\/sup> \u0388\u03ba\u03b4\u03bf\u03c3\u03b7. \u0398\u03b5\u03c3\u03c3\u03b1\u03bb\u03bf\u03bd\u03af\u03ba\u03b7: \u0395\u03ba\u03b4\u03cc\u03c3\u03b5\u03b9\u03c2 \u0395\u03c0\u03af\u03ba\u03b5\u03bd\u03c4\u03c1\u03bf.<\/li>\r\n<\/ol>","bib_journals":""},"_links":{"self":[{"href":"https:\/\/www.ba.ihu.gr\/en\/wp-json\/wp\/v2\/course\/3098"}],"collection":[{"href":"https:\/\/www.ba.ihu.gr\/en\/wp-json\/wp\/v2\/course"}],"about":[{"href":"https:\/\/www.ba.ihu.gr\/en\/wp-json\/wp\/v2\/types\/course"}],"author":[{"embeddable":true,"href":"https:\/\/www.ba.ihu.gr\/en\/wp-json\/wp\/v2\/users\/6"}],"version-history":[{"count":16,"href":"https:\/\/www.ba.ihu.gr\/en\/wp-json\/wp\/v2\/course\/3098\/revisions"}],"predecessor-version":[{"id":4501,"href":"https:\/\/www.ba.ihu.gr\/en\/wp-json\/wp\/v2\/course\/3098\/revisions\/4501"}],"acf:post":[{"embeddable":true,"href":"https:\/\/www.ba.ihu.gr\/en\/wp-json\/wp\/v2\/staff\/1478"}],"acf:term":[{"embeddable":true,"taxonomy":"course_type","href":"https:\/\/www.ba.ihu.gr\/en\/wp-json\/wp\/v2\/course_type\/14"},{"embeddable":true,"taxonomy":"semester","href":"https:\/\/www.ba.ihu.gr\/en\/wp-json\/wp\/v2\/semester\/68"}],"wp:attachment":[{"href":"https:\/\/www.ba.ihu.gr\/en\/wp-json\/wp\/v2\/media?parent=3098"}],"wp:term":[{"taxonomy":"semester","embeddable":true,"href":"https:\/\/www.ba.ihu.gr\/en\/wp-json\/wp\/v2\/semester?post=3098"},{"taxonomy":"course_type","embeddable":true,"href":"https:\/\/www.ba.ihu.gr\/en\/wp-json\/wp\/v2\/course_type?post=3098"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}