{"id":2748,"date":"2023-06-02T10:30:44","date_gmt":"2023-06-02T07:30:44","guid":{"rendered":"https:\/\/www.ba.ihu.gr\/?post_type=course&#038;p=2748"},"modified":"2023-09-27T10:38:36","modified_gmt":"2023-09-27T07:38:36","slug":"202","status":"publish","type":"course","link":"https:\/\/www.ba.ihu.gr\/en\/courses\/202\/","title":{"rendered":"Statistics \u0399\u0399"},"author":6,"template":"","meta":[],"semester":[11],"course_type":[12],"acf":{"code":"202","semester":[11],"level":"1","teaching_activities":{"activity_1":{"description":"Lectures and Practice\/Exercises","weekly_hrs":4,"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":12,"language":"Greek","erasmus":"\u038c\u03c7\u03b9","url":"https:\/\/elearning.cm.ihu.gr\/course\/view.php?id=415","prerequisites":"","instructors":[1478],"coordinator":"","content":"<ul>\r\n \t<li>Hypothesis Tests: The process and stages of testing a statistical hypothesis. Types of error when testing a statistical hypothesis the p-value. Basic Statistical Hypothesis Testing Hypothesis testing, one sided or two sided testing, hypothesis testing of mean, binomial proportion, variance. Hypothesis testing of difference of population means, difference of population proportions, two population variances, computer applications.<\/li>\r\n \t<li>Non-Parametric Procedures: Goodness of fit test for Normal distribution, Binomial distribution, Poisson distribution.<\/li>\r\n \t<li>Relevance test with the X2 criterion, homogeneity test, computer applications.<\/li>\r\n \t<li>Correlation: Pearson's and Spearman's correlation coefficients, hypothesis tests for association in a statistical population.<\/li>\r\n \t<li>Regression \u2013 Correlation: Concept of regression-correlation, scatterplot, estimation of a simple linear regression model by the simple least squares (OLS) method, statistical significance testing of regression coefficients. Analysis of variance in the bivariate model, correlation coefficient, coefficient of determination, computer applications, simple predictions.<\/li>\r\n<\/ul>","goals":"In Business Administration statistical methods are important tools for information analysis, business decision making, applied research and economic policy making. In particular, the course introduces students to hypothesis testing, comparison of parameters in two populations, observed level of statistical significance (p-value), determination of sample size, analysis of variance, non-parametric procedures, simple linear regression \u2013 correlation.\r\n\r\nUpon successful completion of the course, the student should be able to:\r\n<ul>\r\n \t<li>select a scientific sample,<\/li>\r\n \t<li>conclusions about the properties of a population using samples,<\/li>\r\n \t<li>draw conclusions about the properties of two populations using samples,<\/li>\r\n \t<li>test the existence of a correlation between two characteristics of a population,<\/li>\r\n \t<li>use the SPSS statistical package for data analysis to draw conclusions and make scientifically based decisions.<\/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","workload":39},"activity_2":{"description":"Practice\/Exercises","workload":13},"activity_3":{"description":"Laboratory Exercises","workload":10},"activity_4":{"description":"Assignment","workload":10},"activity_5":{"description":"Personal Study","workload":53},"activity_6":{"description":"","workload":""}},"students_evaluation":"to be filled","bib_textbooks":"<ul>\r\n \t<li>\u03a0\u03bb\u03bf\u03c5\u03bc\u03af\u03b4\u03b7\u03c2, \u039a. (2014). \u00ab\u03a3\u03a4\u0391\u03a4\u0399\u03a3\u03a4\u0399\u039a\u0397 \u0395\u03a0\u0399\u03a7\u0395\u0399\u03a1\u0397\u03a3\u0395\u03a9\u039d, \u03a0\u03b5\u03c1\u03b9\u03b3\u03c1\u03b1\u03c6\u03b9\u03ba\u03ae &amp; \u0395\u03c0\u03b1\u03b3\u03c9\u03b3\u03b9\u03ba\u03ae\u00bb. 2<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\u03c7\u03ad\u03b4\u03c9\u03c1\u03bf\u03c2.<\/li>\r\n \t<li>\u03a3\u03b1\u03c1\u03b9\u03b1\u03bd\u03bd\u03af\u03b4\u03b7\u03c2, N. \u03ba\u03b1\u03b9 \u0393. \u039a\u03bf\u03bd\u03c4\u03ad\u03bf\u03c2 (2016). \u00ab\u0395\u03b9\u03c3\u03b1\u03b3\u03c9\u03b3\u03ae \u03c3\u03c4\u03b7 \u03c3\u03c4\u03b1\u03c4\u03b9\u03c3\u03c4\u03b9\u03ba\u03ae\u00bb. \u039a\u03bf\u03b6\u03ac\u03bd\u03b7: \u0395\u03ba\u03b4\u03cc\u03c4\u03b7\u03c2 \u0393\u03b5\u03ce\u03c1\u03b3\u03b9\u03bf\u03c2 \u039a\u03bf\u03bd\u03c4\u03ad\u03bf\u03c2.<\/li>\r\n \t<li>\u03a7\u03b1\u03bb\u03b9\u03ba\u03b9\u03ac\u03c2, \u0399. (2010). \u00ab\u03a3\u03a4\u0391\u03a4\u0399\u03a3\u03a4\u0399\u039a\u0397 - \u039c\u03ad\u03b8\u03bf\u03b4\u03bf\u03b9 \u0391\u03bd\u03ac\u03bb\u03c5\u03c3\u03b7\u03c2 \u03b3\u03b9\u03b1 \u0395\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03b7\u03bc\u03b1\u03c4\u03b9\u03ba\u03ad\u03c2 \u0391\u03c0\u03bf\u03c6\u03ac\u03c3\u03b5\u03b9\u03c2\u00bb. 4\u03b7 \u03ad\u03ba\u03b4\u03bf\u03c3\u03b7. \u0391\u03b8\u03ae\u03bd\u03b1: \u0395\u03ba\u03b4\u03cc\u03c3\u03b5\u03b9\u03c2 Rosili.<\/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<\/ul>","bib_journals":""},"_links":{"self":[{"href":"https:\/\/www.ba.ihu.gr\/en\/wp-json\/wp\/v2\/course\/2748"}],"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":10,"href":"https:\/\/www.ba.ihu.gr\/en\/wp-json\/wp\/v2\/course\/2748\/revisions"}],"predecessor-version":[{"id":3867,"href":"https:\/\/www.ba.ihu.gr\/en\/wp-json\/wp\/v2\/course\/2748\/revisions\/3867"}],"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\/12"},{"embeddable":true,"taxonomy":"semester","href":"https:\/\/www.ba.ihu.gr\/en\/wp-json\/wp\/v2\/semester\/11"}],"wp:attachment":[{"href":"https:\/\/www.ba.ihu.gr\/en\/wp-json\/wp\/v2\/media?parent=2748"}],"wp:term":[{"taxonomy":"semester","embeddable":true,"href":"https:\/\/www.ba.ihu.gr\/en\/wp-json\/wp\/v2\/semester?post=2748"},{"taxonomy":"course_type","embeddable":true,"href":"https:\/\/www.ba.ihu.gr\/en\/wp-json\/wp\/v2\/course_type?post=2748"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}