Statistical Data Analysis (MAE832): Διαφορά μεταξύ των αναθεωρήσεων
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=== General === | === General === | ||
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! Learning outcomes | ! Learning outcomes | ||
| | | | ||
In this course, various statistical methodologies are applied with the help of the computer and the use of statistical programs (SPSS, JASP, R). Emphasis is placed on choosing the appropriate statistical methodology and examining whether the assumptions of its application are met. | |||
|- | |- | ||
! General Competences | ! General Competences | ||
| Γραμμή 74: | Γραμμή 68: | ||
* Criticism and self-criticism. | * Criticism and self-criticism. | ||
|} | |} | ||
=== Syllabus === | === Syllabus === | ||
In this course, various statistical methodologies are applied with the help of the computer and the use of statistical programs (SPSS, JASP, R). | |||
Upon completion of the course, the student will be able to: | |||
# enter data into the computer | |||
# conduct descriptive statistical analysis, that is to summarize the available data, | |||
# conduct basic data analyzes (testing hypotheses concerning the mean of a population, the means of two populations with dependent and independent samples, one way analysis of variance etc.,) | |||
# fits simple-multiple linear regression models, binomial logistic regression models, checking whether the assumptions of their application are violated | |||
# applies basic methodologies of multidimensional analysis (clustering, factor analysis) | |||
# present the results of the above analyzes (reference report). | |||
=== Teaching and Learning Methods - Evaluation === | === Teaching and Learning Methods - Evaluation === | ||
{| class="wikitable" | {| class="wikitable" | ||
Τελευταία αναθεώρηση της 15:25, 16 Αυγούστου 2024
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General
| School |
School of Science |
|---|---|
| Academic Unit |
Department of Mathematics |
| Level of Studies |
Undergraduate |
| Course Code |
ΜΑΕ832 |
| Semester |
8 |
| Course Title |
Statistical Data Analysis |
| Independent Teaching Activities |
Lectures-Laboratory (Weekly Teaching Hours: 3, Credits: 6) |
| Course Type |
Special background |
| Prerequisite Courses | - |
| Language of Instruction and Examinations |
Greek |
| Is the Course Offered to Erasmus Students |
Yes (in English, reading Course) |
| Course Website (URL) | See eCourse, the Learning Management System maintained by the University of Ioannina. |
Learning Outcomes
| Learning outcomes |
In this course, various statistical methodologies are applied with the help of the computer and the use of statistical programs (SPSS, JASP, R). Emphasis is placed on choosing the appropriate statistical methodology and examining whether the assumptions of its application are met. |
|---|---|
| General Competences |
|
Syllabus
In this course, various statistical methodologies are applied with the help of the computer and the use of statistical programs (SPSS, JASP, R).
Upon completion of the course, the student will be able to:
- enter data into the computer
- conduct descriptive statistical analysis, that is to summarize the available data,
- conduct basic data analyzes (testing hypotheses concerning the mean of a population, the means of two populations with dependent and independent samples, one way analysis of variance etc.,)
- fits simple-multiple linear regression models, binomial logistic regression models, checking whether the assumptions of their application are violated
- applies basic methodologies of multidimensional analysis (clustering, factor analysis)
- present the results of the above analyzes (reference report).
Teaching and Learning Methods - Evaluation
| Delivery |
Classroom (face-to-face) | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Use of Information and Communications Technology | Use of ICT in communication with students | ||||||||||
| Teaching Methods |
| ||||||||||
| Student Performance Evaluation |
Final written exam in Greek (in case of Erasmus students in English) which concentrates on the solution of problems which are motivated by the main themes of the course. |
Attached Bibliography
See the official Eudoxus site or the local repository of Eudoxus lists per academic year, which is maintained by the Department of Mathematics. Books and other resources, not provided by Eudoxus:
- Andy Field. Η Διερεύνηση της Στατιστικής με τη χρήση του SPSS της IBM. Εκδόσεις Προπομπός
- Julie Pallant. SPSS Οδηγός ανάλυσης δεδομένων με το ΙΒΜ SPSS. Εκδόσεις Κλειδάριθμος ΕΠΕ.
- Δ. Φουσκάκης. Ανάλυση Δεδομένων με χρήση της R. Εκδόσεις Τσότρας Αν. Αθανάσιος
- Joaquim P. Marques de Sá. Applied Statistics Using SPSS, STATISTICA, MATLAB and R. Springer Berlin Heidelberg Διαθέτης (Εκδότης) HEAL-Link Springer ebooks
- Μαλεφάκη, Σ., Μπατσίδης, Α., & Οικονόμου, Π. (2023). Στατιστική Ανάλυση Δεδομένων [Προπτυχιακό εγχειρίδιο]. Κάλλιπος, Ανοικτές Ακαδημαϊκές Εκδόσεις.