Learning Outcomes
After finishing the course, the student will be able to
A) Understand basic statistical concepts and methods of inferential statistics
B) Execute parametric tests and non-parametric tests
C) Acknowledge and manage problems of the sampling methods,
D) Solve problems of linear regression
E) Use further statistical software packages and tools for data analyses
Course Content (Syllabus)
Statistical Inference: Sampling, Estimation, Hypothesis Testing. Goodness of fit tests, tests for bivariate relationships. Simple linear regression.
Syllabus:
- Sampling methods and sampling distributions for the mean, variance, and proportion.
- Point and interval estimation for the mean, variance, and proportion.
- One sample tests of hypotheses for the mean, variance, and proportion.
- Univariate goodness of fit tests.
- Chi-square tests of independence in two-way contingency tables.
- Bivariate Pearson product moment and rank correlation coefficients. Hypothesis tests for bivariate correlation.
- Simple linear regression.
Keywords
Inference, estimation, hypothesis testing, correlation, regression.
Course Bibliography (Eudoxus)
Βιβλίο [22768741]: ΕΦΑΡΜΟΣΜΕΝΗ ΣΤΑΤΙΣΤΙΚΗ, ΤΑΜΠΑΚΗΣ ΝΙΚΟΛΑΟΣ, ΧΑΨΑ ΞΑΝΘΙΠΠΗ Λεπτομέρειες
Βιβλίο [59381285]: Εισαγωγή στη Στατιστική, Νικόλαος Σαριαννίδης, Γεώργιος Κοντέος Λεπτομέρειες
Βιβλίο [77120360]: ΣΤΑΤΙΣΤΙΚΗ ΤΟΜΟΣ Α', Ζ' ΕΚΔΟΣΗ, ΖΑΧΑΡΟΠΟΥΛΟΥ ΧΡΥΣΟΥΛΑ Λεπτομέρειες