Office Hours: By Appointment, 1st Floor.
Phone: +355 4 2441330
Statistics I course aims to cover all major aspects of the descriptive statistical and probability theory and their applications by using SPSS. There are many examples and problems concerning diverse application areas that will show the pertinence of statistical methodology to solving real-world problems. Descriptive statistics deals with methods of organizing, summarizing and presenting data in a convenient and informative way by using graphical or numerical techniques. The course provides a modern approach that emphasizes applications and how statistics is used in every business economics, economics or social sciences function. It aims in giving the students the foundations for continuing with inferential statistics. The course also gives the foundations of discrete probability theory.
Prerequisite: College Algebra or Visualizing Mathematics
The main purpose of Statistics I course is the collection, analysis, interpretation, and presentation of qualitative or numerical data for assisting in making more effective decisions. Every person in today’s society needs to have a basic understanding of data analysis and statistical concepts, in order to be able to think critically about the quantitative information we encounter every day, from opinion polls to headline news reports based on scientific studies. We need to be able to understand the information that is being presented and to ask the right questions about any conclusions that are drawn from it.
One of the main aims is to prepare undergraduate students in the theory of descriptive statistics with emphasis in interdisciplinary applications, in order to continue with inferential statistics. The usefulness of each statistical method introduced is illustrated by several relevant examples.
Upon completion of this course, students should be able to:
Identify the relevant population, sample, study units (subjects), variables, and factors.
The laboratory part of the course will provide students with hands-on experience with the SPSS. Students will be able to generate tabulated reports, charts and plots of distributions and trends, descriptive statistics and conduct some statistical analysis.
Content of the Course
Participation: Participation extends beyond mere attendance. Active participation is meant as the effort and the interest that a student shows in the class, including homework. After each session students are expected to study all the relevant material, read all the associated exercises, identify the difficult points and pose their questions in the next session either directly to me or in the class. You may miss up to three classes without penalty – your first two absences count whether you have a good excuse or not. The only exceptions to this rule are severe illness (doctor’s note required) and UNYT approved trips/activities. Appropriate documentation for absences beyond the first three is necessary the class day directly before or after the one you miss. In general: this class is intensive and interactive. Missing class could seriously affect your grade! Students who are absent more than 20% of the total hours of the semester (i.e. 9 hours) may be required to withdraw from the course.
Class conduct: Exams are closed books. Also, you use your own calculator and nothing else will be allowed. Mobile phones are strictly not tolerated in the class for any use (including computations). Cheating and plagiarism in any form will result immediately in the grade F.
Students are reminded not to approach the instructor for copies of the previous week’s materials during, or immediately after class. Students are expected to collect materials from their classmates or see the instructor during the office hours.
Students are responsible for everything that is announced, presented or discussed in class. The way to avoid any misunderstanding associated with this course is to attend class. Please, be courteous during class; both to me and your colleagues. I find late arrivals distracting, which cause a decline in the quality of my lecture.
Exams: Two examinations will be taken, a midterm exam during week seven of the course and a final exam covering all course content during the final examination period. Exam format may combine a mixture of short answer, true/false, matching, sort answer, and reasoning problems covering all readings, lecture, hand-out and class discussion content. Another computer based test in SPSS will be included in the period between the midterm and final exam.
Deadlines in submitting the homework are critical. Therefore, late assignments and absence from tests will not be tolerated. In the event of illness or emergency, contact your instructor IN ADVANCE to determine whether special arrangements are possible. The University’s rules on academic dishonesty (e.g. cheating, plagiarism, submitting false information) will be strictly enforced. Please familiarize yourself with the STUDENT HONOUR CODE, or ask your instructor for clarification.
Criteria for Determination of Grade
|Active Participation & Homework||10%|
Grading scale follows the official UNYT and UOG as below:
|Letter Grade||Percent (%)||Generally Accepted Meaning|
|B+||87-89||Good work, distinctly above average|
|D+||67-69||Work that is significantly below average|
|F||0-59||Work that does not meet minimum standards for passing the course|
|Grade Designation||Percentage (%)||Generic Assessment Criteria|
|Distinction||86-100||The work examined is exemplary and provides clear evidence of a complete grasp of the knowledge, understanding and skills appropriate to the Level of the qualification. There is also ample excellent evidence showing that all the learning outcomes and responsibilities appropriate to that Level are fully satisfied.|
|Distinction||76-85||The work examined is outstanding and demonstrates comprehensive knowledge, understanding and skills appropriate to the Level of the qualification. There is also excellent evidence showing that all the learning outcomes and responsibilities appropriate to that Level are fully satisfied.|
|Distinction||70-75||The work examined is excellent and is evidence of comprehensive knowledge, understanding and skills appropriate to the Level of the qualification. There is also excellent evidence showing that all the learning outcomes and responsibilities appropriate to that Level are satisfied.|
|Merit||65-69||The work examined is very good and is evidence of the knowledge, understanding and skills appropriate to the Level of the qualification. There is also very good evidence showing that all the learning outcomes and responsibilities appropriate to the Level are satisfied.|
|Merit||60-64||The work examined is good and is evidence of the knowledge, understanding and skills appropriate to the Level of the qualification. There is also good evidence showing that all the learning outcomes and responsibilities appropriate to that Level are satisfied.|
|Merit||55-59||The work examined is sound and is evidence of the knowledge, understanding and skills appropriate to the Level of the qualification. There is also sound evidence showing that all the learning outcomes and responsibilities appropriate to that Level are satisfied.|
|Pass||40-54||The work examined is sound but provides limited evidence of the knowledge, understanding and skills appropriate to the Level of the qualification. There is also sound but limited evidence showing that all the learning outcomes and responsibilities to that Level are satisfied.|
|Fail||0-39||Work that is significantly below average and does not meet minimum standards for passing a course.|
Technology Expectations: usage of power-point, excel, word, SPSS. Students must keep copies of all assignments and projects sent by e-mail.
Assignments are to be word-processed and converted into pdf files. Continuing and regular use of e-mail is expected.
STUDENTS: If you feel that you have special learning difficulties, please, make an appointment with Dr. Enila Cenko, who is trained to help students with learning difficulties. She has offered to provide this service to our students, just as it is offered in all American universities.