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Faculty of Philosophy / SOCIOLOGY / STATISTICS IN SOCIOLOGY

Course:STATISTICS IN SOCIOLOGY/
Course IDCourse statusSemesterECTS creditsLessons (Lessons+Exercises+Laboratory)
10134Obavezan152+2+0
ProgramsSOCIOLOGY
Prerequisites No
Aims The main goal is to acquaint students with methods of statistical analysis and data processing, ability to solve tasks and use the acquired knowledge in research. Students will master the use of Excel for calculation and visualization of data, as well as obtained results.
Learning outcomes After a student passes this exam, they will be able to understand the concepts of sampling, statistical data analysis, and statistical inference. They will acquire concepts related to descriptive statistics, basic elements of counting and Probability, understand the concept of random variable, become familiar with the most commonly used random variable distributions and encounter point estimation of parameters.
Lecturer / Teaching assistantBiljana Stamatovic, full professor
MethodologyLectures, exercises, homework (case study), consultations, use of Excel and Data Analysis plugin.
Plan and program of work
Preparing weekPreparation and registration of the semester
I week lecturesIntroduction to Statistics
I week exercisesIntroduction to statistics. Refreshing knowledge of the elements of calculation (percentages, fractions, reading from graphs,...)
II week lecturesData and their grouping (frequency, relative frequency, cumulative frequency).
II week exercises Data and their grouping (frequency, relative frequency, cumulative frequency). Excel.
III week lecturesDescriptive statistics. Measures of central tendency
III week exercisesDescriptive statistics. Measures of central tendency (manual and Excel)
IV week lecturesDescriptive statistics. Measures of variation and shape. Statistics.
IV week exercisesMeasures of variation and shape. Excel.
V week lecturesSets. Counting the set.
V week exercisesSets. Counting the set.
VI week lecturesExam
VI week exercisesExam
VII week lecturesProbability. The Law of large numbers.
VII week exercisesProbability. The Law of large numbers.
VIII week lecturesRandom variable and distribution function. Discrete random variable. Measurements of central tendency and variability.
VIII week exercisesRandom variable and distribution function. Discrete random variable. Measurements of central tendency and variability.
IX week lecturesBinomial distribution.
IX week exercisesBinomial distribution. Excel.
X week lecturesHypergeometric distribution. Geometric distribution.
X week exercisesHypergeometric distribution. Geometric distribution.
XI week lecturesPoisson distribution.
XI week exercisesPoisson distribution. Excel.
XII week lecturesThe density function of a continuous random variable. Uniform distribution.
XII week exercisesThe density function of a continuous random variable. Uniform distribution.
XIII week lecturesNormal distribution. Standardized normal distribution. Use of statistical tables.
XIII week exercisesNormal distribution. Standardized normal distribution. Use of statistical tables.
XIV week lecturesExponential distribution. Point estimation.
XIV week exercisesExponential distribution. Point estimation.
XV week lecturesExam.
XV week exercisesExam.
Student workload5
Per weekPer semester
5 credits x 40/30=6 hours and 40 minuts
2 sat(a) theoretical classes
0 sat(a) practical classes
2 excercises
2 hour(s) i 40 minuts
of independent work, including consultations
Classes and final exam:
6 hour(s) i 40 minuts x 16 =106 hour(s) i 40 minuts
Necessary preparation before the beginning of the semester (administration, registration, certification):
6 hour(s) i 40 minuts x 2 =13 hour(s) i 20 minuts
Total workload for the subject:
5 x 30=150 hour(s)
Additional work for exam preparation in the preparing exam period, including taking the remedial exam from 0 to 30 hours (remaining time from the first two items to the total load for the item)
30 hour(s) i 0 minuts
Workload structure: 106 hour(s) i 40 minuts (cources), 13 hour(s) i 20 minuts (preparation), 30 hour(s) i 0 minuts (additional work)
Student obligations Mandatory attendance.
ConsultationsAt the request of students.
LiteratureBoris Pec, Basic statistical methods for non-mathematicians J. Alan Weinstein, Applying Social Statistics, 2010 Mohamed A. Shaiib, Applied Statistics, 2013
Examination methodsHomework - maximum 20 points Exam - maximum 30 points Final exam - maximum 45 points Attendance - maximum 5 points
Special remarksA passing grade is obtained if 51 points are accumulated cumulatively
CommentNo.
Grade:FEDCBA
Number of pointsless than 50 pointsgreater than or equal to 50 points and less than 60 pointsgreater than or equal to 60 points and less than 70 pointsgreater than or equal to 70 points and less than 80 pointsgreater than or equal to 80 points and less than 90 pointsgreater than or equal to 90 points
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