Social and Economic Statistics
Study Board of Market and Management Anthropology, Economics, Mathematics-Economics, Environmental and Resource Management
Teaching language: English
EKA: B500024112, B500024102
Censorship: Second examiner: None
Grading: 7-point grading scale
Offered in: Odense
Offered in: Spring
Level: Bachelor
Course ID: B500024101
ECTS value: 5
Date of Approval: 13-11-2018
Duration: 1 semester
Course ID
Course Title
Teaching language
ECTS value
Responsible study board
Study Board of Market and Management Anthropology, Economics, Mathematics-Economics, Environmental and Resource Management
Date of Approval
Course Responsible
Offered in
Level
Offered in
Duration
Mandatory prerequisites
Recommended prerequisites
Aim and purpose
The purpose of the course is to enable the student to interpret information in statistical charts as well as to summarize and communicate statistical analysis results to others. Examples of social and business applications are used in order to show how statistics is used in everyday life and to illustrate how statistics can help investigate market potential. The course provides the basis for understanding research methodology and conducting independent research when performing anthropological fieldwork. In particular, at the end of the course students are expected to be able to discuss and explain basic statistical methodology, develop skills used in collecting and analysing data, and gain the ability to plan, conduct and analyse their own projects during the 5th semester. The course also provides skills highly valued by public and private employers.
Content
The course contains the following academic main areas:
- Data types, data sources, and sampling designs
- Descriptive statistics and graphical presentation of data
- Probability
- Statistical distributions: Binomial, Poisson, Uniform, Normal
- Sampling distributions
- Confidence intervals
- Hypothesis testing: Parametric methods (e.g. t test) and Nonparametric methods (e.g. Wilcoxon’s rank sum test)
- Association and correlation
- Regression models
Learning goals
Description of outcome - Knowledge
Demonstrate knowledge about the course’s focus areas enabling the student to:
- classify variables according to their data type (quantitative vs. qualitative)
- differentiate between populations and samples
- describe and explain how confidence intervals are constructed
- describe and explain how the various hypothesis tests are conducted
Description of outcome - Skills
Demonstrate skills, such that the student is able to:
- apply the statistical software package STATA in order to perform statistical evaluations
- calculate simple measures of descriptive statistics
- produce graphical presentations of data (e.g. pie charts, bar charts, boxplots, scatter plots)
- calculate probabilities on data following a Binomial, Poisson, Uniform, and Normal distribution
- derive confidence intervals
- conduct statistical tests
- perform linear regression modelling
- formulate statistical hypotheses
Description of outcome - Competences
Demonstrate competences, such that the student is able to:
- relate statistical methods to usual business problems by finding the most appropriate method for computing confidence intervals and conducting statistical tests for a given problem
- argue whether a parametric or a non-parametric statistical test is appropriate in a particular setup
- interpret a confidence interval or the results of a statistical test
- explain the findings in terms of practical implications in the context of the problem at hand
Literature
Examples:
Bruce L. Bowerman, Richard T. O'Connell, Emily S. Murphree. Business Statistics in Practice. McGraw-Hill Education. Latest edition.
Alan C. Acock. A gentle introduction to Stata. Stata Press. Latest edition.
Teaching Method
In order to enable the students to achieve the learning goals of the course, the form of instruction comprises both lectures and exercise sessions. Lectures introduce statistical terms and methods without more focus on the collection and analysis of data rather than on calculation of formulas, while exercise sessions focus the practical application of these statistical methods to given scenarios. Students are expected to study the corresponding chapter(s) in the textbook in the same week when the lecture is held, preferably before the lecture. Moreover, students are expected to use the statistical software STATA from the beginning of the course and to come prepared to the exercise sessions by having worked through the scheduled exercises. Students should be able to communicate, explain and discuss their results with fellow students.
Workload
Scheduled classes:
2 hours of lectures weekly for 15 weeks.
2 hours of exercises weekly for 15 weeks.
Workload:
The teaching activities result in an estimated distribution of the work effort of an average student as follows:
Face-to-face teaching - 30 hours
Preparation for lectures - 30 hours
Exercise sessions - 30 hours
Preparation for exercise sessions - 20 hours
Preparation for examination - 22 hours
Examination - 3 hours
Total -135 hours
Examination regulations
Exam
Name
Exam
Timing
Mid-term evaluation (part 1):
Exam: March/April
Reexam: August
Final evaluation (part 2):
Exam: June
Reexam: August
Tests
Mid-term evaluation (part 1)
Name
Mid-term evaluation (part 1)
Form of examination
Written examination on premises
Censorship
Second examiner: None
Grading
7-point grading scale
Identification
Student Identification Card - Exam number
Language
English
Duration
1.5 hours
Length
No limitations, but short and precise answers preferred.
Examination aids
All exam aids allowed. Communication with others is not allowed.
Assignment handover
In the examination room.
Assignment handin
Via SDU-assignment in the course page in Blackboard.
ECTS value
2.5
Additional information
Individual written mid-term exam, on own computer (weight 50%)
The examination randomly tests the student's attainment of the course goals.
The final course grade is calculated as a weighted average with a weight of 50% on the grade for part 1 and a weight of 50% on the grade for part 2. The average is rounded to the nearest grade with the exception that the grade 02 cannot be given by rounding up the average.
EKA
B500024112
Final evaluation (part 2)
Name
Final evaluation (part 2)
Form of examination
Written examination on premises
Censorship
Second examiner: None
Grading
7-point grading scale
Identification
Student Identification Card - Exam number
Language
English
Duration
1,5 hours
Length
No limitations, but short and precise answers preferred.
Examination aids
All exam aids allowed. Communication with others is not allowed.
Assignment handover
In the examination room.
Assignment handin
Via SDU-assignment in the course page in Blackboard.
ECTS value
2.5
Additional information
Individual written final exam, on own computer (weight 50%).
The examination randomly tests the student's attainment of the course goals.
The final course grade is calculated as a weighted average with a weight of 50% on the grade for part 1 and a weight of 50% on the grade for part 2. The average is rounded to the nearest grade with the exception that the grade 02 cannot be given by rounding up the average.
EKA
B500024102
External comment
NOTE - This course is identical with the former course 9851401 Social and Economic Statistics.
Used examination attempts in the former identical course will be transferred.
Courses that are identical with former courses that are passed according to applied rules cannot be retaken.
The student is automatically registered for the first examination attempt when the student is registered for a course or course element with which one or more examinations are associated. Withdrawal of registration is not possible, and students who fail to participate in an examination have used one examination attempt, unless the University has made an exemption due to special circumstances.
Courses offered
| Offer period | Offer type | Profile | Education | Semester |
|---|---|---|---|---|
| Spring 2019 | Mandatory | HA(jur.) for studerende optaget 1. sept. 2018 eller senere | Bachelor of Science (BSc) in Business Administration and Law | Odense | 2 |
| Spring 2019 | Mandatory | BSc Market and Management Anthropology - Year 2018 | BSc in Market and Management Anthropology | Bachelor of Science in Market and Management Anthropology | Odense | 2 |
| Spring 2019 | Optional | BA negot Spansk, 180 ECTS, Optag 2017 | Bachelor of Arts (BA) in Business, Language and Culture (English), Bachelor of Arts (BA) in Business, Language and Culture (Spanish), Bachelor of Arts (BA) in Business, Language and Culture (German) | Odense | |
| Spring 2019 | Optional | BA negot Tysk, 180 ECTS, Optag 2017 | Bachelor of Arts (BA) in Business, Language and Culture (English), Bachelor of Arts (BA) in Business, Language and Culture (Spanish), Bachelor of Arts (BA) in Business, Language and Culture (German) | Odense | |
| Spring 2019 | Optional | BA negot Engelsk 180 ECTS Særligt forløb for Markedsføringsøkonomer | Bachelor of Arts (BA) in Business, Language and Culture (English), Bachelor of Arts (BA) in Business, Language and Culture (Spanish), Bachelor of Arts (BA) in Business, Language and Culture (German) | Odense | |
| Spring 2019 | Optional | BA negot Engelsk, 180 ECTS, Optag 2017 | Bachelor of Arts (BA) in Business, Language and Culture (English), Bachelor of Arts (BA) in Business, Language and Culture (Spanish), Bachelor of Arts (BA) in Business, Language and Culture (German) | Odense | Spring 2019 | Exchange students |