Quantitative Digital Humanities
Course code
IFI6221.DT
old course code
Course title in Estonian
Kvantitatiivne digihumanitaaria
Course title in English
Quantitative Digital Humanities
ECTS credits
6.0
Assessment form
assessment
lecturer of 2024/2025 Autumn semester
Not opened for teaching. Click the study programme link below to see the nominal division schedule.
lecturer of 2024/2025 Spring semester
Not opened for teaching. Click the study programme link below to see the nominal division schedule.
Course aims
Provide opportunities to develop knowledge and skills in the field of quantitative analysis methods of digital technologies.
Create conditions for developing practical skills in the technologies of digital research.
Create conditions for developing practical skills in the technologies of digital research.
Brief description of the course
Acquiring the methods of descriptive statistics by using practical samples and input from sources with different formats. Filtering and conversion of data for the purpose of manageable research. SQL commands, XML equipment. Main terminology of statistics, the use of them for recognising data.
Evaluating the importance of deviation based on a 2x2 data table.
Finding the data differences and similarities by using Chi-Square Tests of frequency tables. The applications of this method in linguistics, folklore and history studies etc..
Grouping of entries based on meta-data.
Grouping of characteristics. Finding dependencies between characteristics. Linear modelling of correlations. Examples of other possible forms of correlations.
Understanding data distribution by use of histograms.
The characteristics of normal distribution, comparing data set distribution to normal distribution. Examples of indicators that comply better or less well than normal distribution.
Predicting the cumulative values by using expected values and standard deviation. Detecting common and unusual fluctuations in text word frequency.
Comparing expected values by t-test.
Prior calculation of summaries with DataCube.
Evaluating the importance of deviation based on a 2x2 data table.
Finding the data differences and similarities by using Chi-Square Tests of frequency tables. The applications of this method in linguistics, folklore and history studies etc..
Grouping of entries based on meta-data.
Grouping of characteristics. Finding dependencies between characteristics. Linear modelling of correlations. Examples of other possible forms of correlations.
Understanding data distribution by use of histograms.
The characteristics of normal distribution, comparing data set distribution to normal distribution. Examples of indicators that comply better or less well than normal distribution.
Predicting the cumulative values by using expected values and standard deviation. Detecting common and unusual fluctuations in text word frequency.
Comparing expected values by t-test.
Prior calculation of summaries with DataCube.
Learning outcomes in the course
Upon completing the course the student:
- is able to use quantitative methods for analysing humanities;
- knows the usage fields of quantitative methods;
- is able to choose an appropriate method for a situation;
- is able to assess the accuracy of the deductions made and the factors influencing them.
- is able to use quantitative methods for analysing humanities;
- knows the usage fields of quantitative methods;
- is able to choose an appropriate method for a situation;
- is able to assess the accuracy of the deductions made and the factors influencing them.
Teacher
Jaagup Kippar
Study programmes containing that course