An introduction and examples of how to use the Chi square test. The test is used when analyzing assocation between two categorical variables and when comparing proportions. The idea behind the test is to compare the observed frequencies with the expected frequencies, if the two variables are unrelated.

An introduction and examples of how to use Correlation and Simple Linear Regression. Explaining concepts as coefficient of correlation, dependent variables, independent variables and the straight line equation and residuals.

An introduction and examples of how to use Descriptive Statistics. It is about how we present and decribe the data in our sample in the best possible way. This covers tabels, graphs, measures of location and measures of spread/variability.

An introduction and examples of how to use statistical hypothesis testing, introducing the five steps in the significance test: 1. Assumptions 2. Hypothesis and signifincance level 3. Test Statistic 4. P-value 5. Conclusion

Open Code is a tool for coding and categorizing qualitative data. Open Code 4.0 is a tool to help you index and sort big materials, so it can be searched and re-arranged for further analysis. Open Code was developed to follow the first steps of Grounded Theory but it is now possible to use it for all qualitative methods and it is prepared for Grounded Theory and Qualitative Content analysis. It is useful for sorting and classifying any kind of qualitative information. The software is developed to run on Windows. To run it on a Mac, you have to run a virtual machine or other systems to run pc-software on a mac computer.

How to create a project in Open Code 4. How to import documents to prepare for an analysis. Each project is an database of documents. The analysis is an intellectual process, done outside of Open Code. Open Code is a tool for coding and categorizing qualitative data. Open Code is a tool to help you index and sort big materials, so it can be searched and re-arrangede for furhter analysis. Open Code was developed to follow the first steps of Grounded Theory but it is now possible to use it for all qualitative methods and it is prepared for Grounded Theory and Qualitative Content analysis. It is useful for sorting and classifying any kind of qualitative information. The software is developed to run on Windows. To run it on a Mac, you have to run a virtual machine or other systems to run pc-software on a mac computer.

How to work in the documents in Open Code, showing the interface and ways to work through your project. Open Code is a tool for coding and categorizing qualitative data. Open Code is a tool to help you index and sort big materials, so it can be searched and re-arrangede for furhter analysis. Open Code was developed to follow the first steps of Grounded Theory but it is now possible to use it for all qualitative methods and it is prepared for Grounded Theory and Qualitative Content analysis. It is useful for sorting and classifying any kind of qualitative information. The software is developed to run on Windows. To run it on a Mac, you have to run a virtual machine or other systems to run pc-software on a mac computer.

An introduction and examples of how to use basic concepts in statistics, used in quantative studies: samples, population, variables, random samples, groups, ranking, measurement levels.

An introduction and examples of how to use Multiple linear regression. The Linear regression model investigates a linear relationship. The dependent variable should be quantitative and normally distributed. The Multiple Regression Model includes more than one independent variable. The Multiple Regression Model is introduced with real data from the Swedish pregnancy register.

An introduction and examples of how to use the basic ideas and steps in logistic regression and Cox regression. Regression is about trying to explain phenomena in reality by constructing a mathematical model that describes reality.

An introduction and examples of how to use Survival analysis and Life event analysis. This is about statistical methods for analyzing longitudinal data on the occurrence of events. Events may include death, injury, marriage, getting a job (binary variables).