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Chi square test (08:54)
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Chi square test (08:54)
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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.

Subject:
Applied Science
Health, Medicine and Nursing
Mathematics
Statistics and Probability
Material Type:
Lecture
Provider:
Umeå University
Provider Set:
Quantitative Research Methods
Author:
Marie Lindqvist
Associate professor in epidemiology and biostatistics
Date Added:
11/01/2014
MoreLess
Correlation and simple linear regression (09:54)
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Correlation and simple linear regression (09:54)
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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.

Subject:
Applied Science
Health, Medicine and Nursing
Mathematics
Statistics and Probability
Material Type:
Lecture
Provider:
Umeå University
Provider Set:
Quantitative Research Methods
Author:
Marie Lindqvist
Associate professor in epidemiology and biostatistics
Date Added:
11/01/2014
MoreLess
Descriptive statistics (09:20)
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Descriptive statistics (09:20)
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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.

Subject:
Applied Science
Health, Medicine and Nursing
Mathematics
Statistics and Probability
Material Type:
Lecture
Provider:
Umeå University
Provider Set:
Quantitative Research Methods
Author:
Associate professor in epidemiology and biostatistics
Marie Lindqvist
Date Added:
11/01/2014
MoreLess
Hypothesis testing (12:35)
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CC BY-NC-ND
Hypothesis testing (12:35)
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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

Subject:
Applied Science
Health, Medicine and Nursing
Mathematics
Statistics and Probability
Material Type:
Lecture
Provider:
Umeå University
Provider Set:
Quantitative Research Methods
Author:
Associate professor in epidemiology and biostatistics
Marie Lindqvist
Date Added:
11/01/2014
MoreLess
Introduction to statistics (08:01)
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CC BY-NC-ND
Introduction to statistics (08:01)
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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.

Subject:
Applied Science
Health, Medicine and Nursing
Mathematics
Statistics and Probability
Material Type:
Lecture
Provider:
Umeå University
Provider Set:
Quantitative Research Methods
Author:
Marie Lindqvist
Associate professor in epidemiology and biostatistics
Date Added:
11/01/2014
MoreLess
Multiple linear regression (10:43)
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CC BY-NC-ND
Multiple linear regression (10:43)
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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.

Subject:
Applied Science
Health, Medicine and Nursing
Mathematics
Statistics and Probability
Material Type:
Lecture
Provider:
Umeå University
Provider Set:
Quantitative Research Methods
Author:
Marie Lindqvist
Associate professor in epidemiology and biostatistics
Date Added:
11/01/2014
MoreLess
Overview of basic Logistic- and Cox regression (12:36)
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Overview of basic Logistic- and Cox regression (12:36)
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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.

Subject:
Applied Science
Health, Medicine and Nursing
Mathematics
Statistics and Probability
Material Type:
Lecture
Provider:
Umeå University
Provider Set:
Quantitative Research Methods
Author:
Marie Lindqvist
Associate professor in epidemiology and biostatistics
Date Added:
11/01/2014
MoreLess
Survival analysis and life event analysis (10:05)
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Survival analysis and life event analysis (10:05)
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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).

Subject:
Applied Science
Health, Medicine and Nursing
Mathematics
Statistics and Probability
Material Type:
Lecture
Provider:
Umeå University
Provider Set:
Quantitative Research Methods
Author:
Marie Lindqvist
Associate professor in epidemiology and biostatistics
Date Added:
11/01/2014
MoreLess