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Can you do regression if data is not normally distributed?
In short, when a dependent variable is not distributed normally, linear regression remains a statistically sound technique in studies of large sample sizes. Figure 2 provides appropriate sample sizes (i.e., >3000) where linear regression techniques still can be used even if normality assumption is violated.
Does my data need to be normal for linear regression?
Summary: None of your observed variables have to be normal in linear regression analysis, which includes t-test and ANOVA. The errors after modeling, however, should be normal to draw a valid conclusion by hypothesis testing.
How do you interpret odds ratio?
interpreting the odds ratio for continuous variable depends on the unit of the continuous variable. It will mean the odds increase for every one unit increase in the continuous variable measure. You can also computer the odds ratio for every 10 units or any number of increase in the continuous variable measure.
What are the odds ratio in statistics?
An odds ratio ( OR) is a statistic that quantifies the strength of the association between two events, A and B . The odds ratio is defined as the ratio of the odds of A in the presence of B and the odds of A in the absence of B, or equivalently (due to symmetry ), the ratio of the odds of B in the presence of A and the odds of B in the absence of A.
What is odds ratio greater than 1?
An odds ratio greater than 1 indicates that the condition or event is more likely to occur in the first group. And an odds ratio less than 1 indicates that the condition or event is less likely to occur in the first group.
What is the meaning of odds ratio?
Definition in terms of group-wise odds. The odds ratio is the ratio of the odds of an event occurring in one group to the odds of it occurring in another group. The term is also used to refer to sample-based estimates of this ratio.