Causal interference - Bivariate tests
8 important questions on Causal interference - Bivariate tests
What is an bivariate analysis?
- It's a very simple quantitative analysis
What can the bivariate analyse help with?
- For testing simple hypotheses of association.
- determine to what extent it becomes easier to know and predict a value for one variable (possibly a dependent variable) if we know the value of the other variable (possibly the independent variable).
When can we use a T-test?
- Strictly speaking, it can only be used if the variances of the two populations are assumed to be equal.
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How to perform the t-test? (three steps)
- Calculalte the t-value
- Look at the degrees of freedom
- Determine if the H0 can be rejected by using a T-table
How to use a T-table?
For the row we need to decide the Degrees of Freedom (Df = N1 + N2 -2)
- Then the T-value is higher than the value found in the T-table, H0 can be rejected.
When do we use the Chi-squared test and what is its purpose?
Purpose?
To evaluate how likely the observations that are made would be, assuming the null hypothesis is true.
What does the Chi-squared (change) test do and what is its equation?
Oi = observed data
Ei = Expected values
What is the difference between a t-test and a chi-squared test?
- Tests a null hypothesis about two means; most often, it tests the hypothesis that two means are equal, or that the difference between them is zero.
Chi-square test:
- Tests a null hypothesis about the relationship between two variables.
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