Lecture bioinformatic databases - Linear regression
14 important questions on Lecture bioinformatic databases - Linear regression
What is the basis equation of a straight line?
--> intercept and slope (y=b+ax)
If ß0 and ß1 fit perfectly, does this say something about the population with 100% reliability?
Is a linear regression model always a good idea?
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Often, an error term (e) is included in the equation of linear regression, why?
What is the purpose of residuals?
What is the null hypothesis (H0) for linear regression?
Reject null hypothesis if P<0.05 (with alpha level 5%)
What is the difference when to use linear regression model and t-test?
Linear regression model for impact of continuous variable on continuous outcome (covariates)
How can the 95% confidence interval be calculated?
--> -1.96 is the 2.5th percentile of standard normal distribution and 1.96 the 97.5th percentile
Which assumptions are made for linear regression model?
2. Observations in the sample are independent
3. For each x, outcome y is normally distributed in the population with mean y(x) and variance SD^2
4. Variance is constant
5. X can be measured without error
How can you check assumption 1 of linear regression (linear relationship between x and y) ?
--> no pattern in residual(s), but random scatter: on average 0
How to check assumption 3 of linear regression (for each x, outcome y is normally distributed in the population)?
How to check assumption 2 and 5 of linear regression? (observations are independent and x can be measured without error)
5: choose proper measuring device
When do you use multiple linear regression models?
--> length depends on age and sex, crop depends on fertilizer and amount of rain
What is the general equation of multiple linear regression?
ß0 = constant
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