Can you use confidence intervals for non-normal data?
This method can be applied to a wide variety of parameters (mean, median, slope of a calibration curve, etc.) and is appropriate for normal and non-normal data sets. As a worked example, the confidence interval around the median concentration of cocaine in femoral blood is calculated using bootstrap techniques.
Does confidence interval assume normality?
The confidence interval of the mean of a measurement variable is commonly estimated on the assumption that the statistic follows a normal distribution, and that the variance is therefore independent of the mean.
Can you use z score Non-normal distribution?
Non-normal distributions can also be transformed into sets of Z-scores. In this case the standard normal table cannot be consulted, since the shape of the distribution of Z-scores is the same as that for the original non-normal distribution.
How do you find the confidence interval for an unknown distribution?
For a population with unknown mean and unknown standard deviation, a confidence interval for the population mean, based on a simple random sample (SRS) of size n, is + t* , where t* is the upper (1-C)/2 critical value for the t distribution with n-1 degrees of freedom, t(n-1).
What is the z score for 99 confidence interval?
Step #5: Find the Z value for the selected confidence interval.
| Confidence Interval | Z |
|---|---|
| 85% | 1.440 |
| 90% | 1.645 |
| 95% | 1.960 |
| 99% | 2.576 |
How do you handle non normal data?
There are two ways to go about analyzing the non-normal data. Either use the non-parametric tests, which do not assume normality or transform the data using an appropriate function, forcing it to fit normal distribution. Several tests are robust to the assumption of normality such as t-test, ANOVA, Regression and DOE.