In: Math
What would be one example that may demonstrate a non-normal distribution of blood pressures? Would it have a particular type of skew? Why or why not? Why would it look this way?
An example will help you to find out why blood pressure data is/is not normal.
Blood Glucose | Blood Pressure |
241 | 477 |
229 | 519 |
0 | 3 |
84 | 167 |
106 | 191 |
0 | 0 |
192 | 341 |
321 | 497 |
4 | 5 |
165 | 219 |
216 | 299 |
0 | 0 |
28 | 59 |
14 | 24 |
Here I shall plot the theoretical quantile vs actual quantile to get the data checked for blood pressure.
Here is the graph below.
From this, we can see that the data is NOT normal. But what can be possible reasons?
1. Lack of data may lead to some different distribution rather than a normal distribution.
2. If the data is inflated in a certain region, then also the data might be skewed for that region. Hence, normality will be violated in those cases.
3. If the data is heavy-tailed, i.e. if we go much further than the theoretical median, then also we will get some probabilities. Hence the normality will be violated in that case also.
So, these are some reasons where normality can be violated. Hope this answer has helped you.
Thanks !!