Starting Point: determination and contrast of hypothesis.
Null Hypotesis (H0): Fluid Overload not becomes meaningful on the evolution of patients with septic shock. Defect action: Not change protocol, continue with actual proceedings.
Alternative Hypotesis (H1): Fluid Overload becomes meaningful on the evolution of patients with septic shock. Fluid resucitation excessive to impact in prognosis. Alternative action: protocol with adjustment of procedures that allow to minimize the evidences of consequences and worsening associated to a gain of volume.
Strategies to make post actions, with new model for evaluation:
Analyze data samples to identify features and distribution of cases type, and find a percentage value to minimize impact on the evolution of patients.
Make Sample to evaluate impact, (e.g. with volume gains greater than 10%).
If meaningful, determine a cut-off value of volume gain, after the third day of admission, or until the first week on all hospitalization.
Good practices:
Analytics (simply look at a dataset and summarize what you see) cares about what’s here), has only one golden rule: stick to the data and don’t go beyond it. Some people seem to think that whenever they analyze data, the universe owes them insights beyond the facts.
Statistics cares more about what isn’t, is trickier. Subtle things matter when you do battle with the unknown. Statistics is the science of changing your mind under uncertainty. Making decisions based on facts (parameters) is hard enough as it is, but sometimes, we don’t even have the facts we need. Instead, what we know (our sample) is different from what we wish we knew (our population). That’s what it means to have uncertainty.
Remember!: Option A: we learned nothing interesting. Null hypothesis. Option B:Does the evidence that we collected make our null hypothesis look ridiculous?Yes...Alternative hypothesis.