#inferentialstats — Public Fediverse posts
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Alright, future engineers!
**Central Limit Theorem (CLT):** The distribution of sample means approaches normal, regardless of population shape, as sample size grows.
Ex: Avg strength of many concrete batches will be normal, even if single tests vary wildly.
Pro-Tip: Makes powerful inferential statistics possible even with non-normal raw data!
#CLT #InferentialStats #STEM #StudyNotes -
A **p-value** is the probability of seeing your data (or more extreme) IF the null hypothesis is true. Ex: If p < 0.05, reject the null. Pro-Tip: A *low* p-value means your result is unlikely by pure chance – strong evidence against the null!
#InferentialStats #EngineeringDecisions #STEM #StudyNotes -
A **p-value** is the probability of seeing your data (or more extreme) IF the null hypothesis is true. Ex: If p < 0.05, reject the null. Pro-Tip: A *low* p-value means your result is unlikely by pure chance – strong evidence against the null!
#InferentialStats #EngineeringDecisions #STEM #StudyNotes -
A **p-value** is the probability of seeing your data (or more extreme) IF the null hypothesis is true. Ex: If p < 0.05, reject the null. Pro-Tip: A *low* p-value means your result is unlikely by pure chance – strong evidence against the null!
#InferentialStats #EngineeringDecisions #STEM #StudyNotes -
A **p-value** is the probability of seeing your data (or more extreme) IF the null hypothesis is true. Ex: If p < 0.05, reject the null. Pro-Tip: A *low* p-value means your result is unlikely by pure chance – strong evidence against the null!
#InferentialStats #EngineeringDecisions #STEM #StudyNotes -
A **p-value** is the probability of seeing your data (or more extreme) IF the null hypothesis is true. Ex: If p < 0.05, reject the null. Pro-Tip: A *low* p-value means your result is unlikely by pure chance – strong evidence against the null!
#InferentialStats #EngineeringDecisions #STEM #StudyNotes