SJSU Final Exam Bio 155/55 Questions With Answers Graded A+ Assured Success
10 views 0 purchase
Module
SJSU Bio 155/55
Institution
SJSU Bio 155/55
Is Alpha = 0.05 meaningful? - ️️-Depends on how you look at it
-It seems like a rational number and it works, but we can adjust it depending on what we
are looking for.
-Medically, we may be wanting a p value of 0.01 in order to have most accurate results
-For ecology, we may change the p v...
SJSU Final Exam Bio 155/55
Is Alpha = 0.05 meaningful? - ✔️✔️-Depends on how you look at it
-It seems like a rational number and it works, but we can adjust it depending on what we
are looking for.
-Medically, we may be wanting a p value of 0.01 in order to have most accurate results
-For ecology, we may change the p value to 0.1
-For many statisticians it is valuable, and they use it as a determining factor of wether or
not they want to publish their data.
-The problem with this is that a lot of the time scientist repeat experiments due to
unpublished negative findings
-Another outlook is that p value was meant to be a first look of findings
Since many scientists see p value as meaningful, they stop their studies when they get
negative results even if there is a correlation. R.A Fishcher meant for it to be more of a
first look at your findings
-Many statisticians in the community have began no longer using a p value for the
reasons listed above, and therefore the alpha can be meaningful, it varies from
statistician to statistician, along with the field of work.
Relative Risk: - ✔️✔️-Aka risk ratio
-Ratio of risks for 2 groups
-RR = (risk of intervention group/risk for reference group)
-RR = 1 means risk is the same
-RR > 1 patients with paclovid are more likely to be hospitalized than placebo
-RR<1 patients with paxlovid less likely to get hospitalized than placebo
Relative Risk reduction (RRR): - ✔️✔️-proportionate reduction in risk for the
intervention group relative to refrence group
-RRR = ( risk for reference group - risk for intervention -group / risk for refrence group )
x 100
-Interpretation example: RRR= 88.8837%, paxlovid groups risk of HOD is reduced by
88.9% relative to the placebo group
-Reference = placebo group
-Intervention = paxlovid
How was alpha =0.05 determined? - ✔️✔️-R.A. Fisher wrote a book in 1925 he put
statistical tables used to determine statistical significance
-Needed a separate table for each df which was too many
-He chose alpha= 0.05
-Is arbitrary, feels reasonable, it works, socially accepted
-intended as a first look
-If alpha = 0.02 that means there is a 2% chance of making a type one error.
Decreasing type one error we increase the chance of a type two error ( missing
significant findings )
, Using Alpha and Null Hypothesis significance Testing( NHST) - ✔️✔️-Caused by the p-
value there is dichotomy( 2 outcomes ) which are significant p< alpha and non
significant p> alpha
-Significant also called positive findings ( most published)
-non significant also called negative findings (put in the file drawer)
2 x 2 Table - ✔️✔️2 variables:
-1 variable: treatment/ Intervention/ Factor
-2nd variable: outcome/ Event
There are frequencies analyzed in a 2 x 2 contingency table
Risk - ✔️✔️-Probability an event will occur
-Risk in one group: # of individuals with the outcome/ total # of individuals in that group
Importance of negative findings - ✔️✔️-In scientific knowledge they are important
-Scientists may repeat studies because they may not know about the unpublished
studies (negative findings usually dont get published)
-They are scientifically significant
Publication Bias: - ✔️✔️positive findings are more likely to be published (95%)
P-hacking - ✔️✔️-When a statistician is trying to get positive results they add or take
away data to get the positive results they want.
-This makes the data no longer accurate/ should no longer be published ( not
meaningful)
-Therefore focusing on p values makes us ignore trends that are still important
-The trend could also possibly be due to chance
-Managing data can be p-hacking depending on the study
biased
Why is focusing on p-values problematic? - ✔️✔️-Scientific significance/significance
meaning ( + results wanting to be published, there is still knowledge to be learned even
if it is a negative finding) losing sight of scientific knowledge and significance
-Contribution to science
-What knowledge we gain from it
-Can look over some relationships and effects
-Arbitrary
-intended for first look, it wasn't meant for it to be determining factor
Solutions - ✔️✔️-Look at the scientific significance
-Look at how it contributes to the field
-Meaning of the results
-Look at trends
The benefits of buying summaries with Stuvia:
Guaranteed quality through customer reviews
Stuvia customers have reviewed more than 700,000 summaries. This how you know that you are buying the best documents.
Quick and easy check-out
You can quickly pay through credit card for the summaries. There is no membership needed.
Focus on what matters
Your fellow students write the study notes themselves, which is why the documents are always reliable and up-to-date. This ensures you quickly get to the core!
Frequently asked questions
What do I get when I buy this document?
You get a PDF, available immediately after your purchase. The purchased document is accessible anytime, anywhere and indefinitely through your profile.
Satisfaction guarantee: how does it work?
Our satisfaction guarantee ensures that you always find a study document that suits you well. You fill out a form, and our customer service team takes care of the rest.
Who am I buying these notes from?
Stuvia is a marketplace, so you are not buying this document from us, but from seller PatrickKaylian. Stuvia facilitates payment to the seller.
Will I be stuck with a subscription?
No, you only buy these notes for £6.82. You're not tied to anything after your purchase.
