100% satisfaction guarantee Immediately available after payment Both online and in PDF No strings attached
logo-home
Previously searched by you
Previously searched by you
logo
OMSA Midterm 2 Exam Questions With 100% Verified Answers. $10.49
Add to cart
Quickly navigate to
Preview
  2.  
  3. OMSA
  4.  
  5. OMSA

Exam (elaborations)

OMSA Midterm 2 Exam Questions With 100% Verified Answers.
 0 purchase
  • Course
  • OMSA
  • Institution
  • OMSA

OMSA Midterm 2 Exam Questions With 100% Verified Answers. Overfitting - answerNumber of factors is too close to or larger than number of data points -- fitting to both real effects and random effects. Comes from including too many variables! Ways to avoid overfitting - answer- Need number of fa...

[Show more]

Preview 2 out of 9  pages

Document information

  • October 2, 2024
  • 9
  • 2024/2025
  • Exam (elaborations)
  • Questions & answers

Subjects

  • omsa midterm 2 exam questions with 100 verified a

Written for

  • OMSA
  • OMSA

Seller

avatar-seller
Brainbarter

Reviews received

Content preview

©BRAINBARTER 2024/2025




OMSA Midterm 2 Exam Questions With
100% Verified Answers.



Overfitting - answer✔Number of factors is too close to or larger than number of data points --
fitting to both real effects and random effects. Comes from including too many variables!

Ways to avoid overfitting - answer✔- Need number of factors to be same order of magnitude as
the number of points
- Need enough factors to get good fit from real effects and random effects

Simplicity - answer✔Simple models are better than complex. When fewer factors exist, less data
collection is required -- less chance for including factors that are not significant. Another reason
for variable selection!

DOE - answer✔systematic method to determine the relationship between factors affecting a
process and the output of that process.
must make sure either:
1) 2 data sets have same mix
2) break down data into smaller tests that test all factors, not just one.

forward selection - answer✔go step by step either narrowing or building a model -- begin with
no factors.
only allow new factors with p-value 0.1 or lower and removing any factors above 0.05.

Greedy models - answer✔forward selection, backward selection, stepwise regression


means: at each step it does the one thing that looks best withouth taking future options into
consideration

scaled variable selection models - answer✔lasso, elastic net, (and ridge even though not variable
selection)

, ©BRAINBARTER 2024/2025


backward selection - answer✔start with model includes all factors and at each step find worst
factor and remove it from the model.
continue till there's no factor bad enough to remove and model doesn't have any more factors we
want.

step-wise regression - answer✔combination of forward and backward elimination -- beginning
with either all factors or no factors.
after adding each new factor (and at end) -- eliminate right away any factors that no longer
appear any good. future options are not considered.
could use AIC or BIC, or model's R squared to pick factor to add/remove in fwd, bckwd, or
stepwise

lasso method - answer✔adds constraint tau to std reg model. chooses coefficients to min sum of
squared errors.


right value of tau dependent on 2 things:
1) # of variables you want
2) quality of the model as you allow more variables


Correlation -- picks just one to have non-0 coefficient. other is left out.

elastic net - answer✔constrain combination of abs value and coefficients and their squares -- mix
of ridge and lasso.
need to scale and pick right value of tau + lambda

ridge regression - answer✔similar to elastic net, but without abs value term (lasso portion).
adds quadratic term that shrinks coefficient values (pushing reg coeff to 0 or regularizes them).
this adds bias but shrinks variance as cannot shrink to 0 as easily as quadratic term


trades off bias for variance but can lead to better predictive models.

blocking - answer✔arranging of experimental units in groups that are similar to one another.


accounts for bias differences via variable differences that are dependent on dependent variable

The benefits of buying summaries with Stuvia:

Guaranteed quality through customer reviews

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

Quick and easy check-out

You can quickly pay through credit card or Stuvia-credit for the summaries. There is no membership needed.

Focus on what matters

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 Brainbarter. Stuvia facilitates payment to the seller.

Will I be stuck with a subscription?

No, you only buy these notes for $10.49. You're not tied to anything after your purchase.

Can Stuvia be trusted?

4.6 stars on Google & Trustpilot (+1000 reviews)

69052 documents were sold in the last 30 days

Founded in 2010, the go-to place to buy study notes for 15 years now

Start selling
$10.49
  • (0)
Add to cart
Added