Question
upstudy study bank question image url

What is a lurking variable?
A. A lurking variable is a quantitative variable that has either a finite number of possible values or a countable number of possible values. In addition, lurking variables are typically
to zero, or almost equal to zero.
B. Alurking variable is a quantitative variable that has an infinite number of possible values that are not countable. In addition, lurking variables are typically very large numbers that
them difficult, if not impossible, to include in a study.
C. Alurking variable is an explanatory variable that was not considered in a study, but that affects the value of the response variable in the study. In addition, lurking variables are typ
related to explanatory variables in the study.
D. Alurking variable is a response variable that was not considered in a stidy, but is also affected by the casual relationship of the explanatory variables in the study. In addition, lurke a very strong relationship.
variables are typically related to response variables in the study.

Ask by Harrington Griffin. in the United States
Jan 19,2025

Upstudy AI Solution

Tutor-Verified Answer

Answer

A lurking variable is an explanatory variable not considered in a study that affects the response variable.

Solution

Sign in to Unlock Answers for Free!

A Learning Platform Trusted by Millions of Real Students and Teachers.

star-icon Unlock

Answered by UpStudy AI and reviewed by a Professional Tutor

The Deep Dive

A lurking variable, often sneaky and devious, is like that unexpected guest at a party who influences the vibe but wasn’t invited. It’s an explanatory variable not considered in a study that significantly impacts the response variable, often causing misleading results or conclusions. For example, when studying the relationship between exercise and weight loss, a lurking variable could be diet—quite the party crasher!
To avoid pitfalls associated with lurking variables, engaging in thorough research design is essential! Researchers should brainstorm potential factors that could influence their results and try to measure or control for them as much as possible. Common mistakes include overlooking well-known confounding variables or assuming all relevant factors have been accounted for. Remember, sometimes what you can’t see can hurt your findings!

Related Questions

Latest Statistics Questions

Try Premium now!
Try Premium and ask Thoth AI unlimited math questions now!
Maybe later Go Premium
Study can be a real struggle
Why not UpStudy it?
Select your plan below
Premium

You can enjoy

Start now
  • Step-by-step explanations
  • 24/7 expert live tutors
  • Unlimited number of questions
  • No interruptions
  • Full access to Answer and Solution
  • Full Access to PDF Chat, UpStudy Chat, Browsing Chat
Basic

Totally free but limited

  • Limited Solution
Welcome to UpStudy!
Please sign in to continue the Thoth AI Chat journey
Continue with Email
Or continue with
By clicking “Sign in”, you agree to our Terms of Use & Privacy Policy