A researcher compares a group of children who participate in a large number of extracurricular activities to a group of children who do not participate in any extracurricular activities. The researcher finds that the first group gets much higher grades than the second group. Based on this study, the researcher can conclude that:
Are there answer choices or is this just an open question?
A.Participating in extracurricular activities causes children to get better grades. B.Getting better grades causes children to want to participate in more extracurricular activities. C.Some relationship exists between participating in extracurricular activities and grades. D.Nothing can be concluded from this data.
The answer would be A. Since the first group, the one who gets higher grades, participates in extracurricular activities
Granted, there's a number of ways to refute that claim. C is also a possible answer. But I believe A is the clearest and safest one.
well, even though A seems to be the most direct and possibly correct answer, we cannot directly prove that these kids got better grades because of that, but you can surely notice a relationship there
so its C, right?
but the key is that, it says relationship between activities and grades, not higher grades, so yeah A is right
A is my pick as well
note that this is not an experimental study, its an observational study. you cannot infer causality from observational study
so what do you think it is? @perl
well you can eliminate the choices that say 'causes'
so you think its C?
I can't give the answer :)
but there does seem to be some (positive) relationship between grades and extracurriculur activities
idk im either between A or C
A says causes so thats wrong
you have narrowed it down between C and D ,
perl you just disproved your own argument. If there is a positive relationship, then it DOES indeed cause better grades.
no i didnt . there is a positive relationship between number of churches and crime. that does not mean churches *cause* crime
But this question is very vague and the answers are not at all clear.
its clear enough
is not vague is very analytical
I disagree. But you're the one getting a medal for every answer. So I suppose you're correct.
it is a fact that the more churches there are, the higher the crime rate. does that show that churches cause crime? ask yourself this.
that's what I said about C also, you can't directly think of A because of the nature of the experiment :P
what causes crime is not churches but the third variable of population. the more populated an area, the more churches, (and then the more crime)
That example doesn't apply here if there is more than two variables at play. Here there are two things at play: Kids in extracurriculars and kids who aren't, and quality of grades. To me there is a clear direction the question the taking.
yes it does apply. its the same type of question
a researcher observes that the more churches there are in a town, the higher the crime rate.
How? There's only 2 variables here. In your churches example there are several.
there is a *positive* relationship between number of churches and crime
yes there are two variables in the example i gave. just as in this example
Yes but you JUST said that the cause of that relationship is a THIRD variable, population.
that has to be determined independently
actually the cause of crime is very complex
i know for sure tht is not D
Clearly the cause of these kids getting better grades is very complex. There's home life at play, diet, literacy level, etc... You're complicating this question far beyond it's intended academic level.
google "correlation does not prove causation" thats basically what im saying
so @perl you think its A?
getting high grades is positively correlated with extracurricular activities. you cannot infer a causality
getting high grades is positively correlated with extracurricular activities. you cannot infer causality
Can you help me with this one? @perl The validity of a test refers to: A.Its consistency B.The extent to which two raters agree on its result C.The degree to which it measures what it is intended to measure D.The level of agreement between different observers of the same behavior
The term validity refers to whether or not the test measures what it claims to be testing
so C
thanks for your help
By any chance would you know how to answer this? @perl Dr. Fisher wants to know whether an infant can tell the difference between a human face and a monkey face. Describe the methods that she should use to test this question. Be sure to state what the infants are exposed to, as well as what response is measured.
may i ask what book you are using?
this is a pretty broad question, i have to think about it
maybe your book has an example
the book is how children develop 4th edition, from notes of class we talked about the habituation task and the violation of expectation task
hmm
@perl Do you know this question? The harmfulness of a teratogen is determined in part by the genes of the fetus. True False
@Kommander_Kitten here is another good example of the aforementioned point. "Researchers have observed that as ice cream sales increase, the rate of drowning deaths increases sharply. " There is a positive relationship between ice cream sales and drowning. Can we conclude from this that increasing ice cream sales causes more drowning? no, that would be an absurd conclusion
The aforementioned example fails to recognize the importance of time and temperature in relationship to ice cream sales. Ice cream is sold during the hot summer months at a much greater rate than during colder times, and it is during these hot summer months that people are more likely to engage in activities involving water, such as swimming. The increased drowning deaths are simply caused by more exposure to water-based activities, not ice cream. The stated conclusion is false.
Point taken.
Another famous example: we can observe a positive link between lung cancer and cigarettes (the tar producing kind), ie, that people who smoke have a higher rate of cancer compared to non smoking population. This does not demonstrate causality however. To demonstrate that cigarettes *cause* lung cancer you would have to take 100 young adults, randomly divide them in half, tell 50 of them to smoke and the rest cannot smoke, and wait 40-50 years, and compare the rate or percentage of lung cancer in two groups. (not an easy experiment and pretty much unethical) sorry to be pedantic, but this is so important :)
Point taken even further.
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