Biol 101: Problem Solving Workshop #1
Summary
TLDRThis workshop teaches non-scientists how to evaluate scientific claims using a checklist. It emphasizes the importance of determining if a claim is scientific, meets criteria of rationality, testability, and repeatability, and follows rigorous methods. Participants learn to assess evidence, including its collection, presentation, and whether it supports the claim. They also explore the difference between correlation and causation, and consider the credibility of the claimant and potential conflicts of interest. The workshop uses a case study on spa treatments to apply these concepts.
Takeaways
- 🔍 Evaluate scientific claims by using a checklist to consider various aspects of the inquiry.
- 🌐 Ensure the claim is focused on explaining something about the natural world and meets the criteria of being rational, testable, and repeatable.
- 🔬 Look for a logical flow in the explanation and a rigorous, methodical process in the scientific inquiry.
- 📊 Examine the type of evidence presented and its relevance, as well as the detail provided about how it was collected.
- 📈 Be critical of how evidence is presented, especially in graphical form, as it can skew conclusions.
- 🔢 Units are crucial for numerical evidence, as a number without units lacks meaning.
- ❓ Question whether conclusions logically follow from the evidence and if they are supported by multiple studies.
- 🔄 Be wary of overgeneralizations based on limited data or samples.
- ⚠️ Avoid confusing correlation with causation; just because two variables change together does not mean one causes the other.
- 👨🔬 Consider the expertise of the person making the claim and whether they have a conflict of interest or are promoting a conspiracy theory.
- 📚 Use a case study to apply these evaluation techniques, focusing on one aspect at a time rather than trying to address everything at once.
Q & A
What is the main focus of the workshop?
-The main focus of the workshop is to teach non-scientists how to evaluate scientific claims by going through a checklist of considerations.
Why should one not attempt to answer all the questions on the checklist?
-One should not attempt to answer all the questions on the checklist because it is not appropriate or necessary for every situation, and the checklist serves more as a source of ideas for evaluation rather than a comprehensive set of questions to be answered.
What are the three criteria that a claim must meet to be considered scientific?
-A claim must be rational, testable, and repeatable to be considered scientific.
What types of scientific inquiry are mentioned in the script?
-The types of scientific inquiry mentioned are observational, descriptive studies, hypothesis-driven experiments, and the development of models and theory.
Why is it important to understand the type of scientific inquiry when evaluating a claim?
-Understanding the type of scientific inquiry is important because different types of inquiry use different rigorous methods, and knowing the type helps determine if the steps taken are appropriate for that type of inquiry.
What role does evidence play in evaluating scientific claims?
-Evidence, which consists of the data collected during scientific inquiry, plays a critical role as it supports or refutes the claims being made.
Why is the presentation of evidence important?
-The presentation of evidence is important because it can influence the conclusions drawn from the data, especially when graphical representations are used, which can skew interpretations if not appropriate.
What is the significance of units in numerical evidence?
-Units are significant in numerical evidence because a number without units lacks context and meaning, affecting the interpretation and decisions based on that data.
How can one determine if a conclusion is valid based on the evidence presented?
-One can determine if a conclusion is valid by checking if it logically follows from the evidence and does not make leaps that are not supported by the data.
What is the difference between correlation and causation as it relates to scientific claims?
-Correlation refers to two variables changing in relation to each other, while causation implies one variable causes the change in the other. It's important not to confuse the two, as correlation does not necessarily imply causation.
Why is it important to consider the expertise of the person making the scientific claim?
-The expertise of the person making the claim is important because an expert in the relevant field is more likely to make accurate and informed claims about a subject.
What are some red flags to look for when evaluating a scientific claim?
-Red flags include conflicts of interest, economic motivations, and references to secrets, conspiracies, or special hidden information that require payment to access.
How should one approach the case study on spa treatment claims in the workshop?
-One should approach the case study by reviewing each part, taking notes, and considering the questions and checklist items relevant to that part before moving on to the next.
Outlines
🔍 Evaluating Scientific Claims
The paragraph discusses a workshop aimed at teaching non-scientists how to evaluate scientific claims. It introduces a checklist to consider when assessing such claims, emphasizing that not all questions on the checklist need to be addressed for every situation. The focus is on determining whether a claim meets the criteria of science, including rationality, testability, and repeatability. The paragraph also highlights the importance of understanding the type of scientific inquiry (observational, descriptive, or hypothesis-driven) and whether the methods used were rigorous and appropriate. The workshop encourages participants to think critically about the evidence presented, the collection process, and the logical flow of the claims.
📊 Analyzing Evidence and Inferences
This section delves into the critical analysis of evidence and the inferences drawn from it. It stresses the need to evaluate the type and quality of evidence, such as its sufficiency and the rigor of its collection. The paragraph warns against hastily accepting conclusions that seem to skip logical steps or lack a clear connection to the evidence. It also addresses the importance of considering how evidence is presented, including the appropriateness of graphical representations and the clarity of data presentation. The summary points out the potential for overgeneralization and the common mistake of confusing correlation with causation, using historical examples to illustrate the pitfalls of these errors in reasoning.
🕵️♂️ Considering Expertise and Potential Biases
The final paragraph of the script focuses on additional factors to consider when evaluating scientific claims, such as the expertise of the claimant and potential conflicts of interest. It advises participants to be wary of claims made by individuals outside their field of expertise or those with ulterior motives, like economic gain. The paragraph also cautions against claims that rely on secrecy or conspiracy theories, suggesting that such elements are red flags for potentially dubious claims. The workshop concludes with instructions for participants to apply these considerations to a case study on spa treatments, encouraging a thoughtful and critical approach rather than a checklist式的 response to every aspect of the study.
Mindmap
Keywords
💡Scientific Claims
💡Rational
💡Testable
💡Repeatable
💡Scientific Inquiry
💡Evidence
💡Inferences
💡Correlation vs. Causation
💡Expertise
💡Conflicts of Interest
💡Case Study
Highlights
Workshop focuses on evaluating scientific claims for non-scientists.
Participants are guided through a checklist for evaluating scientific claims.
The importance of determining if a claim meets the criteria of scientific inquiry is emphasized.
Claims should be rational, testable, and repeatable to be considered scientific.
The necessity of a logical flow in scientific explanations is discussed.
Participants are advised to consider the type of scientific inquiry and its methodology.
The presentation of evidence and its collection process is a critical aspect of evaluation.
The quantity and quality of evidence supporting a claim are important to assess.
The presentation of evidence, such as graphs and tables, should be appropriate and clear.
Units of measurement are crucial for understanding numerical evidence.
Inferences and conclusions should logically follow from the presented evidence.
Consistency with other studies strengthens the validity of a scientific claim.
Overgeneralization from limited evidence can lead to incorrect conclusions.
The difference between correlation and causation is a common pitfall in scientific claims.
Expertise in the relevant field is important when evaluating the credibility of a claim.
Conflicts of interest or economic motivations can influence the objectivity of a claim.
References to secrets, conspiracies, or hidden information should raise skepticism.
The case study method will be used to apply the evaluation process to a spa treatment claim.
Participants are encouraged to take notes and reflect on each part of the case study before proceeding.
A single discussion board post summarizing thoughts on the case study is required.
Transcripts
so in this workshop we're going to talk
about how you as non-scientists can
evaluate scientific claims we're going
to be going through a checklist of
things that you can think about but as
you work through the case study that
we're going to be using for this
workshop don't try to answer all of
these questions it's not even an
appropriate thing to try to do
one of the things that this checklist is
useful for is to give you a lot of ideas
to think about and evaluate and some of
these types of items are going to be
more relevant than others to specific
situations
so one of the first things that you
always want to do whenever you're
evaluating scientific claims is decide
is this science does it meet the
criteria
of a scientific inquiry or of a
scientific claim so is it focused on
explaining something about the natural
world remember that's what science is
trying to do and does it meet those
three criteria of being rational
testable and repeatable so is it trying
to invoke any kind of supernatural
entity not going to fit that rational
criteria is there a logical flow to the
explanation that you've been given or
does it seem to kind of skip some steps
and it goes from step a and then there's
something mysterious then it suddenly
reaches a conclusion you're not quite
sure where that conclusion came from
well then it's missing that rational
criterion as well
is the investigation following a
rigorous methodical process remember
there's three main types of scientific
inquiry we have observational
descriptive studies we have
hypothesis-driven experiments we have
development of models in theory and
those are all valid types of scientific
inquiry but they all are going to have a
rigorous method that they are using
where individuals are documenting the
steps that they're taking so that other
people can come in and try
replicating those steps and seeing if
the two sets of evidence that they
collect are compatible with each other
so
have you been presented with how
particular pieces of evidence were
gathered what steps were taken
to
perform this particular type of
scientific inquiry and what type of
scientific inquiry was it and does it
seem like the steps are appropriate for
that type of inquiry
then we're going to look at two
things that are both critical to
anything that you've decided yet seems
on the surface to be a valid type of
scientific inquiry we then need to look
at the evidence that that inquiry has
gathered the facts that have been
collected and then finally we'll look at
the inferences that are made from those
evidence
so the evidence that gets gathered is
facts this is the data that is collected
in the process of performing a
scientific inquiry and sometimes when
you're presented with a scientific claim
you're told what evidence supports that
claim and sometimes pieces of that
evidence might be missing so you want to
look at what type of evidence are you
given to support this claim is there
enough detail that you're given about
how it was collected or was an adequate
amount of evidence collected or did they
just go and talk to like one person and
get their opinion and that was their
entire bit of evidence
not going to be so
rigorous a claim in that case or are
there lots and lots and lots of
different types of evidence collected
from different sorts of sources and if
they all support a particular claim that
is going to strengthen the evidence for
that claim
and then you want to think about how
evidence is presented go back and look
at the topic lecture where it showed you
how
the way data is presented in graphical
form for example can very much skew the
conclusions that you're going to draw
even if it's relying on the same set of
data so you want to look at if a graph
is used is it appropriate for the type
of data a line graph for example isn't
appropriate if you're looking at
categorical data but if you're looking
at something where they've collected
like daily temperatures over a period of
time then a line graph might make some
more sense
if a table is used is it understandable
are you given units and clear labels
units are super super important because
a number without units doesn't really
have any meaning think about if someone
were to tell you you've won 10.
okay
i've won 10 is that 10
10 000 or 10 million dollars because the
decisions that i am going to make are
going to vary widely depending on
whether we're looking at 10 10 000 or 10
million dollars
so units are always a critical aspect of
any type of evidence that you are
presented that is numerical
and if you're looking at any kind of
graphic are the scale on those graphs
appropriate and are they labeled so
those are all the kind of things that
you might ask about the evidence but you
aren't necessarily going to ask every
single one of these questions you want
to think about what information you're
being given and what are the most
relevant questions for that and then in
contrast you want to then look at the
inferences the conclusions that are
being presented based on the evidence
that is available
and first thing you always want to ask
yourself is does it seem like that
conclusion
makes sense given the evidence you don't
want to have oh the daily temperature
has varied between
65 degrees fahrenheit and 90 degrees
fahrenheit so i think you should invest
a thousand dollars in this particular
stock
that is okay there's some evidence that
you've given me what the daily
temperatures were but where the heck did
that conclusion about why i should
invest money in this particular stock
come from that doesn't derive from that
set of evidence that you've been
presented
and then how well
do the particular claims from
one scientific
inquiry fit with other studies that are
on the same topic if you have lots of
studies done by different groups and
different people and they all are
kind of consistent with each other
that's going to be a stronger conclusion
than if there's one kind of random group
that has
a conclusion that's very very different
from what all the other people studying
that same issue have come up with
do we have inferences that have over
generalized so
if for example i look at the high
temperatures in orange county over the
past week i might come up with very very
different conclusions if i'm looking at
those numbers in january versus in june
versus in late august very very
different conclusions if i'm then saying
and this is what the
climate is like in southern california
well if it's one of those cold weeks in
january you're going to have a really
different conclusion about southern
california climate than if it's one of
those hundred degree weeks that we get
in the summer we're all buying
really really vastly different
conclusions just based on
over generalizing from a small sample
and that is a very easy example to think
of but that can often happen with
scientific claims that get presented to
you
and then finally we want to think about
is that inference confusing correlation
with causation and correlation is
two variables two things are
changing at the same time in ways that
seem to be related so maybe they're both
going up or they're both going down or
when one goes up the other one goes down
but there seems to be a pattern
and oftentimes when you have a
correlation like that people assume that
that means one of those things is
causing the other one to also move
and that rarely is the case
correlation
doesn't necessarily mean that those two
things are
related in a causal relationship where
one thing is causing the other thing to
go up or to go down and there's a very
classic case of this after world war ii
comparing
automobile tire sales with
number of births that were recorded in
japan
and they both tended to go up over a
consistent period of time in japan after
world war ii
and if you were going to
confuse correlation with causation here
you might say purchasing automobile
tires causes you to have a baby and all
of us can think about that and go
obviously not purchasing automobile
tires does not cause you to have a baby
and what it really was is that both of
those two factors were tied to a third
factor which is the war had ended the
economy was booming people were very
happy that the war had ended and we're
now getting to be back together so there
were many babies that were born that is
the source of all of those boomers that
we all have to deal with
and they were also
having a whole lot of economic growth
and so many people were able to purchase
automobiles and you need to have tires
in order to have an automobile so the
booming post-war economy was what was
leading to both births and purchase of
automobile tires going up and not
purchasing automobile tires causes you
to have a baby
so that's one thing to think about
correlation versus causation oftentimes
when you're looking at two things and
they're correlated
but they don't appear to be causing each
other there's some third thing that is
causing them both to change in whatever
way they are changing
and then there's some random things that
kind of collect together you can
evaluate whether something is scientific
you can evaluate the evidence you can
evaluate the inferences and then there's
this kind of random collection of stuff
is the person who is making the claims
an expert in the appropriate field so
is an expert in disease epidemiology for
example making claims about covid
transmission or is it somebody who was
an expert in say
astrophysics or
ophthalmology or something else that's
not related to disease transmission of
viral diseases
think about the expert and whether they
are an expert in the correct kind of a
field to make those claims that they are
making
are there any kind of conflicts or
interests or is there especially any
economic interest is someone trying to
get you to spend money
and that's why they're making a
particular claim and then finally
is there any reference to secrets or
conspiracies or special hidden
information especially something where
if you just give me some money then i
will be showing you that special secret
information that should be sending up
not just a red flag but all the red
flags that this claim might be a little
suspect
and so all of these things are the kind
of questions that you might ask yourself
again don't try to ask every single one
of these questions for every single
claim but that's giving you some ideas
about the kind of things you want to be
thinking about as you get presented with
different types of claims
and what you're going to do in this
workshop is use a case study and the
case study files are presented to you on
canvas in four parts
and it's a case study on a spa treatment
and the claims that are made about what
this treatment does and how it works
it's broken into four parts and i really
recommend that you do each part and take
notes on that part before moving on to
the next part
you're going to be creating a
single discussion board post for this
that's going to be about a paragraph so
again you're not going to be able to go
through every item on the checklist that
we just reviewed
and each part of the case study has some
kind of thought discussion questions for
you to think about
but you're not going to try to answer
all of those
the checklist that we've just gone
through and the questions that you'll
see on the case study are to kind of
help get you thinking about what you'd
like to write about that particular part
so don't worry about trying to answer
everything don't worry about trying to
go through the entire
set of checklist questions because that
would be pages and pages of material and
i want you to have a single fairly short
paragraph
and so
i now recommend that you either listen
to this recording again or that you go
on to canvas and pull down that first
case study file and complete that and
the instructions on canvas will give you
a little more guidance
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