Download Scientific Investigations Notes Questions Notes: Screen 1: Welcome

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Scientific Investigations Notes
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Screen 1: Welcome
Welcome to the lesson, "Scientific Investigations." In this lesson,
you'll explore how scientists collect data and make observations.
The vocabulary words for this lesson are experiment, hypothesis,
independent variable,
dependent variable, observation, data, and constant.
Click each word to learn more about it.
Screen 2: Experiments
What do you imagine when you think of a scientific investigation?
Most of us picture a scientist conducting an experiment in a sterile
laboratory.
In reality, a scientist can be anyone, and many scientists perform
their experiments outside of a lab.
An experiment is an organized procedure to study something under
controlled conditions.
Screen 3: Types of investigations
Not all scientific investigations are experiments.
Scientists can also learn about the natural world in many other ways.
Click the images to explore different types of scientific investigations.
In a laboratory, scientists have complete control over things like
temperature, heat, humidity, and light.
Laboratory experiments allow scientists to make precise observations
because more factors are in their control.
Chemists often perform their experiments in a laboratory.
Sometimes, a lab is not the best place for an experiment.
This scientist is working with plants in a greenhouse instead of in a
laboratory.
For this type of experiment, a greenhouse is better than a lab
because it allows scientists to control certain conditions
while recreating conditions that are closer to nature than the
conditions inside a lab.
Many scientific investigations happen in the field, where scientists
can't control the factors around them.
In the field, scientists make observations and collect data to study
natural phenomena.
This volcanologist is collecting lava samples to learn more about
volcanoes.
Some scientists use computer models for their investigations.
A computer model of the climate allows climatologists to control all
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the factors that affect the model's climate.
Changing one factor in the model tells us what effect that factor
might have on the climate.
Screen 4: Scientific processes
Scientists follow a series of steps when performing an investigation.
Click the images on the right to learn about these steps.
A soil scientist discovers that soil in a particular region is lacking
certain nutrients.
The scientist hypothesizes that a certain type of crop will grow much
better in the region's soil than the crops that grow there now do.
Local farmers are interested in finding out which plants might grow
better in that soil type.
To test a hypothesis, scientists adjust and test only one factor in an
investigation.
Adjusting one factor at a time allows scientists to see the effect that
factor has on the other factors in the investigation.
The factor that's changed is called the independent variable.
The factors that are affected by the change are called the dependent
variables.
Changes to the dependent variables are recorded.
Certain factors in an investigation remain unchanged.
These are called constants.
Don't confuse a constant with a control.
A control is a trial in an investigation in which the independent
variable is not changed.
It is used to ensure the investigation results are caused by the
change to the independent variable,
and not some other factor.
The soil scientist collects several soil samples from a field.
The scientist grows different species of crop plants in the soil to see
which species grows best.
For this investigation, the independent variable is the plant species.
The dependent variable is the plant growth.
Some of the constants are soil type, the amount of water given the
plants, and the temperature.
A control is not needed in this investigation.
Trials are repeated several times using sample sizes that are large
enough to ensure the results are reliable.
Scientists need the appropriate equipment and technology to collect
and interpret data.
They can use a computer program to organize data into a chart,
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making it easier to examine, or interpret, the data.
After collecting and interpreting data, scientists then analyze that
data.
By comparing the results of the growth of the different plant species
in the soil,
scientists identify one species that grows best in the nutrient-poor
soil.
After analyzing the information, scientists make conclusions.
In this investigation, the data gathered supported the soil scientist's
hypothesis
that one particular species of crop plant would grow better than
others in the region's nutrient-poor soil.
The scientist tells the farmers that barley is a plant that grows well in
their particular soil type.
After performing an investigation, scientists share their results.
Part of the peer review process might involve replication of the
investigation by other scientists.
Replication helps to validate results obtained from the original
experiment.
Screen 5: Types of investigations
You've learned that there are different types of scientific
investigations.
Now, see if you can match each type of scientific investigation with its
description.
Drag the term to its matching description.
Great job!
You've identified the different types of scientific investigations.
Scientists decide which is the best type of scientific investigation to
use based on what they are studying.
Screen 6: Variables
A scientist tested how acid precipitation affects the percentage of
salamander eggs that hatch.
The pH level of the water is the independent, or test, variable.
The percentage of eggs that hatch is the dependent variable.
This is also called the outcome variable.
Click to see how pH affects the development of salamanders.
Fewer eggs hatched when the pH level of the water was low.
Many of the salamanders that did survive were born deformed or with
stunted gills.
With the pH of the water near neutral, almost all of the eggs hatched.
Fewer eggs hatched when the pH level of the water was high.
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Screen 7: Errors
How do scientists know their results are reliable?
One way is by making sure that they identify and then account for
experimental error in their investigations.
An experimental error is the difference between the recorded
measurement and the measurement's true value.
Experimental errors are caused by taking measurements.
They can be caused by using tools that are calibrated imprecisely,
by incorrect reading of the measurement by the user,
or by the small imprecision in the tools that cause measurements to
vary slightly above or slightly below the true value of the
measurement.
Click the images to learn more.
Sources of experimental error include incorrect calibration of
equipment or incorrect reading of the measurement by the user,
such as reading the volume of a liquid in a beaker from the wrong
angle.
Accuracy measures how close a measured value is to the true value.
Precision measures how closely two or more measurements are to
each other.
Calibrations of tools help make them as accurate as possible.
Experimental errors can be accounted for during the data analysis
stage.
Another type of error, different from experimental error, is called
design error.
Design errors have to do with problems in the design of the
experiment.
Design errors include lack of a control when one is needed, an
inadequate sample size, too few trials, and having more than one
independent variable.
So how do you eliminate experimental errors?
You might pre-test the accuracy of an instrument such as a pH meter
by calibrating it with solutions of known pH values.
Or, you might calibrate a balance scale by measuring masses of a
known weight.
Also, choosing the appropriate tool for the job is important.
However, even being as careful as possible, it is sometimes difficult to
avoid experimental error.
Occasionally, small inaccuracies in measurements caused by the tools
used might occur.
If enough small inaccuracies occur during an experiment, these can
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really add up.
But scientists can take these inaccuracies into account during data
analysis.
Before starting an experiment, scientists plan their investigations to
avoid design errors.
Scientists determine an adequate number of trials to perform,
adequate sample sizes, and whether the experiment requires a
control.
They also make sure that their experiment only has one independent
variable.
Screen 8: Good investigations
Not all science is good science.
How do you evaluate the quality of a scientific investigation?
Click the pictures to learn more.
Scientists perform multiple trials in the same experiment.
They use sample sizes large enough to ensure reliable results.
In an experiment studying the nutrient content of soil in a certain
field,
a scientist would take multiple samples from different parts of that
field.
If the scientist had performed only one trial, his results would not
have been representative of the entire field.
Scientists should communicate with one another about their
investigation's processes and results.
Other scientists may have valuable knowledge to add to an
investigation, or find mistakes in certain processes.
To make sure the results of an investigation are accurate, a different
scientist should replicate the same investigation.
If the scientist replicating the investigation has different findings,
it's possible the original investigation will need to be redone.
Scientific information is all around us, in magazines, newspapers,
even on the Internet.
To make sure the information you find is accurate and reliable, look to
the source of the information.
Research papers in scientific journals are reliable because many
scientists
and content experts review them before they are published.
Scientific magazines are also reliable sources because content experts
often write the articles.
Science articles in newspapers, magazines, and news websites are
often written by people who do not have a background in science,
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so these would be a less reliable source of science information.
Screen 9: Identifying sources of error
You have learned ways that scientists try to minimize sources of error
in an experiment.
The setup shown here is an experiment studying the rate of
photosynthesis of a specific type of plant.
Can you identify the ways in which the setup of this experiment helps
to minimize design and experimental errors?
Drag the label to its matching part in the correct location.
Way to go!
You have correctly identified the parts of an experimental setup that
minimize error in an experiment.
Using an adequate sample size, including a control, and identifying
one independent variable all help to minimize design error.
Using accurate measuring tools minimizes experimental error.
Screen 10: Hypothesis
An astronomer has observed a new object near a star.
Which statement is a hypothesis the astronomer can make based on
this observation?
Click the correct answer.
That's not it, but try again.
That's not it, but try again.
That's not correct. Try again.
Good job!
Based on his observation the astronomer can hypothesize that the
object is a new planet.
He and other scientists would investigate further to test this
hypothesis to see if it is correct.
Screen 11: Identifying variables
You are studying a certain ant species and its food preferences.
You've collected part of an ant colony and set up a habitat in your lab.
You've placed different types of food at equal distances from the ants'
mound.
The distance to each food is a constant, and so is the ant species.
You decide to measure food preference based on the number of ants
that visit each food type in a certain period of time.
What are the independent and dependent variables in your
investigation?
Your independent variable is the food type.
You are varying the food type so that you can see whether food type
has an effect on the number of ants that visit.
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The number of ants visiting each food type within a certain period of
time is your dependent variable.
Screen 12: Summary
You've learned a lot about how scientists perform investigations.
Before we finish, let's take a quick look at the main points you
covered.
Scientific investigations can involve experiments, models, and
observations.
The processes in an investigation include observing, hypothesizing,
experimentation, analysis, and communication.
Good investigations have large sample sizes, repeated trials, and are
replicated by other scientists.
Now that you've finished this lesson, if you wish, you can go back and
review any part of the lesson again.
Summary