Data Table
Setup 1
Test tube
A
B
C
D
E
F
Color of Liquid
Amount of Liquid (ml)
Total liquid from test tube A to F:
Setup 2
Test tube
A
B
C
D
E
F
Color of Liquid
Amount of Liquid (ml)
Total liquid from test tube A to F:
Amount of remaining liquid in each Erlenmeyer flask:
Red:
Blue:
Yellow:
Amount of remaining liquid in each 50ml beaker:
Setup 1
Red:
Blue:
Yellow:
Guide Questions:
For each setup:
1.
2.
3.
4.
Setup 2
Red:
Blue:
Yellow:
Comparing the Setup:
1.
2.
Reflections:
1.
2.
Conclusions:
Data Table
Setup 1
Test tube
A
B
C
D
E
F
Color of Liquid
Amount of Liquid (ml)
Total liquid from test tube A to F:
Setup 2
Test tube
A
B
C
D
E
F
Color of Liquid
Amount of Liquid (ml)
Total liquid from test tube A to F:
Amount of remaining liquid in each Erlenmeyer flask:
Red:
Blue:
Yellow:
Amount of remaining liquid in each 50ml beaker:
Setup 1
Red:
Blue:
Yellow:
Setup 2
Red:
Blue:
Yellow:
Guide Questions:
For each setup:
1. The volume of liquid in each test tube is roughly 10ml, with minor variations observed.
Additionally, it is possible to generate new colors, such as green, by combining the
colors blue and yellow.
2. It is important that the volume contained within each flask is consistent, specifically
10 ml. Any inaccuracies or miscalculations throughout the measuring process would
result in differences in the liquid quantities present within the respective test tubes.
3. It is possible that systematic errors may occur. Improper measurement of measuring
devices, such as pipettes and beakers, has the potential to induce systematic
inaccuracies. If a pipette repeatedly deviates from its expected liquid delivery volume,
this error will exhibit consistency.
Random error refers to the variability or deviation observed in the measurements.
This type of error is inherent in any process of pouring or transferring liquid and may
result in minor variations in the quantity distributed on each occasion.
4. The presence of stains may indicate the potential presence of hazardous substances,
such as acids, which may have been accidentally spilled and come into contact with
the skin. This emphasizes the importance of obeying safety protocols while handling
chemicals.
Comparing the Setup:
1.
We can tell that our setup is right because the color and specs are the same. But we
can't say that it also shows precision because the two sets used different pouring
techniques. This makes it possible for the measured amounts to be different between
the two sets, which is why some of the colors in the picture don't have the same
amount.
2. Yes, the chance of different calibration in each pipette or beaker caused our group to
have more or less volume. This meant that we could see different measurements in
each test tube.
Reflections:
1.
It's important to measure things like flour, water, and spices very carefully if you want
reliable and tasty results in the kitchen. The skills you learned in your experiment can
help you follow recipes more correctly.
2. No, they have nothing to do with measuring, calibrating, and validating data from the
action we did. Mathematical measurements have nothing to do with gender, race,
language, etc.
Conclusion:
Before we started the experiment, our teacher told us how important accuracy is in
science. We were given samples of different liquids, each of which had its own color,
viscosity, and density. Our job was clear: we had to measure and pour these liquids
into test tubes as accurately as possible. We quickly understood that this activity
would only work if everyone in the group worked together and talked to each other.
While one person held the test tube steady, another carefully poured the liquid in, and
someone else took the measures. It was a symphony of movement and attention, and
it helped us all work toward the same goal. During the action, it became clear how
important accuracy is. The results could be different if a millimeter was added or
taken away. We got better at noticing things, learned how to find the meniscus, and
checked our measures twice.