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General Science PRAXIS 5435 Exam | Questions And Answers Latest {} A+ Graded | 100% Verified

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General Science PRAXIS 5435 Exam | Questions And Answers Latest {2024- 2025} A+
Graded | 100% Verified


Identifying problems based on observations - Causal question—what am I seeing, what hypothesis might
I test to learn more information about what I am seeing?



Forming and testing hypotheses - Hypotheses make a prediction about what will happen upon
experimentation, but will not make inferences as to why something is happening. I.e. As amount of
physical exertion increases, heart rate will increase.



Development of theories, models and laws - A theory is a thoroughly vetted explanation for phenomena.
It is not a name taken lightly, it is almost fact; no evidence has arisen to disprove the theory. A model is
a type of theory that attempts to explain how something works. I.e. heliocentric model. A law is a theory
that has been proven to be fact, such as the laws of motion. It has been affirmed that no evidence will
ever be brought forward to disprove a law. Hypotheses become theories as they are tested and
supported over time. Theories become laws when it is clear no evidence will come forward to disprove
them.



Experimental design, including independent and dependent variables, controls, and sources of error -
The independent variable is the one and only thing about an experimental setup that I am changing, in
order to measure a dependent variable. I.e. I change the amount of exercise, and heart rate changes as
a result. Controls are what stays the same in my experiment. I.e. how quickly I do jumping jacks, how
many jumping jacks I do, that the same person is doing the jumping jacks. Sources of error include
anything that may be changing data that is uncontrolled. I.e. food calorimetry lab, not all heat is being
captured efficiently by the water.



Process skills including observing, comparing, inferring, categorizing, generalizing, and concluding -
Observing; making observations and asking causal questions.

Comparing; evaluate two phenomena in light of each other

Inferring; using evidence to offer an explanation of why something is happening

Categorizing: using observations to organize information

Generalizing: knowing what can and cannot be included in a generalization

Concluding: drawing conclusions based on experimental evidence.

,Nature of scientific knowledge: subject to change - As new evidence is gathered, previous conclusions
may change to fit the evidence. We can't know things until we make hypotheses, and those hypotheses
may be disproven.



Nature of scientific knowledge: consistent with evidence - We cannot call something a scientific finding
unless it is based on experimental evidence; anecdotal evidence is insufficient.



Nature of scientific knowledge: based on reproducible evidence - Evidence has to be reproducible in an
experimental setting. A one-time phenomenon is not enough to come to scientific conclusions. I.e. "I
drank a soda and did well on my exam" does not make drinking soda a tried and true way to do well on
an exam; it needs to be experimentally tested.



Nature of scientific knowledge: includes unifying concepts and processes (e.g., systems, models,
constancy and change, equilibrium, form and function) - Consistent with previous knowledge. Fits with
other systems and models. Is able to be disproven and/or modified.



Common units of measurement (metric and English) including unit conversion and prefixes such as milli
and kilo - Kilogram (kg) -- .5 kg in 1 pound

Second (s)

Kelvin (K)

Meter (m) - 0.3 m = 1 ft

Liter (L) - 0.9 L in 1 quart



Unit Prefixes from largest to smallest:

Giga

Mega

Kilo

Deci

Centi

Milli

Micro

Nano

, Pico

Femto



Organization and presentation of data - Bar graph to compare numbers in different groups.

Line graph to look at data over time.

Pie chart to compare parts of a whole.

Histogram to compare continuous numerical groups.

Dot plot a modification of bar graphs.

Labels on axes.



Basic data and error analysis including determining mean, accuracy, precision, and sources of error -
Mean: total divided by number of groups/individuals. Accuracy: correct results. Precision: same results
repeatedly. Sources of error: Why does my data not look how it should?



Trends in data - Skewed? Right or left? Continuous growth or shrinking?



Relationships between variables - Correlation vs. causation. We often cannot conclude causation.



Predictions based on data - What will happen in the future? What could cause a change in the data?



Drawing valid conclusions based on data - Drawing correlations between variables while accounting for
any error or confounding factors.



Appropriate and safe use of materials (e.g., chemicals, lab specimens) - Always read safety labels, and
have access to the SES sheet.

If chemical is labeled as "harmful when inhaled" it must only be used in a fume hood. Gloves must be
worn for any chemical that is an irritant or corrosive.

Glass, heat, or chemicals require the use of safety goggles.

Always label all beakers.

Store specimens properly according to handling notes.

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