Science Study Guide for the TEAS

Scientific Reasoning

Scientific reasoning questions on the TEAS 7 are designed to evaluate your ability to answer questions and problems using scientific methods and inquiry. Focused on different areas of science, these questions require the use of logic and reason to find the correct answer. They may be presented as a word problem, requiring scientific knowledge and math skills to respond accurately.

Scientific Measurements and Measurement Tools

To collect data, lab measurements are required. The nature of these measurements will depend on the question that is asked. Tools such as thermometers and scales might be used to determine the effect of temperature or weight, for example. For these measurements to be reliable and useful, it is important that they are carried out in a methodical way. It is important to be able to identify different lab measurements and the tools with which they would be carried out.

Metric Units

The metric system of measurement (abbreviated as SI for Système International) is widely used in scientific and medical settings. Each basic unit (e.g., meter, gram, liter) is enlarged or reduced by a multiple of 10 using a certain prefix. Numerically, measurements can be expressed in alternate units by moving the decimal point to the left or right.

Measures of Length
1 meter (m)	= 1,000 millimeters (mm)
1 meter (m)	= 100 centimeters (cm)
1 kilometer (km)	= 1,000 meters (m)
1 decimeter (dm)	= 1/10 meter (m)
Measures of Mass
1 gram (g)	= 1,000 milligrams (mg)
1 kilogram (kg)	= 1,000 grams (g)
Measures of Liquid Volume
1 liter (L)	= 1,000 milliliters (mL)
1 deciliter (dL)	= 1/10 liter (L)

Accuracy in Measurement

Accuracy reflects how close a measurement comes to the actual value of what is being measured. Different tools have different methods for accurate measurement. For example, to measure length on the ruler below, you would place the object at 0, then use the centimeter markings and then the millimeter markings to get the most accurate measurement.

Retrieved from: https://commons.wikimedia.org/wiki/File:Ruler_with_millimeter_and_centimeter_marks.png

Dimensional Analysis

Dimensional analysis refers to calculations used to convert from one set of measurement units to another, for example from seconds to minutes or from meters to kilometers.

Choosing a Measurement Tool

Choosing the correct measurement tool is essential to getting an accurate measurement. The tool will vary depending on the dimension you are measuring and the accuracy required.

Measuring Length

Measuring length requires the use of a ruler or tape measurer. The units are typically centimeters or millimeters.

Measuring Volume

To measure liquid volume accurately, a graduated cylinder is most often used, with mL as the units. Larger amounts of liquid can be measured in a beaker, though with less accuracy.

Glass Measuring Tools

When measuring liquid volume in a glass graduated cylinder, the water tends to climb up the sides of the cylinder to create a meniscus. To read volume accurately, measure the volume at the bottom of the meniscus, at eye level.

Retrieved from: https://psu.pb.unizin.org/eshanichemistry110/chapter/measurement-uncertainty-accuracy-and-precision-1-5/

Balances

A triple-beam balance consists of a platform, where the sample being measured is placed, and three counterweights of different values. The weights are moved until they balance out the sample, and the combination of values gives the mass of the sample, usually in grams or kilograms. Electronic balances can be used to measure samples more accurately.

Choosing the Appropriate Scale

The measurement scale you use will depend on the item you are measuring and its projected value. It is best to communicate results in terms that are relatable. For example, we would likely be more comfortable saying a sample is 5 g rather than 0.005 kg. The metric system allows an easy transition between units of measurement.

Applying Logic and Evidence to Explanations

In any branch of science, you must be able to make decisions based on evidence and logical thinking. Especially in the health field, there are many myths and false claims that can be perpetuated on the internet that are not based on scientific data. It’s important to be able to evaluate such claims in terms of their scientific basis.

Drawing Conclusions

Conclusions should be based on evidence that was gathered in a systematic and scientifically sound manner. A true scientific conclusion should be backed up with data and should not contain any inference or conjecture about things not directly measured.

Finding Cause-and-Effect Relationships

In science, it is important to identify cause-and-effect relationships. Two variables may correlate, that is, occur at the same time, but that doesn’t always mean that one causes the other. For example, people believed that the stagnant air in swampy regions caused the disease malaria because those two incidents correlated. But what was actually causing the malaria was mosquitos, which were more often found in swampy regions.

Evaluating Evidence

It’s important to examine the evidence behind any scientific claim. If the evidence is incomplete or was obtained in an unreliable way, that casts doubt on the conclusion drawn from that evidence.

Reliability of Evidence

Reliable evidence will avoid the possibility of bias. Sometimes experiments are double-blind, meaning neither the subjects nor the experimenters know what variable is being tested so as to rule out any unconscious bias toward or against the data being gathered. In medical trials testing new medications, one group will be given a placebo (a substance without the actual medication in it), so that no one knows who is actually getting the medicine.

Design of Experiment

To gather reliable data, an experiment must have a large sample and/or include multiple trials run the same way. This helps determine whether the same results develop consistently, or whether they are influenced by some other factor.

Independent Variable—Only one variable should be changed by the experimenter at a time. This is called the independent variable.

Control Variable—The control variables, also called constants, are variables in the experiment that should be kept the same with each trial. Any variable besides the independent variable should be accounted for in the experiment.

Making Predictions

The more information that is gathered about a topic, the more accurately scientists can make predictions about likely outcomes. A prediction that has not been thoroughly tested yet is known as a hypothesis. A hypothesis is made based on prior knowledge and tested during a controlled experiment.

Magnitude

In determining cause-and-effect relationships and making predictions based on them, it’s important to consider the magnitude of the prediction. For example, let’s say that medication A causes side effect B in a number of patients in a clinical trial. One could make a prediction about the number of people in the general population that will experience that side effect when they take medication A.

Causal Relationships

There are three basic rules to determine if the relationship between two variables is causal or not. First is sequencing: A is always followed by B. The second rule is that the relationship between A and B can’t happen due to chance. And finally, there are no other variables that can explain the relationship between A and B.

Using Sequence

A thorough investigation of the sequence of events can help establish a causal relationship and make sure there are no variables unaccounted for.

The Scientific Method

A key scientific reasoning concept to know is the scientific method. The scientific method involves six specific steps: problem identification, question asking, hypothesis development, data collection, analysis, and conclusion. The first two steps help us to formulate the hypothesis. Data collection involves the collection of facts through a scientific method, in a controlled environment, to test the hypothesis. In the analysis step, the data are analyzed to see if they support the hypothesis. The conclusion states whether the data analyzed are consistent with the hypothesis.

Hypothesis

A hypothesis is a proposed answer to a testable question. A hypothesis can be tested through research and/or experimentation. You should be able to identify a relevant hypothesis based on a given investigation. A hypothesis can often be stated as an if/then statement describing the predicted effect of the independent variable on the dependent variable.

Experimental Design

A good experimental design will test one variable at a time (the independent variable) and hold all other variables constant. There should be an adequate number of trials to dilute the effect of chance events on the outcome. The sample size should be large to gather the most comprehensive data possible.

Variables and Controls

It’s important to identify the independent variable and to make sure that is the only variable that is changed on purpose in the experiment. For comparison, a control group to which the independent variable is not applied may be necessary in an experiment. A group receiving a placebo medication would be an example of a control.

Independent Variables

The independent variable is changed deliberately in the experiment. There may be several levels of the independent variable being tested, such as having groups take different doses of the same medication to see which is most effective.

Dependent Variables

The dependent variable changes in response to the independent variable. It is the variable of interest that will be measured during the course of the experiment. If a medication was being tested to increase bone density, the medication would be the independent variable and the bone density of the patients would be the dependent variable.

Constants

For an experiment to be valid, any other factor that could affect the dependent variable needs to be accounted for and held constant. This is essential in establishing that causal relationship mentioned earlier.

Plotting Results on a Graph

When creating or viewing results on a graph, the independent variable is typically on the \(x\)-axis, while the dependent variable is plotted on the \(y\)-axis. The constants are not included, since they remain the same.

Final Analysis

After an experiment has been performed, the data must be analyzed. Any potential errors in the experiment must be identified, and any invalid data resulting from errors may be removed. Statistical analysis may be performed to determine whether the changes in the dependent variable are statistically significant.

Accept or Reject?

If the data does not support the hypothesis being tested, the hypothesis must be rejected. A new hypothesis may be created based on the results of the experiment. If the data supports the hypothesis, further testing will strengthen it.

Peer Review

Scientists must submit their work to be reviewed by other scientists. Science is a social endeavor, and by allowing others to evaluate and attempt to replicate their work, scientists can be more certain of their outcomes.