HLT 540 Grand Canyon Week 2 Discussion 1

What kinds of extraneous variables (not cited in the studies) do you think could have affected the relationships between the independent variables and the dependent variables in both the Messina et al. and Coyne et al. studies?

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Extraneous variables

Introduction

In scientific experiments, we want to control for all factors except the ones we are testing, so that we can be sure the results of our experiment are due to the factors that we are investigating. In an experiment conducted in a laboratory, the following might be extraneous variables:

In scientific experiments, we want to control for all factors except the ones we are testing, so that we can be sure the results of our experiment are due to the factors that we are investigating.

When you are conducting a scientific experiment, it is important to control for extraneous variables. If you do not control for extraneous variables, you are likely to get incorrect results from your experiment.

Extraneous variables can affect your results in many different ways:

• They might make it difficult to determine the cause and effect relationship between your independent variable and your dependent variable

• They could skew the data so that they don’t accurately reflect what’s going on in reality

In an experiment conducted in a laboratory, the following might be extraneous variables:

In an experiment conducted in a laboratory, the following might be extraneous variables:

• The length of the day

• The size of the lab space / number of lights

• The kind of equipment used (e.g., if it’s a large room with many windows and doors, you may have more light outside than if it’s just one small window)

• Temperature in the lab (if your room gets cold at night) or hot during summertime

The length of the day.

The length of the day is a variable that can affect the results of an experiment. It’s not under your control, so it’s not something you can manipulate to get what you want.

The length of the day, or how much time there is between sunrise and sunset, is measured by many factors like weather conditions, season and latitude.

The size of the lab space / number of lights.

One of the most obvious ways to control for extraneous variables is to use a large lab space and many lights. This can be done in two ways:

• You could lay down some vinyl on your floor, then put up some whiteboards.

• You could put up some whiteboards and add some lights above them (and maybe even hang a few paper lanterns from the ceiling).

The kind of equipment used.

You will need equipment that is reliable, calibrated and appropriate for your experiment.

The reliability of the equipment depends on how well it has been constructed and tested. It also depends on how long it has been used in a laboratory before you start using it in your experiment (and whether this was done under controlled conditions). The calibration is important because there are standards against which to measure changes in temperature or pressure. Finally, if there are any uncertainties about how accurate the equipment is likely to be when used for measuring temperatures ranging from -55°C to +50°C (±0°F), then these uncertainties must be taken into account when choosing which thermometers or barometers would provide better accuracy levels than others available on the market today at reasonable prices.

Think about how many different things could affect your measurement besides just your independent variable!

Think about how many different things could affect your measurement besides just your independent variable.

You might be surprised at how many variables there are that could have an impact on the results of your experiment. Make sure to consider all of them and keep in mind that they may not be able to be controlled in this way, but they could still affect the outcome of your experiment.

Conclusion

Once you have eliminated extraneous variables from your experiment, the only variable that remains is your independent variable. You can then use this information to create a conclusion based on your data.

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