How to Conduct a Science Experiment at Home

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When I was in elementary school, science was not part of the curriculum.  We had daily math, social studies, English, spelling, reading, and physical education.  We even had weekly art and music, but no science.  In high school, biology, physics, and chemistry were offered, but not required.  I made it all the way to college, on scholarships even, without taking any science classes.  Then I fell in love with it.  The discovery, first-hand, of why things did what they did got me hooked.  I went on to get several college degrees, but the one I use and value most is my degree in science.

In the 1970s and 1980s, most elementary and secondary schools beefed up their science programs.  Then, in the 1990s, widespread budget cuts seemed to hit science programs the most.  With fewer resources and less time, science instruction became short, choppy, and incomplete.  It also became a lot less fun.  Without hands-on labs to impress and enthrall, fewer and fewer kids got hooked on science.

So how can you be Bill Nye the Science Guy and enthrall your kids with science?  You start with the basic fundamentals—the scientific method and the basics of conducting research.

The Scientific Method and the Hypothesis

The scientific method begins with a problem, usually stated as a question.  For example, how much rain do we get each week?  The next part of the scientific method is the hypothesis.  Suppose you’ve checked out the rainfall in your area and calculate that an average of about four tenths of an inch of rain falls every week in your backyard.  The hypothesis is always stated in such a way that an experiment can be designed to either disprove it or fail to disprove it.  Note that, as inherently flawed and imperfect human beings, we can never design the perfect experiment and thus can never prove our hypothesis, only fail to disprove it.  Given what information we already have about local rainfall, we could hypothesize that the rainfall in our backyard would be approximately 0.4 inches each week, on average.

The Experiment, Control Group, and Test Group

After the hypothesis comes the experiment.  The basics of experiment design are relatively simple.  If you are measuring how much something changes, then you have a control group and a test group.  The control group is the group that stays the same, but is measured at the same time as the test group, and then the two results are compared.  For example, if we wanted to measure how heat affected a plant, we would need at least two plants for the experiment—one to use as the control and not expose to heat, another to use as the test and expose to heat.

List of Materials and Procedure Section

As part of the experiment, we would include a list of materials needed and a procedure section describing the various steps in the experiment.  Our rainfall experiment would include a materials list with rain gauges, while our heat experiment would need plants, a heat lamp or other heat source, and maybe a ruler to measure changes in height or leaf width.  The procedure section for the rain experiment would go something like this:

  1. Place six rain gauges at intervals of ten feet in our backyard.
  2. At 6 pm every day, measure and record the amount of water in each rain gauge, then empty them.
  3. At the end of the week, after 7 days, add the amounts for days 1 through 7 and record that amount in our data journal.
  4. Repeat for four weeks and average totals.

The Results Section with Tables and Graphs

The next part is the results section.  This can be a table, graph, or other depiction of the data we’ve collected.  It also includes a written summary of what we found out.  For example, the average weekly rainfall in our backyard for the month of September 2006 was 1.3 inches.

The Conclusion

The last part of the scientific method is the conclusion. The conclusion relates the results back to the hypothesis.  For example:

Conclusion:  The average rainfall in my backyard for the month of September 2006 was 1.3 inches, much more than my hypothesis of 0.4 inches.  This disproves my hypothesis.

Of course, the conclusions section also includes a place to record what you learned from your experiment so that others reading your work can design a better experiment and not necessarily duplicate your work.  Scientists are always building on the work of other scientists.  In our rainfall example, the hypothesis could have been more specific.  If we had researched seasonal rainfall and then formed our hypothesis, it probably would have been closer to the real measurement since rainfall can vary dramatically by seasons.  We also could have taken measurements for three months, the entire season, instead of just one month.  These suggestions for revising the experiment or further research are perfect for the conclusions section.

Primary versus Secondary Data

A basic understanding of research methods is also necessary in science.  Not all data is gathered in an experiment, what we call primary or first-hand data.  Often, we search the internet, read books, or interview experts and gather data that was collected by someone else, called secondary or second-hand data.  If you collect only secondary data, then be sure you use multiple sources.  If you go to three websites which each quote the same source of data, then you still only have one source and are not adding anything new to it.  On the other hand, if you gather data from three different sources and interpret it, then you are adding to it, building on previous research.


Another common research method is averaging.  Averaging is taking data for a given time period, adding it, and then dividing by the number of data points.  For example, if we’re averaging rainfall, we take the seven daily rainfall amounts, add them together, and then divide by seven to get an average daily rainfall.  If we’re averaging weekly rainfall, we can take the four weekly totals, add them together, and then divide by four.


One of the most difficult research methods to understand, and the one most often done poorly, is sampling.  Let’s suppose your two year-old wants to count the number of bugs in your backyard and your ten year-old thinks it would make a neat science experiment.  You have a huge backyard and realize this would be impossible.  This is where sampling comes in.  A sample is a smaller portion of what you are experimenting on that is representative of the whole.  For example, if your backyard is 800 square feet, then you could count the number of bugs in one square foot (your sample area), and then multiply this by 800 to get an estimate of the total number of bugs in your backyard.  If your entire backyard looks alike, that would work.  What if one half of your yard is rocky (and we all know bugs love to hide under rocks) and the other half is grassy?  It would be more accurate and representative of the whole if you have one square foot sample area in the rocky half and another in the grass.  Then you would average these two pieces of data and then multiply by 800 to get an estimate of the total bugs in the backyard.

Sampling and Averaging Together

Sampling and averaging, when done correctly and appropriately, makes scientific experiments much more accurate.  Sampling makes sure that all relevant data is included, while averaging makes sure that unusually low or high data points don’t dramatically affect the experiment results.  Going back to our rainfall example, we would want to place our six rain gauges in areas of the backyard that represented the whole backyard, collecting three samples from under the trees and three samples from the non-tree-covered part of the yard.  We would average this data so that the gauge under the magnolia tree, which collected almost no rain, would not aversely affect our results.

Tailor the Experiment to the Child

These are just guidelines in doing science at home.  Experiments are fun if you remain flexible.  Obviously, a two year-old can’t count all the bugs in a square foot of backyard, but he can count the number of butterflies and his 10 year-old brother can count the number of pill bugs.  In other words, fit the experiment to the kid.

Additional Resources

There are many science books written for kids by Janice Van Cleave.  I would recommend any of them.  For older kids, grade 6 and up, I highly recommend Painless Research Projects by Barron’s.

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