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Table of Contents  ||   Previous:   Elements of Literature  ||   Next:   Meal Planning: What's For Dinner?

Inductive Reasoning - Be a Skeptic Who Employs Common Sense

—by Jean Fisher
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Inference is the process of drawing conclusions by making observations and applying logic. Combine skepticism with commmon sense in the process of inductive reasoning and improve your decision making skills.

Part-to-Whole and Data Analysis

Inductive reasoning is the process of making observations and, through inference, forming a generalization. A very simple example would be the part-to-whole model:

  • The people who live on my street draw their blinds or close their curtains when it starts getting dark outside.
    therefore...
  • All people pull the shades on their windows at night.

Is this a valid conclusion? Probably not. The logic of inductive reasoning requires a measure of skepticism combined with a good dose of common sense.

The skeptic looks at the conclusion--all people pull their shades at night--as possibly false. Common sense is then applied to consider reasons why the conjecture might not be true.

  • No one is home to draw the blinds.
  • The residents are too busy realize that is has become dark.
  • The room with the open curtains is empty, all the occupants of the home are in other rooms.
  • It is a hot night and open blinds allow cool air to circulate.

There appears to be much room for doubt about the uniformity of shutting curtains after dark. Sampling only the surrounding neighborhood does not supply enough data. More neighborhoods must be visited after dark to reach an accurate conclusion.

The open-curtain example uses a part-to-whole approach. One part of the population--the people in my neighborhood--always close their curtains at night, therefore all curtains are closed after dark.

Prediction Requires Experience

Applying experiences from the past in attempt to predict the future is inductive reasoning. The results of stormy weather illustrate:

  • Whenever I go to the beach after a storm, the sand is littered with algae.
  • It is stormy tonight.
    Therefore...
  • I am sure to step over a lot of seaweed as I walk along the shore tomorrow.

This time the skeptic would consider the idea that the beach might be clear of seaweed following a storm. Common sense, however, supports the prediction of seaweed on the shore tomorrow.

  • There is an abundance of algae in the ocean.
  • The tide carries shells, driftwood, and bits of plant life onto the beach even when it isn’t stormy.
  • Waves amplified by a storm have the force to uproot algae plants and toss them onto the shore.

Experience increases accuracy when using inductive reasoning in the form of a prediction. The more times you have seen the ocean shore after a storm, the more likely you are to offer an accurate prediction of the results of that storm.

Extrapolation and the Unknown

Extrapolation is the third type of inductive reasoning. Extrapolation is projecting information from known data to draw a conclusion regarding the unknown. A bird watcher might make an inference using extrapolation:

  • Tuesday morning I saw 8 goldfinches, 16 sparrows, and 2 bluebirds at the bird feeder.
  • Wednesday morning I saw 4 goldfinches, 7 sparrows, and 1 bluebird.
  • Thursday morning I saw 9 goldfinches, 12 sparrows and 1 bluebird.
    Therefore...
  • The ratio of birds in my neighborhood could be represented - goldfinches : sparrows : bluebirds = 7 : 12 : 1

Let skepticism and common sense challenge this inference.

  • One or more birds may have visited the feeder two or more times during the period of observation.
  • Some birds may prefer to feed during the evening.
  • Weather, nesting or migration could affect the number of birds using the birdfeeder.
  • A cat could have been skulking around scaring the birds away.
  • The feeder in the neighbor’s yard could be tastier.

Extrapolation is useful when it is impossible to test enough data to verify the conclusion. A dedicated scientist would need plenty of time and patience to count the bird population in a neighborhood with a high degree of accuracy.

Inductive reasoning is very useful in everyday life. Decisions such as taking an umbrella to work, or selecting a movie for the whole family to enjoy will be more successful through the use of inductive reasoning. Remember to question conclusions, use your experience and apply your intelligence.



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