Logic and
Critical Thinking

Philosophy 4

Gale Justin

u        Causal Arguments          

The objective of today’s class is learn how to recognize and evaluate a third kind of inductive  arguments.  This a a causal argument.  Like inductive generalizations and analogical arguments, causal arguments can only be inductive strong, not deductively certain.

u        Causal Statements:

These are claims that one thing (usually an event) caused another thing (usually another event).  For example, “over-watering killed my plants.”  In some cases the cause can be the absence of some event, such as “Failure to water caused the wilting of my plants.”

u        For example:

u        Cause: over-watering

                                Effect: dead plants

u        Cause:  Failure to water

                 Effect:  dead plants

u        The difference between cause and background conditions:

Generally the cause is the factor that “triggers” the effect.  It is an event that upon being introduced into a set of circumstances brings about another event.  For example, an apple might be just about to fall from a tree and does so when the wind picks up.  The background conditions include the weight of the apple and the sturdiness of the branch.  The on set of the wind is the direct cause. It makes the difference.

u        Some examples of causal connections:

v  Smoking and cancer

v  Dieting and weight loss

v  Raining and water on the pavement

v  Midterms and anxiety

u        Not every correlation is a causal connection:

v  The service man who fixed the garage door opener may not have taken the bicycle that I noticed was missing after he left. 

v  My putting my head down on the pillow is not the cause of the faucet beginning to drip.

v  Ulysses S. Grant’s alcohol consumption may not have been the cause of his being a good general.

u        The difference between a correlation and a cause:

u        A correlation is “two things going together”.

u        A correlation is evidence that the two correlates are connected in some way.

u        A correlation is something to explain.

We want to know “Why did these two things occur together?”

u        There are four basic ways to explain the joint occurrence (correlation)  of A and B:

    1. A causes B. (Direct Cause)

    2. B causes A. (Reverse Cause)

    3. X causes both A and B. (Common Cause)

    4. Chance.  A and B occur together by chance.

u        For example:

    1. Direct Cause: Exercise causes fitness.

    2. Reverse Cause: Fitness causes exercise.

    3. Common Cause: Living in sunny climate causes both fitness and exercise.

    4. Chance: By chance the faucet started to leak after I put my head on my pillow.

u        Conventions for describing Causal Correlations:

u        We will use descriptive phrases to identify the events that are correlated and may be causally related.  Thus:

  1. Fitness
  2. Exercise

u        We will choose the relationship that best describes the manner of the causal connection.  In some cases, more than one connection is possible.

u        For example, fitness and exercise can correlated as:

  1. A causes B.
  2. B causes A.
  3. Some common cause (c), such as living in California, can cause both A and B.

u        Example:

College graduates earn substantially more than people who only complete high school.  The occurrence “having a college degree” + “earning more money” is a correlation.  The correlation is represented by phrases:

A: having a college degree

B: earning more money


u        Applying these four patterns to the example, you get:

  1. Having a college degree causes earning more money. (Direct Cause)
  2. Earning more money causes having a college degree. (Reverse Cause)
  3. Being a hard worker causes both having a college degree and earning more money.
  4. Chance causes the correlation.

u        How can we decide between rival causal explanations?:

1. To rule out chance, look for more correlations of the same type.  If they are present, then the correlation is probably not due to chance. For example, if there is no statistically significant correlation between drinking alcohol and being a good general, then the correlation in Grant’s case was probably due to chance.

2. In some cases, the specific correlation will be an instance of a general causal relationship, as in the common cause explanation of having a college degree and earning more money.

                Having money tends to lead to both A and B.

3. In uncertain cases, look for a plausible causal story about the events that would help to determine their causal pattern.

u        Consider:

Women who have breast implants drink more alcohol, have children at a younger age, have more sexual partners and make other life style choices that could account for some of the health troubles blamed on the implants. 

1. What are the correlates?  2. What pattern of connection between the correlates does this passage raise doubts about? 3. What pattern of connection between the correlates does the passage suggest?

u        Classwork and, then, homework:

u        In class now do Groupwork #8.

u        For homework, complete homework #9 & 10.