Topic: What is the role of nature and nurture in intelligence?
Statistical Concepts Covered:
In this applet, you’ll learn about how to visualize, interpret, and compare correlational values. We will also continue our discussion of causality and confounding variables as they relate to the complicated nature vs. nurture debate on intelligence.
Introduction:
Your text chapter covers the long-standing debate of nature versus nurture in regards to intelligence. This applet will allow you to explore simulated data with IQs of individuals in various relationships, at different ages, and in various environments.
Statistical Lesson. As the text explains, when we measure a correlation we will typically get a correlation coefficient, a mathematical measure of both the direction and strength of a correlation. It is most commonly represented by the letter r. This value for the correlation tells us how strong the correlation is and the direction of the correlation. The strength of a correlation can range from 0 to ±1. The closer r gets to 1, the stronger the relationship is between the variables, while the closer r gets to 0, the weaker the relationship.
The following table provides a guide to the various strengths based on the value (so only look at the number and not the sign before it):
| Value of the correlation (r) | Strength |
| 0 | Zero or No |
| 0.1 – 0.3 | Weak |
| 0.4 – 0.6 | Moderate |
| 0.7 – 0.9 | Strong |
| 1 | Perfect |
The sign for the correlation tells us whether the correlation is positive (greater than 0) or negative (less than 0).
• An r with a positive (+) sign or no sign is considered positive. A positive correlation means that as one variable increases, so does the other, which is evident in an upward sloping line or data in a graph.
• An r with a negative (-) sign is considered negative. A negative correlation means that as one variable increases, the other decreases, which is evident in a downward sloping line or data in a graph.
Remember the coverage on correlation in the applet for Emotion & Motivation? We discussed the importance of remembering that when considering relationships between variables, we cannot conclude that one of the variables caused the change we see in the other variable. This is especially true when we do not conduct an experiment that included manipulation or control over the variables or environment being studied. Studies of intelligence are great examples of naturalistic studies where we cannot manipulate, but only measure our variables. However, the way these studies are design can lead us to further pinpoint what might contribute to the relationship or differences we see. For example, comparing siblings or twins raised apart with those who are reared together can give us insight into how much a shared environment or genetics contribute to IQ. As always, keep in mind when interpreting relationship to not infer causality, and always look for confounding variables.
1) One way to evaluate the influence of genetics is to look at identical twins because they share 100% of the same genetic code. How strong is the relationship between the IQs of identical twins who are reared together? (Pick “Childhood” for the Age, “Identical twins” for the Relationship, and “Together” for the Rearing. Compare this r value and graph to when “Adolescence” and “Adulthood” are selected as the Age.)
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2) In the previous question we evaluated data regarding identical twins who were raised together. What about fraternal twins raised together? Keep in mind that these twins share about 50% of the same genes, similar to non-twin siblings. (Pick “Childhood” for the Age, “Fraternal twins” for the Relationship, and “Together” for the Rearing. Compare this r value and graph to when “Adolescence” and “Adulthood” are selected as the Age.)
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3) We’ve evaluated the relationship between IQs when two people are identical twins and share 100% of their genes, and fraternal twins sharing 50% of their genes. What about children raised together but do not come from the same parents, thus sharing 0% of the same genes? What is the relationship between IQs in unrelated children reared together? (Pick “Childhood” for the Age, “Unrelated” for the Relationship, and “Together” for the Rearing. Compare this r value and graph to when “Adulthood” is selected as the Age.)
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4) Compare the results obtained in questions 1-3. What patterns can we see in comparing the IQs of adults who were identical twins, fraternal twins, and unrelated children reared together?
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5) In the previous questions we kept the environment consistent by only comparing those that were reared together, thus any differences between these correlations from identical twins, fraternal twins, and unrelated children, could be attributed to genes and how much or how little were shared between the two individuals. What conclusions can we reach based on this data?
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6) Let’s compare identical twins raised together versus those raised apart. How is the relationship similar or different depending on the environment for these individuals? (Pick “Adulthood” for the Age, “Identical twins” for the Relationship, and “Together” for the Rearing. Compare this r value and graph to when “Apart” is selected as the Rearing.)
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7) Let’s now compare fraternal twins raised together versus those raised apart. How is the relationship similar or different depending on the environment for these individuals? (Pick “Adulthood” for the Age, “Fraternal twins” for the Relationship, and “Together” for the Rearing. Compare this r value and graph to when “Apart” is selected as the Rearing.)
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8) Based on the data we’ve reviewed thus far for adults, how would we order these groups from strongest to weakest correlation?
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9) Which of the following is a possible confounding variable that could explain the relationship between nature and nurture in the data evaluated? Think about which of the following would be related to both variables.
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10) Based on what you’ve learned from the data explored in this applet and the readings in the chapter on intelligence and heritability, what would be the best conclusion we can reach regarding this topic?
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