The Bell Curve Controversy
Critical thinking is an important part of psychology. Examining concepts such as the Bell Curve is improtant in upper level pschology course work. Paper Masters will help you learn about the bell curve controversy in a research paper that is designed to address all your academic needs.
"The Bell Curve: Intelligence and Class Structure in American Life" was a book written in the early 1990s about human intelligence and how it is cultivated. The book posited that human intelligence is encouraged through environment and things like socioeconomic status. The controversy surrounding the book and the concept of intelligence is rooted in the elitist nature of the research. The foundation of the issue is that the book is stating that the more money a person has and the better environment in which they thrive, the more intelligent they are likely to be. While there are environmental factors that play a role in the development of intelligence, to say that the amount of money someone has or the number of amenities in their environment skews the odds in favor of those with more prosperity than others.
The controversy also focuses on the following:
- The idea that those with higher intelligence are among the elite in society. This allows the notion to persist that smarter people are somehow "better" than everyone else. It is a divisive way of thinking and this is part of the reason that there is so much controversy around it.
- The controversy also contributed to racial divides regarding intelligence, which has not been proven by research. There is no difference in intelligence when it comes to the races that have anything to do with the biological factors associated with the way that the mind works.
The "normal distribution" represents a particular shape of the graph representing a collection of data points. The normal distribution, or normal curve, appears as a bell-shaped curve on a graph.The shape of this curve shows that the majority of data points are clustered around the mean and fewer data points exist which are further away from the mean.In a normal curve, 68.2% of the data points will fall within one standard deviation of the mean, 27.2% of the data points will fall within two standard deviations of the mean, and the remaining 4.6% of the data points fall far from the mean at three or four standard deviations away.
The normal distribution is important for at least two reasons. When data is distributed normally, the variance and the mean have little to do with each other.In other words, if the mean changed, the amount of variance in the data would still remain the same. It is also important because this type of distribution describes a large variety of natural phenomena in the world, such as human height, weight, and blood pressure.
When considering data that represents the age at the time of human death in the United States and data pertaining to annual income in the United States, the latter of the two does not represent a normal distribution. The distribution is skewed to the left, since the average income level is between $17,000 and $66,000. The number of data points between the 50th and 99th percentiles far exceeds the number of data points below the 10th percentile, and the data does not take the form of a bell curve. Data regarding the age of death in the U.S. does assume a normal distribution. The average lifespan is at about 70 years and the amount of data points on either side of this is roughly equal. This curve is bell-shaped.