What does it mean when we state: "Many frequency distributions in the social sciences are approximately?
And, why does this occur?
My thinking is:
I would have to say that many frequency distributions, in particularly the social sciences are approximately normal. When working with a typical distribution, there are going to be a few low scores and also a few high ones, but the majority will fall in the middle. This probably occurs when the probability of all the many determiners of a trait pointing in the same direction is virtually nil, and that of a balanced combination of determiners is much higher. As mentioned in class, the normal distribution is a good indicator to the kinds of distribution frequently encountered in medical and behavioral investigations and is the best-known for statistical treatments.
Is my logic correct here?
The assumption is that any distribution of scores determined solely by chance factors will approximate a normal distribution, especially with a higher number of scores.
I'm not sure what you are saying in the third sentence of your thinking. It is unclear.
I hope this helps. Thanks for asking.
Your logic is partially correct. It is true that many frequency distributions in the social sciences exhibit a shape that is approximately normal or bell-shaped. This means that the majority of observations cluster around the mean, with fewer observations on either extreme.
The reason for this occurrence is often related to the Central Limit Theorem. This theorem states that when independent random variables are summed or averaged, regardless of their individual distribution, the resulting distribution tends to be approximately normal as the sample size increases. In the social sciences, data often stems from complex interactions of multiple factors and variables. When these factors are combined, their effects may follow this pattern.
Additionally, the normal distribution is often observed in the social sciences due to the presence of multiple determinants of a trait or behavior. Each determinant can have either a positive or negative influence, leading to a balanced combination of determinants. This balancing effect contributes to the normal distribution shape.
However, it is important to note that not all frequency distributions in the social sciences are approximately normal. There are cases where other distribution shapes, such as skewed or bimodal distributions, might be observed depending on the specific variables and factors being studied.
In conclusion, while your explanation captures some aspects of why many frequency distributions in the social sciences are approximately normal, it is important to consider the role of the Central Limit Theorem and the complex interactions of multiple determinants in shaping these distributions.