Final answer:
The advertisement uses a playful comparison of I.Q. scores for humor, leading to the application of a statistical hypothesis test on brown trout's I.Q. Using a one-sample t-test and the given data, the hypothesis that the average I.Q. of brown trout is greater than four could not be supported due to a p-value higher than the alpha level.
Step-by-step explanation:
The Nissan Motor Corporation advertisement playfully compares the I.Q. scores of humans to brown trout to humorously suggest that despite humans having a higher I.Q., catching brown trout is still challenging. This is not a direct commentary on intelligence but rather a marketing strategy to engage with the audience. However, this scenario provides an interesting opportunity to explore statistical hypothesis testing in a real-world context.
To conduct a hypothesis test on the belief that the average I.Q. of brown trout is greater than four, one can use a one-sample t-test. This can determine if the sample mean significantly differs from the hypothesized population mean. In this case, a fish psychologist determines the I.Q.s of 12 caught brown trout and a hypothesis test is performed using these scores.
Based on the given scores, we can calculate the sample mean and conduct a two-tailed Student's t-test to see if the difference from the hypothesized mean I.Q. of 4 is statistically significant. The reported t-value of 1.95 and a p-value of 0.076 would be compared against a significance level, Alpha: 0.05. As the p-value is greater than the alpha level, there is insufficient evidence to reject the null hypothesis, suggesting that the sample does not provide strong enough evidence to say the average I.Q. of brown trout is not four.
It's important to remember that I.Q. in animals, especially fish like brown trout, is not directly comparable to human I.Q. scores. The concept of I.Q. itself has been debated and may not fully represent intelligence as it interacts with various environmental and genetic factors. The study of human intelligence has evolved considerably since the days of Lewis Terman, who found contrary to popular belief that people with high I.Q.s are often well-adjusted and successful.