Final answer:
To determine which statement about the distribution t¹.⁶ is incorrect, we need additional context. The exponent indicates a non-linear relationship, but does not inherently define the strength of the relationship. Likely, the incorrect statement is the one suggesting a weaker relationship between variables, as it lacks supporting context.
Step-by-step explanation:
The correct identification of the statement about the distribution t¹.⁶ that is not correct is contingent upon an understanding of various statistical concepts such as skewness and the nature of relationships in data distributions. Considering the exponent 1.6, statement (c) 'The exponent implies a stronger relationship than linear.' is not necessarily incorrect as it indicates a non-linear relationship, potentially stronger than a simple linear relationship depending on context. However, given that there is no context provided regarding a comparison of variables or their relationship, determining whether it is stronger can be challenging. Statement (d) 'It suggests a weaker relationship between variables.' is ambiguous without additional context. In general, exponents do not directly indicate the strength of the relationship but rather the type of relationship (linear, quadratic, exponential, etc). With the given choices and based on the principles of statistics, such as those outlined in the Central Limit Theorem and skewness, it's possible to infer that the assumption of a non-linear relationship (statement a) and a positively skewed distribution (statement b) are potentially correct. However, statement (c) has insufficient information to be deemed correct or incorrect outright, and statement (d) seems to be out of context and is likely to be the incorrect statement as it suggests a weaker relationship without basis.