The correct answer to this open question is the following.
You forgot to attach the text, the argument, and the options for this question. However, doing some research, we can say the following.
The argument in the second paragraph of the inscription regarding king Adityawarman is about how his spiritual attributes and worldly achievements made him a respected, powerful, and effective ruler.
Historians say that he was a strict but good ruler of the Kingdon of Malayapura, is Sumatra, in Southeastern Asia.
Deeper research on the part of historians has found that he had deep spiritual belief systems that made him a compassionate ruler too, and people respect him for that.
We can see from Dr. Aguilera's findings that high levels of anxiety are associated with poor academic performance. However, the number of hours of sleep has little bearing on how well or poorly a student does in class.
The confounding variable is important to avoid obstacles to the measurement
<h3>How to illustrate the information?</h3>
Dr. Aguilera discovered a strong link between anxiety and academic achievement. Additionally, this number is negative, indicating a negative correlation between the two variables. According to this negative correlation, the value of the other variable decreases as the value of the first variable increases. Therefore, academic performance declines when anxiety levels rise.
The term "correlation" describes the connection between two variables. In other words, if the correction equals 0, there is no correlation between the two variables. The relationship between sleep duration and academic performance was zero. This indicates that these factors are unrelated and have no bearing on one another.
The Cohort effect is crucial to avoid obstacles to the measurement and research methodologies used, nevertheless.
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Answer:
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Explanation:
When population growth was high and HDI was low there was a high rate of deforestation, but when HDI was high, rate of deforestation was low, despite high population growth. The correlation among variables was significant for the 1990s but not for the 1980s.
