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dE_logics
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Within specified limits, the area under the curve of an equation and the submission of all values on that curve will be different right?...just confirming.
dE_logics said:So this will be 5+5.1+5.2+5.3......10.5+10.6+10.7+10.8+10.9+11
This won't give an accurate result...the intervals at which the addition should occur should be infinity small to give 100% accuracy.
No, it wouldn't. That is the sum of x-values, not f(x) and it is done with a "step" of 0.1. You had said nothing about a particular step interval before.dE_logics said:aaa...thanks for notifying me about that.
Take a function y = x (simplest possible)
Suppose I want summation of f(x) (or y) from limits 5 - 11 on x.
So this will be 5+5.1+5.2+5.3......10.5+10.6+10.7+10.8+10.9+11
The Riemann sum, of f(x) with a step of 0.1, between 5 and 11 would be (f(5)+ f(5.1)+ ...+ f(10.9))(0.1). Is that what you are asking about?This won't give an accurate result...the intervals at which the addition should occur should be infinity small to give 100% accuracy.
So what I mean to say is when we integrate a function, this summation is not the result right? The summation will be the result in cause of line integral right?
The "area under the curve" refers to the total area enclosed by a curve and the x-axis on a graph. It is important in scientific research because it can provide valuable information about the relationship between two variables and can be used to calculate important parameters such as the mean, variance, and standard deviation.
The area under the curve is typically calculated using mathematical integration techniques. For continuous curves, this involves finding the definite integral of the function represented by the curve. For discrete data, the area can be approximated by dividing the curve into smaller sections and using the trapezoidal rule or Simpson's rule.
The shape of the curve, the range of the x-axis, and the values of the variables represented by the curve can all affect the area under the curve. Additionally, the accuracy of the data points and the method used to calculate the area can also impact the results.
The area under the curve can be used to compare different data sets and determine which one has a larger or smaller overall value. It can also be used to identify patterns or trends in the data and make predictions about future values. In some cases, the area under the curve can also be used to calculate probabilities and make statistical inferences.
Submitting the area under the curve in scientific research is important because it allows other researchers to replicate and verify the results. It also provides a standardized way of presenting and comparing data, making it easier for others to understand and interpret the findings. Additionally, submitting the area under the curve allows for transparency and accountability in the research process.