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Full explanation, worked examples & memory tricks in the app
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Full explanation, worked examples & memory tricks in the app
Every question in the paper gets a full exam-length answer in the app — organised by marks, the way a topper writes it.
Apply Runge-Kutta method of order 4 to find the approximate value of y for $x = 0.2$, in step of $h=0.1$ if $rac{dy}{dx} = x + y^2$, $y = 1$ when $x=0$.
Use the Runge-Kutta method to compute $y(0.2)$.
The full exam-length answer is in the app.
Explain Euler's method for finding the approximate solution $y(x)$.
Euler's method approximates solutions of differential equations using iterative steps based on the slope.
The full exam-length answer is in the app.
Apply Regula Falsi method to find the real root of the equation $3x - \cos x - 1 = 0$.
Use the Regula Falsi method iteratively to approximate the root.
The full exam-length answer is in the app.
Apply Newton's Forward interpolation formula to find number of students who obtained marks between 40 and 45 from the following data.
Use Newton's Forward interpolation on the provided frequency data.
The full exam-length answer is in the app.
Apply Newton-Raphson's method to find the real root of the equation $xe^x = 2$ by taking suitable initial approximation.
Iterate using the Newton-Raphson formula to find the root.
The full exam-length answer is in the app.
Apply Lagrange's interpolation formula to find f(x) from the data. Hence, find f(3.5).
Use Lagrange's formula to interpolate and evaluate at $x=3.5$.
The full exam-length answer is in the app.
Find the mean and median of the data set. 15, 13, 9, 9, 7, 1, 11, 10, 13, 1, 13.
Mean = 9.09, Median = 9.
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Write a short note on Discrete Probability distribution function.
A discrete probability distribution function assigns probabilities to discrete outcomes.
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From the following table, find the values of $rac{dy}{dx}$, $rac{d^2y}{dx^2}$ at $x = 2.02$.
Use finite difference methods to estimate derivatives at $x=2.02$.
The full exam-length answer is in the app.
Find the mean of the Poisson distribution.
The mean of a Poisson distribution is equal to its parameter $\lambda$.
The full exam-length answer is in the app.
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