The estimated standard error for the sample mean difference is 2.5 .
According to the question
A repeated-measures study comparing two treatments
n = 4
MD(mean difference) = 2
SS (sum of square) = 75
Now,
error for the sample
Formula for standard error

by substituting the value
S² = 25
S = 5 (s is never negative)
Standard error of the estimate for the sample mean difference
As
The standard error of the estimate is the estimation of the accuracy of any predictions.
The formula for standard error of the mean difference
standard error of the mean difference =
standard error of the mean difference =
standard error of the mean difference = 2.5
Hence, the estimated standard error for the sample mean difference is 2.5 .
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By Euler's method the <em>numerical approximate</em> solution of the <em>definite</em> integral is 4.189 648.
<h3>How to estimate a definite integral by numerical methods</h3>
In this problem we must make use of Euler's method to estimate the upper bound of a <em>definite</em> integral. Euler's method is a <em>multi-step</em> method, related to Runge-Kutta methods, used to estimate <em>integral</em> values numerically. By integral theorems of calculus we know that definite integrals are defined as follows:
∫ f(x) dx = F(b) - F(a) (1)
The steps of Euler's method are summarized below:
- Define the function seen in the statement by the label f(x₀, y₀).
- Determine the different variables by the following formulas:
xₙ₊₁ = xₙ + (n + 1) · Δx (2)
yₙ₊₁ = yₙ + Δx · f(xₙ, yₙ) (3) - Find the integral.
The table for x, f(xₙ, yₙ) and y is shown in the image attached below. By direct subtraction we find that the <em>numerical</em> approximation of the <em>definite</em> integral is:
y(4) ≈ 4.189 648 - 0
y(4) ≈ 4.189 648
By Euler's method the <em>numerical approximate</em> solution of the <em>definite</em> integral is 4.189 648.
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8.6
Since there is one number before the decimal, we don't have to move the decimal
8.6 * 10^0
Answer 8.6 * 10^0
Step-by-step explanation:

p(x) = -2












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