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Q: Solve x*+6r34y dx+ +3x=+y = (1 + logx)* dx²

A: Given differential equation, x4d4ydx4+6x3d3ydx3+9x2d2ydx2+3xdydx+y=1+logx2 This is a homogeneous…

Q: Determine the y-intercept of the exponential function h(x)=e^x

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Q: Let p(t)=10(0.001)^t and   q(t)=log⁢  t^3. Solve the equation q(p(t))=0 for t.

A: The given functions are,

Q: log(x³) dx

A: Consider the integral: ∫logx3xdx…

Q: Differentiate y =( logx) sinx

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Q: If log3 (x + 2) = 2, the value of 'x' is..... %3D

A: If logam=n then m=an

Q: dy = (x +y – 1) + ¥+y log(x +y)

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Q: f(x)=log_(2)x that is 6 units to the right and 2 units up?

A: Parent function f(x)=log2x We have to find the equation of function that is 6 units to the right and…

Q: 9⋅7x=3.5e^(2x) Find x using natural log

A: Given exponential equation is:Solve for x using natural log.

Q: For the following equation, find x. log_(b)x=(2)/(3)log_(b)27+(1)/(2)log_(b)4-log_(b)6 x=2 (Type an…

A: The properties of logarithms are a set of rules that allow us to simplify expressions involving…

Q: Solve the exponential regression function 100.34(1.25)^x when x=30

A: The given exponential regression function is,

Q: Differentiate f(x) = log, (9 – 10x).

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Q: Solve A. t= x/log B. t=logx C. t=x^10 D. t=10^x

A: See the attachment

Q: Create two exponential functions that have a horizontal asymptote at y=3 and go through the point…

A: The solution is given below

Q: Graph function y= 2x and y= log2^x on a single set of axes.

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Q: y=log_((1)/(4))(x). Write your answer only as an interval in the corroctlv written answer: (-inf,…

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Q: Expand ln 3√y3z2/x4 as a sum, difference and/ or the consent multiple of logarithms.

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Q: For the function f(x)=log_((1)/(3))(x)+3, determine whether the function is increasing or…

A: The given function fx=log13x+3. We have determine whether the function is increasing or decreasing.

Q: 7. Differentiate y = log10 (x² + 1)² b. 4xlog10e x²+1 a. 4x(x² + 1) c. log e(x) (x² + 1) d. 2x(x² +…

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Q: for a positive value of x . log_(x)(8)=3  Find  X.

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Continuous Probability Distributions

Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.

Normal Distribution

Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!