Consider a binomial random variable x given by (2.9), with prior distribution for u given by the beta distribution (2.13), and suppose we have observed m occurrences of x = 1 and l occurrences of x = 0. show that the posterior mean value of x lies between the prior mean and the maximum likelihood estimate for u. to do this, show that the posterior mean can be written as lambda times the prior mean plus (1 - lambda) times the maximum likelihood estimate, where 0 < = lambda < = 1. this illustrates the concept of the posterior distribution being a compromise between the prior distribution and the maximum likelihood solution

system of linear equation

step-by-step explanation:

as given in the data

a= 20 , b= -12

let us suppose that it is a straight line equation

now we know the formula for the system of linear equation

b= ma + c )

here m is slope of a straight line which is equal to formula

m=   (ii)

and here c is a constant

now putting the value of a and b in equation (ii)

m=

m=

putting the value of a,b and m in equation (i) gives us

-12 = + c

-12=-12 + c

adding 12 to both sides

-12 +12 = -12 +12 +c

0 =c

or c=0

as the value of the constant is zero which gives us that it is a linear equation and this order pair satisfies the system of linear equations.

large crystals result from very slow cooling.

evaporation of water: this would produce an evaporite which is a sedimentary rock. like a salt pan in a desert. not possible to have volcanic rocks originate this way.

crystalization in molten earth: slow cooling over time. (hundreds to millions of years)

crystalization at earth's surface: this results in fast cooling. (a few hours to a few months or years)

crystalization from cooling off hot water: that would be a hydrothermal deposit. while associated with volcanics they are not volcanic rocks themselves and usually occur fairly rapidly.

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hope this