Answer and Step-by-step explanation:
The concept of "shaping" is: "a term of behaviur that refers to slowly shaping or educating an organ to execute a particular response by improving any responses that come even close to the desired answer.
Let's take one rat example.
Here, in an experiment, a researcher may use moulding technique to coach a rat to push a lever.
To begin with, the researcher may award the rat if it does any movement in the lever direction at all. The rat will then simply take a step towards to the lever to be rewarded. Likewise, as the rat moves over to the lever and so forth, the rat also gets a reward before just pushing the lever generates reward.
Here the behaviour of the rat was 'formed' in order to make it push the lever. According to the example, any time the rat is awarded, it is praised for a "successive approximation" or for behaving in a manner that is nearer to the desired behaviour or result.
Likewise, algebraic equations are also progression steps and step-by - step progression allows solve the issue.
Answer:
B is the answer bruh
Step-by-step explanation:
give me a brainless and follow me
La fille a mudane guah garcon la homme la femme. 6/9
It's 3 (total number of have rabbits that's 43 - Have rabbits which is 40) 43-40= 3
Answer:
a) 
And replacing we got:

b) ![E(80Y^2) =80[ 0^2*0.45 +1^2*0.2 +2^2*0.3 +3^2*0.05]= 148](https://tex.z-dn.net/?f=%20E%2880Y%5E2%29%20%3D80%5B%200%5E2%2A0.45%20%2B1%5E2%2A0.2%20%2B2%5E2%2A0.3%20%2B3%5E2%2A0.05%5D%3D%20148)
Step-by-step explanation:
Previous concepts
In statistics and probability analysis, the expected value "is calculated by multiplying each of the possible outcomes by the likelihood each outcome will occur and then summing all of those values".
The variance of a random variable Var(X) is the expected value of the squared deviation from the mean of X, E(X).
And the standard deviation of a random variable X is just the square root of the variance.
Solution to the problem
Part a
We have the following distribution function:
Y 0 1 2 3
P(Y) 0.45 0.2 0.3 0.05
And we can calculate the expected value with the following formula:

And replacing we got:

Part b
For this case the new expected value would be given by:

And replacing we got
![E(80Y^2) =80[ 0^2*0.45 +1^2*0.2 +2^2*0.3 +3^2*0.05]= 148](https://tex.z-dn.net/?f=%20E%2880Y%5E2%29%20%3D80%5B%200%5E2%2A0.45%20%2B1%5E2%2A0.2%20%2B2%5E2%2A0.3%20%2B3%5E2%2A0.05%5D%3D%20148)