The score which is assigned from 1 to 4 by the teacher to each student for the project and is most likely to be is 3 with 0.48 probability.
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What is probability distribution?</h3>
Probability distribution is the statistical model which represent all the achievable and similar values of a random variable that it can possess in a specified range.
A teacher assigns a score from 1 to 4 to each student project. the table below shows the probability distribution of the scores for a randomly selected student.
- Probability distribution score: 1, 2, 3, 4,
- x probability: p(x) 0.06, 0.20, 0.48, 0.26
In the above data, the height probability of selection is 0.48. This probability belongs to the score 3.
Thus, the score which is assigned from 1 to 4 by the teacher to each student for the project and is most likely to be is 3 with 0.48 probability.
Learn more about the probability distribution here;
brainly.com/question/26615262
Step-by-step explanation:
5*(4x+8)=6*(2x+3)
20x+40=12x+18
20x _12x= 18_40
8x = _22
x=_22/8
x= _11/4
Answer:
B
Step-by-step explanation:
y = 
is the equation of a horizontal line parallel to the x- axis.
A line perpendicular to it will be a vertical line parallel to the y- axis with equation
x = c
where c is the value of the x- coordinates the line passes through.
The line passes through (- 6, - 9 ) with equation
x = - 6 → B
Answer:
Step-by-step explanation:
Hello!
The definition of the Central Limi Theorem states that:
Be a population with probability function f(X;μ,δ²) from which a random sample of size n is selected. Then the distribution of the sample mean tends to the normal distribution with mean μ and variance δ²/n when the sample size tends to infinity.
As a rule, a sample of size greater than or equal to 30 is considered sufficient to apply the theorem and use the approximation.
X[bar]≈N(μ;σ²/n)
If the variable of interest is X: the number of accidents per week at a hazardous intersection.
There is no information about the distribution of this variable, but a sample of n= 52 weeks was taken, and since the sample is large enough you can approximate the distribution of the sample mean to normal. With population mean μ= 2.2 and standard deviation σ/√n= 1.1/√52= 0.15
I hope it helps!
