-3/5x=6 Solve it please I neeeeeeeeeeeeeeed help
1 answer:
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Answer:
In order to calculate the expected value we can use the following formula:
And if we use the values obtained we got:
Step-by-step explanation:
Let X the random variable that represent the number of admisions at the universit, and we have this probability distribution given:
X 1060 1400 1620
P(X) 0.5 0.1 0.4
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.
In order to calculate the expected value we can use the following formula:
And if we use the values obtained we got:
Answer:
<em>Center: (3,3)</em>
<em>Radius: </em><em />
Step-by-step explanation:
<u>Midpoint and Distance Between two Points</u>
Given two points A(x1,y1) and B(x2,y2), the midpoint M(xm,ym) between A and B has the following coordinates:
The distance between both points is given by:
Point (5,7) is the center of circle A, and point (1,-1) is the center of the circle B. Given both points belong to circle C, the center of C must be the midpoint from A to B:
Center of circle C: (3,3)
The radius of C is half the distance between A and B:
The radius of C is d/2:
Center: (3,3)
Radius:
Answer:
c) Is not a property (hence (d) is not either)
Step-by-step explanation:
Remember that the chi square distribution with k degrees of freedom has this formula
Where N₁ , N₂m .... are independent random variables with standard normal distribution. Since it is a sum of squares, then the chi square distribution cant take negative values, thus (c) is not true as property. Therefore, (d) cant be true either.
Since the chi square is a sum of squares of a symmetrical random variable, it is skewed to the right (values with big absolute value, either positive or negative, will represent a big weight for the graph that is not compensated with values near 0). This shows that (a) is true
The more degrees of freedom the chi square has, the less skewed to the right it is, up to the point of being almost symmetrical for high values of k. In fact, the Central Limit Theorem states that a chi sqare with n degrees of freedom, with n big, will have a distribution approximate to a Normal distribution, therefore, it is not very skewed for high values of n. As a conclusion, the shape of the distribution changes when the degrees of freedom increase, because the distribution is more symmetrical the higher the degrees of freedom are. Thus, (b) is true.