The total marks obtained in a mathematics test was 384 if the mean was 24 how many children took the test

A Basket contains 3 types of fruits weighing 58/3 kg in all. If 73/9 kg of are apples,19/6 are oranges and the rest are pears. W

strojnjashka [21]

Answer:

Step-by-step explanation:

233 322

4 0

2 years ago

-4+ =-1 what is the missing number?

Oksi-84 [34.3K]

T h e. a n s w e r I s t h r e e

4 0

2 years ago

Find the following limit or state that it does not exist. ModifyingBelow lim With x right arrow minus 2 StartFraction 3 (2 x min

leva [86]

Answer:

-60

Step-by-step explanation:

The objective is to state whether or not the following limit exists

$\lim_{x \to -2} \frac{3(2x-1)^2 - 75}{x+2}$ .

First, we simplify the expression in the numerator of the fraction.

$3(2x-1)^2 -75 = 3(4x^2 - 4x +1) -75 = 12x^2 - 12x + 3 - 75 = 12x^2 - 12x -72$

Now, we obtain

$12(x^2-x-6) = 12(x+2)(x-3)$

and the fraction is transformed into

$\frac{3(2x-1)^2 - 75}{x+2} = \frac{12(x+2)(x-3)}{x+2} = 12 (x-3)$

Therefore, the following limit is

$\lim_{x \to -2} \frac{3(2x-1)^2 - 75}{x+2} = \lim_{x \to -2} 12(x-3) = 12 \lim_{x \to -2} (x-3)$

You can plug in $-2$ in the equation, hence

$12 \lim_{x \to -2} (x-3) = 12 (-2-3) = -60$

6 0

2 years ago

PLEASE SOMEONE PLEASEE HELP ME. NO LINKSSSS <3

Levart [38]

Answer:

C and E

Step-by-step explanation:

JUST MULTYPLY:):):)

3 0

2 years ago

A set of bivariate data was used to create a least squares regression line. Which of the following is minimized by the line

77julia77 [94]

Answer:

B) The sum of the squared residuals

Step-by-step explanation:

Least Square Regression Line is drawn through a bivariate data(Data in two variables) plotted on a graph to explain the relation between the explanatory variable(x) and the response variable(y).

Not all the points will lie on the Least Square Regression Line in all cases. Some points will be above line and some points will be below the line. The vertical distance between the points and the line is known as residual. Since, some points are above the line and some are below, the sum of residuals is always zero for a Least Square Regression Line.

Since, we want to minimize the overall error(residual) so that our line is as close to the points as possible, considering the sum of residuals wont be helpful as it will always be zero. So we square the residuals first and them sum them. This always gives a positive value. The Least Square Regression Line minimizes this sum of residuals and the result is a line of Best Fit for the bivariate data.

Therefore, option B gives the correct answer.

5 0

2 years ago

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