Which decimal has the greatest value0.0005, 0.5 or 0.05 ?

Solve using long division.

yuradex [85]

I pray to hod for yourgood day

5 0

3 years ago

Read 2 more answers

Help please I don’t know the answer and the teacher didn’t explain

Diano4ka-milaya [45]

Answer:

Step-by-step explanation:

$\frac{-4d^{2}+15d^{2}}{5}=\frac {11d^{2}}{5}\\\\=\frac{11*1^{2}}{5}\\\\=\frac{11}{5}\\\\=2\frac{1}{5}$

3 0

3 years ago

What is the product of 2x - 5 and 3x2 + 5x - 7? Write your answer in standard form.

andrew11 [14]

Answer:

a) 6x³ − 5x² − 39x + 35

b) no

Step-by-step explanation:

(2x − 5) (3x² + 5x − 7)

Distribute:

3x² (2x − 5) + 5x (2x − 5) − 7 (2x − 5)

Distribute again:

6x³ − 15x² + 10x² − 25x − 14x + 35

Combine like terms:

6x³ − 5x² − 39x + 35

5x − 2 is the opposite of 2x − 5, so you would get the negative of the answer from part (a).

8 0

3 years ago

Supply the missing reasons to complete the proof

Sladkaya [172]

3. Congruent by AAS

4. CPCTC

8 0

3 years ago

The correlation between the height and weight of children aged 6 to 9 is found to be about r = 0.8. Suppose we use the height x

Andrew [12]

Answer:

$r=\frac{n(\sum xy)-(\sum x)(\sum y)}{\sqrt{[n\sum x^2 -(\sum x)^2][n\sum y^2 -(\sum y)^2]}}$

The value of r is always between $-1 \leq r \leq 1$

And we have another measure related to the correlation coefficient called the R square and this value measures the % of variance explained between the two variables of interest, and for this case we have:

$r^2 = 0.8^2 = 0.64$

So then the best conclusion for this case would be:

c. the fraction of variation in weights explained by the least-squares regression line of weight on height is 0.64.

Step-by-step explanation:

For this case we know that the correlation between the height and weight of children aged 6 to 9 is found to be about r = 0.8. And we know that we use the height x of a child to predict the weight y of the child

We need to rememeber that the correlation is a measure of dispersion of the data and is given by this formula:

$r=\frac{n(\sum xy)-(\sum x)(\sum y)}{\sqrt{[n\sum x^2 -(\sum x)^2][n\sum y^2 -(\sum y)^2]}}$

The value of r is always between $-1 \leq r \leq 1$

And we have another measure related to the correlation coefficient called the R square and this value measures the % of variance explained between the two variables of interest, and for this case we have:

$r^2 = 0.8^2 = 0.64$

So then the best conclusion for this case would be:

c. the fraction of variation in weights explained by the least-squares regression line of weight on height is 0.64.

3 0

3 years ago