Have a wonderful day :)and here are free pts to make your day better <3 12 x 9 = ?

Mathematics

2 answers:

Mamont248 [21]3 years ago

8 0

Answer:

108

Step-by-step explanation:

mafiozo [28]3 years ago

4 0

Answer:

its 108

and tysm thats so sweet

Step-by-step explanation:

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joe weighs 20lbs.less yhantwice jeffs weight.if jeff would gain 10lbs.,then together they wouldweigh 250lbs. how much does each

masya89 [10]

So,

Let x represent Joe's weight and y represent Jeff's weight.

"Joe weighs 20 lbs. less than twice Jeff's weight."
x = 2y - 20

"If Jeff would gain 10 lbs., then together they would weigh 250 lbs."
(y + 10) + x = 250

We now have our two open sentences.
x = 2y - 20
(y + 10) + x = 250

Get rid of parentheses.
x = 2y - 20
x + y + 10 = 250

We will use Elimination by Substitution.
2y - 20 + y + 10 = 250

Collect Like Terms.
3y - 10 = 250

Add 10 to both sides.
3y = 260

Divide both sides by 3.
$Jeff's\ weight = 86 \frac{2}{3} \ lbs.$

Substitute again.
$x = 2(86 \frac{2}{3} )-20$

Multiply.
$x = 173 \frac{1}{3} -20$

Subtract.
$Joe's\ weight = 153 \frac{1}{3}\ lbs.$

Check.

"Joe weighs 20 lbs. less than twice Jeff's weight."
Jeff's weight times two is 173 and one-third.
20 lbs. less than that is 153 and one-third lbs. Check.

"If Jeff would gain 10 lbs., then together they would weigh 250 lbs."
86 and two-thirds + 10 = 96 and two-thirds.
96 and two-thirds + 153 and one-third equals 250 lbs. Check.

$Joe's\ weight\ is\ 153 \frac{1}{3} \ lbs.$
$Jeff's\ weight\ is\ 86 \frac{2}{3} \ lbs.$

3 0

3 years ago

A random sample of ten professional athletes produced the following data where x is the number of endorsements the player has an

lukranit [14]

ŷ= 1.795x +2.195 is the equation for the line of best fit for the data

<h3>How to use regression to find the equation for the line of best fit?</h3>

Consider the table in the image attached:

∑x = 29, ∑y = 74, ∑x²= 125, ∑xy = 288, n = 10 (number data points)

The linear regression equation is of the form:

ŷ = ax + b

where a and b are the slope and y-intercept respectively

a = ( n∑xy -(∑x)(∑y) ) / ( n∑x² - (∑x)² )