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3 years ago

If u answer ill give brainlist

Mathematics

1 answer:

makkiz [27]3 years ago

3 0

Answer:

120; 643 units squared

Step-by-step explanation:

Perimeter: Add all the sides, so 120 units

_________________________________

Area: First multiply 19 by 24 for the first shape within this other shape, so That equals 456 units squared. Since we know that one whole side is 36 we can subtract 19 from it to get the lower side of the smaller shape and then multiply that by 11. So the smaller side ends up being 17. So 17 times 11 equals: 187 units squared. Then just add the areas together 187+456=643 units squared.

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In a class of 50 students, the number of students who offer accounting is twice as the number who offer economics.10 students of

myrzilka [38]

Answer:

accounting=30, economics=15, only one=35

Step-by-step explanation:

a=2e

5 both

10 neither

40=a+e-5

45=a+e

45=2e+e

e=15

a=2e

a=30

8 0

3 years ago

If 15 mi = 8 km, about how many miles would be equal to 50 km?

Anon25 [30]

Use ratios to solve

15 m/8 km = x m/50 km Cross multiply
15(50) = 8x
750 = 8x divide by 8 on both sides
93.75 = x

93.75 miles = 50km

6 0

3 years ago

3x + 6y= 6<br> 9x - 12y = 18 elimination with multiplication

rjkz [21]

Answer: x = 4y/3+2

y = 0

Step-by-step explanation:

3 0

3 years ago

Jack is 2 times as old as Lacy. 5 years ago the sum of their ages was 20. How old are they now?

Mama L [17]

Answer:

2x-6=8

2x-6=8+6

2x=24

x=12

4 0

3 years ago

Consider this scenario: The population of a city increased steadily over a ten-year span. The following ordered pairs show the p

vova2212 [387]

Answer:

Regression function: $y=1986.406+0.0059x$

The function predicts that population will reach 14,000 in year 2068.

Step-by-step explanation:

We have to determine a function $y=b_0+b_1x_1$ by applying linear regression. The data we have is 5 pair of points which relates population to year.

According to the simple regression model (one independent variable), if we minimize the error between the model (the linear function) and the points given, the parameters are:

$b_0=\bar{y}+b_1\bar{x}\\\\b_1=\frac{\sum\limits^5_{i=1} {(x_i-\bar x)(y_i-\bar y)}}{\sum\limits^5_{i=1} {(x_i-\bar x)^2}}$

We start calculating the average of x and y

$\bar x=\frac{2500+2650+3000+3500+4200}{5}=\frac{15850}{5}=3170\\\\ \bar y=\frac{2001+2002+2004+2007+2011}{5}=\frac{10025}{5}=2005$

The sample covariance can be calculated as

$\sum\limits^5_{i=1} {(x_i-\bar x)(y_i-\bar y)}=(2500-3170)(2001-2005)+(2650-3170)(2002-2005)+(3000-3170)(2004-2005)+(3500-3170)(2007-2005)+(4200-3170)(2011-2005)\\\\\sum\limits^5_{i=1} {(x_i-\bar x)(y_i-\bar y)}=2680+1560+170+660+6180\\\\ \sum\limits^5_{i=1} {(x_i-\bar x)(y_i-\bar y)}=11250$

The variance of x can be calculated as

$\sum\limits^5_{i=1} {(x_i-\bar x)^2}=(2500-3170)^2+(2650-3170)^2+(3000-3170)^2+(3500-3170)^2+(4200-3170)^2\\\\\sum\limits^5_{i=1} {(x_i-\bar x)^2}=448900+270400+28900+108900+1060900\\\\\sum\limits^5_{i=1} {(x_i-\bar x)^2}=1918000$

Now we can calculate the parameters of the regression model

$b_1=\frac{\sum\limits^5_{i=1} {(x_i-\bar x)(y_i-\bar y)}}{\sum\limits^5_{i=1} {(x_i-\bar x)^2}}=\frac{11250}{1918000}=0.005865485 \\\\ b_0=\bar{y}+b_1\bar{x}=2005-0.005865485*3170=1986.406413$

The function then become:

$y=1986.406+0.0059x$

With this linear equation we can predict when the population will reach 14,000:

$y=1986.406+0.0059(14,000)=1986.406+82.117=2068.523$

6 0

3 years ago