$a_1=96;\ a_2=48;\ a_3=24;\ a_4=12;\ a_5=6\\\\a_1=a_2:2\to96:2=48\\a_2=a_3:2\to48:2=24\\a_3=a_2:2\to24:2=12\\a_4=a_3:2\to12:2=6\\\\therefore\\\\a_n=96:2^{n-1}=\frac {96}{2^{n-1}}\\\\check:\\a_1=\frac{96}{2^{1-1}}=\frac{96}{1^0}=96\\a_2=\frac{96}{2^{2-1}}=\frac{96}{2^1}=\frac{96}{2}=48\\a_3=\frac{96}{2^{3-1}}=\frac{96}{2^2}=\frac{96}{4}=24\\\vdots$

8 0

4 years ago

olive's garden in only 10y2 and the watermelon plants she wants to grow required 2.5y2 each.how many watermelon plants can she g

DerKrebs [107]

Answer:

4 plants

Step-by-step explanation:

In this problem, we are given the total area of the garden, which is:

$A=10y^2$

The number of plants that can fit inside the garden is given by the equation:

$A=na$

where:

n is the number of plants

a is the area of each plants

In this problem, the area of each plant is

$a=2.5y^2$

Therefore, we can re-arrange the equation to find the number of plants that can fit:

$n=\frac{A}{a}=\frac{10}{2.5}=4$

8 0

3 years ago

Please answer correctly will mark brainliest, thanks!

monitta

2 first class tickets
4 coach tickets

3 0

3 years ago

a. obtain the equation of the estimated regression line and use it to calculate a point prediction of ammonium concentration for

Alex Ar [27]

The equation of the regression line is $\bar{y}$ =9.1006+(-0.2157)x and the point prediction of ammonium concentration for 25ml/h is $\bar{y}$ =3.7081

<h3>What is meant by regression line?</h3>

A regression line is an approximation of the line that describes the true, but unknown, linear connection between two variables. The regression line equation is used to predict (or estimate) the value of the response variable from a given value of the explanatory variable.

In statistical modeling, regression analysis is a collection of statistical techniques for estimating the associations between a dependent variable and one or more independent variables.

a) $\bar{y}$ =β₀+β₁x

Where,

β₁= $S_{xy}$ / $S_{xx}$ -------(1)

Where,

$S_{xy}$ = -341.959231

$S_{xx}$ 1585.230769

By substituting these values in equation 1 we get,

β₁= -0.2157

β₀= $\bar{y}$ -β₁x

Where,

$\bar{y}$ =∑ $y_{i}$ /n

∑ $y_{i}$ =52.8

n=13

Then,

$\bar{y}$ =4.0615

$\bar{x}$ =∑ $x_{i}$ /n

∑ $x_{i}$ =303.7

n=13

$\bar{x}$ =23.3615

β₀=4.0615-(-0.2157)(23.3615)

=9.1006

Therefore, β₀=9.1006

The regression equation is $\bar{y}$ =9.1006+(-0.2157)x

If x=25,

$\bar{y}$ =9.1006+(-0.2157)(25)

$\bar{y}$ =3.7081

To know more about regression line, visit:

brainly.com/question/7656407

#SPJ4

7 0

1 year ago