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vazorg [7]
3 years ago
13

URGENT! WILL GIVE BRAINLIEST!!

Mathematics
2 answers:
Anastasy [175]3 years ago
6 0

Answer:

Option C

Step-by-step explanation:

It is given that (m + b), (2m + b), (3m + b), (4m + b)...... is an infinite sequence.

To check the correct way to define the sequence we will check each option given.

Option A.

f(x) = mx + b,      x = {1, 2, 3.....}

So the sequence formed by placing x = {1, 2, 3.....}

f(1) = m + b

f(2) = 2m + b

So this option is not the answer.

Option B.

f(x) = 2m + b + m(x - 2) for x = {1, 2, 3,........}

f(1) = 2m + b + m(1 - 2)

    = 2m + b - m

    = m + b

Which is our sequence.

Therefore, this option is not correct.

Option C.

a_{n}=m-b+m(n-1) for n = {1, 2, 3, ........}

a_{1}=m-b+m(1-1)

    = m - b

Which is not our sequence.

Therefore, this is the correct option which is not the correct way to define the given sequence.

Option D.

a_{1}=m+b and a_{n+1}=a_{n}+m for n = {1, 2, 3......}

a_{2}=a_{1}+m

    = m + b + m

    = 2m + b

So, this option is also incorrect.

Therefore, Option C is the answer.

Slav-nsk [51]3 years ago
5 0

Answer:

C) an = m − b + m(n − 1) for n = {1, 2, 3, ...}

Step-by-step explanation:

Nevermind you dont gotta tell me nothin. I just guessed and got C right. lol.

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Find the linear regression equation for the transformed data. x=1,2,3,4,5 y=13,19,37,91,253 log y=1.114,1.279,1.568,1.959,2,403
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Answer:

The answer is OPTION (D)log(y)=0.326x+0.687

<h2>Linear regression:</h2>

It is a linear model, e.g. a model that assumes a linear relationship between the input variables (x) and the single output variable (y)

The Linear regression equation for the transformed data:

We transform the predictor (x) values only. We transform the response (y) values only. We transform both the predictor (x) values and response (y) values.

(1, 13) 1.114

(2, 19) 1.279

(3, 37) 1.568

(4, 91) 1.959

(5, 253) 2.403

X            Y           Log(y)

1              13           1.114

2             19         1.740

3             37        2.543

4             91        3.381

5            253      4.226

Sum of X = 15

Sum of Y = 8.323

Mean X = 3

Mean Y = 1.6646

Sum of squares (SSX) = 10

Sum of products (SP) = 3.258

Regression Equation = ŷ = bX + a

b = SP/SSX = 3.26/10 = 0.3258

a = MY - bMX = 1.66 - (0.33*3) = 0.6872

ŷ = 0.3258X + 0.6872

The graph is plotted below:

The linear regression equation is  log(y)=0.326x+0.687

Learn more about Linear regression equation here:

brainly.com/question/3532703

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