All categories

3 years ago

Question 6

Mathematics

1 answer:

s2008m [1.1K]3 years ago

5 0

Answer:

24.4

Step-by-step explanation:

Given the data :

Month (X) : 0, 1, 2, 4, 6

Weight (Y) : 7.2, 9.4, 10.5, 13.2, 15.9

To obtain the predicted weight at 1 year, we fit the data to obtain the regression model. Using technology, the regression model obtained is :

y = 7.6 + 1.4X1

Substituting x = 1 year into the regression model, we obtained the predicted weight at 1 year ;

1 year = 12 months, hence, x = 12

y = 7.6 + 1.4(12)

y = 7.6 + 16.8

y = 24.4

You might be interested in

Please help me with this...

AURORKA [14]

Answer:

- 84 + 10i

Step-by-step explanation:

A complex number in standard form is a ± bi

a is the real part and bi the imaginary part

and $\sqrt{-1}$ = i

Given

$\sqrt{-100}$ - 84

= $\sqrt{100(-1)}$ - 84

= $\sqrt{100}$ × $\sqrt{-1}$ - 84

= 10i - 84

= - 84 + 10i ← in standard form

3 0

3 years ago

Suppose that 10% of all homeowners in an earthquake-prone area of California are insured against earthquake damage. Four homeown

guapka [62]

Remainder of question:

Find the probability distribution of x

Answer:

The random variable x is defined as: X = {0, 1, 2, 3, 4}

The probability distribution of X:

P(X = 0) = 0.656

P(X = 1) = 0.2916

P(X= 2) = 0.0486

P(X=3) = 0.0036

P(X = 4) = 0.0001

Step-by-step explanation:

Sample size, n = 4

Random variable, X = {0, 1, 2, 3, 4}

10% (0.1) of the homeowners are insured against earthquake, p = 0.1

Proportion of homeowners who are not insured against earthquake, q = 1 - 0.1

q = 0.9

Probability distribution of x,

$P(X = r) = ^nC_r *p^r q^{n-r} \\\\P(X= 0) =(^4C_0 *p^1 q^4 )\\P(X=0) = (^4C_0 *0.1^0 0.9^4 ) = 0.656\\P(X= 1)= (^4C_1 *p^1 q^3 )\\P(X=1) = (^4C_1 *0.1^1 0.9^3 ) = 0.2916\\P(X= 2)=( ^4C_2 *p^2 q^2) \\P(X=2) = (^4C_2 *0.1^2 0.9^2 ) = 0.0486\\P(X= 3) = (^4C_3 *p^3 q^3) \\ P(X=3) = (^4C_3 *0.1^3 0.9^1 ) = 0.0036\\P(X= 4) = (^4C_4 *p^4 q^0 )\\ P(X=4) =(^4C_4 *0.1^4 0.9^0 ) = 0.0001$