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nadya68 [22]
3 years ago
7

Baker sammy helppppp​

Mathematics
1 answer:
svetoff [14.1K]3 years ago
7 0

Answer:

a = 8.5t

y = 32.55

Step-by-step explanation:

Solving (9): The equation of the table

We start by calculating the slope (m)

m = \frac{a_2 - a_1}{t_2 - t_1}

Where:

(t_1,a_1) = (15,127.5)

(t_2,a_2) = (16.5,140.25)

m = \frac{140.25 - 127.5}{16.5 - 15}

m = \frac{12.75}{1.5}

m = 8.5

The equation is then calculated using:

a = m(t - t_2) + a_2

So, we have:

a = 8.5(t - 16.5) + 140.25

Open bracket

a = 8.5t - 140.25 + 140.25

a = 8.5t

Solving (10):

4.8y = 156.24

Required

Find x

Divide both sides by 4.8

y = 32.55

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8 0
3 years ago
Charlotte has been saving up to buy a home gym so she can work out at home without having to pay for a
Y_Kistochka [10]

The 15% discount for home gym, and the $889 cost of the Flex 3,000 gives;

1. f(x) = 0.85•x + 139.95

2.

  1. With the deal, Charlotte's before tax cost is $895.6
  2. The deal cost is more than the initial price making the deal not worth it.

3. The domain is; 889 < x < ∞

The range is; 895.6 ≤ f(x) ‹ ∞

<h3>How can the function notation for the cost be found?</h3>

1. The percentage discount Charlotte gets = 15% = 0.15

Cost of the 6 months subscription = $139.95

f(x) = Final before tax

x = Price of the home gym equipment

Therefore;

Given the 15% off, we get;

f(x) = (1-0.15)•x + 139.95

Which gives;

  • f(x) = 0.85•x + 139.95

2. Question 1

Cost of the Flex3000, <em>x</em> = $889

Therefore;

f(889) = 0.85 × 889 + 139.95 = 895.6

Charlotte's before–tax cost with the deal is therefore, $895.6

Given that the workout channel holds no value to Charlotte, and the deal cost is higher than the initial cost, it isn't worth it for her to pay for the subscription to get the 15% discount

3. The domain if the Awesome Flex is the cheapest option, is the possible initial price of the home gym equipment.

The domain is therefore;

  • 889 < x < ∞

The range is the possible values of the before tax cost.

The range is therefore;

  • 895.6 ≤ f(x) ‹ ∞

Learn more about writing equations here:

brainly.com/question/11331093

#SPJ1

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1 year ago
PLEASE HELP! Match the steps to find the equation of the parabola with focus (-1, -8) and directrix y = - 12.
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Answer:

3,2,1,6,5,4

Step-by-step explanation:

Hope this helps!!!

4 0
3 years ago
Please help this is confusing.
Makovka662 [10]

Answer:

The mashi e drilled down 45 feet. So -45

Step-by-step explanation:

72 = 24h

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7 0
3 years ago
A researcher collected data on the hours of TV watched per day from a sample of five people of different ages. Here are the resu
frozen [14]

Answer:

1. The least squares regression is y = -0.1015·x + 6.51

2. The independent variable is b) age

Please see attached table

Step-by-step explanation:

The least squares regression formula is given as follows;

\dfrac{\sum_{i = 1}^{n}(x_{i} - \bar{x})\times \left (y_{i} - \bar{y}  \right ) }{\sum_{i = 1}^{n}(x_{i} - \bar{x})^{2}}

We have;

\bar x = 24

\bar y = 4

\Sigma (x_i - \bar x) (y_i - \bar y) = -79

\Sigma (x_i - \bar x)^2 = 778

\therefore \hat \beta =\dfrac{\sum_{i = 1}^{n}(x_{i} - \bar{x})\times \left (y_{i} - \bar{y}  \right ) }{\sum_{i = 1}^{n}(x_{i} - \bar{x})^{2}} = \frac{-79}{778} = -0.1015

The least squares regression is y = -0.1015·x + α

∴ α = y  -0.1015·x = 6 - (-0.1015 × 5) = 6.51

The least squares regression is thus;

y = -0.1015·x + 6.51

2. The independent variable is the age b)

3. Steps to create an ANOVA table with α = 0.05

The overall mean = (43  + 30  + 22  + 20  + 5  + 1  + 6  + 4  + 3  + 6 )/10 = 14

There are 2 different treatment = df_{treat} = 2 - 1 = 1

There are 10 different treatment measurement = df_{tot} = 10 - 1 = 9

df_{res} = 9 - 1 = 8

df_{treat} + df_{res} = df_{tot}

The estimated effects are;

\hat A_1 = 24 - 14 = 10

\hat A_2 = 4 - 14 = -10

SS_{treat} = 10^2 \times 5 + (-10)^2 \times 5 =1000

\sum_{i}\SS_{row}_i = \sum_{i}\sum_{j} (y_{ij} - \bar y)= [(1 - 4)^2 + (6 - 4)^2 + (4 - 4)^2 + (3 - 4)^2 + (6 - 4)^2] = 18

\sum_{i} S S_{row}_i = \sum_{i}\sum_{j} (y_{ij} - \bar y) ^2= [(43 - 24)^2 + (30 - 24)^2 + (22 - 24)^2 + (20 - 24)^2 + (5 - 24)^2] = 778

S S_{res} = \sum_{i} S S_{row}_i = 778 + 18 = 796

SS_{tot} = (43  - 14)² + (30  - 14)² + (22  - 14)² + (20  - 14)² + (5  - 14)² + (1 - 14)1² + (6  - 4 )² + (3  - 14)² + (6  - 14)² = 1796

MS_{treat} = \dfrac{SS_{treat} }{df_{treat} } = \dfrac{1000}{1} = 1000

MS_{res} = \dfrac{SS_{res} }{df_{res} } = \dfrac{796}{8} = 99.5

F- value is given by the relation;

F = \dfrac{MS_{treat} }{MS_{res} } = \frac{1000}{99.5} = 10.05

We then look for the critical values at degrees of freedom 1 and 8 at α = 0.05 on the F-distribution tables 5.3177

Hence; F = 10.05 > F_{1,8}^{Krit}(5\%) = 5.3177, we reject the null hypothesis.

7 0
3 years ago
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