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gayaneshka [121]
3 years ago
5

Simplify 6x-36=16x-42

Mathematics
2 answers:
lakkis [162]3 years ago
8 0
X = 7 that the answer

Murrr4er [49]3 years ago
6 0
<span>7 — = 1.16667 6. hope it helps

</span>
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Find a point-slope form for the line with slope 1/5 and passing through the point (-4,-9).
sattari [20]

Answer:

y + 9 = \frac{1}{5}(x + 4)

Step-by-step explanation:

The equation of a line in point- slope form is

y - b = m(x - a)

where m is the slope and (a, b) a point on the line

Here m = \frac{1}{5} and (a, b) = (- 4, - 9) , thus

y - (- 9) = \frac{1}{5}(x - (- 4) ) , that is

y + 9 = \frac{1}{5}(x + 4)

3 0
2 years ago
Gaetano spent $37.80, including tax, on a pair of jeans. How much did the jeans cost if there was an 8% sales tax?
Fiesta28 [93]
<span>1.       </span><span>Gaetano spent 37.80 dollars including the tax for a pair of jeans
=> the tax is 8%, how much is the original cost of a pair of jeans?
=> 8% = 8/100
=> .08
Now, multiply .08 by 37.80 to get the 8% of 37.80
=> 37.80 x .08
=> 3.024 – this is the tax of a pair of jeans.
now, let’s subtract 3.024 by 37.80 to get the actual price of a pair of jeans.
=> 37.80 – 3.024
=> 34.776 – the original price of a pair of jeans without tax.



</span>



3 0
3 years ago
The following box plot shows the number of books sold each day at a store for 80 days. How many days did the bookstore sell 2 to
ddd [48]

Answer:

882

Step-by-step explanation:

5 0
3 years ago
Read 2 more answers
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
if danielle still drove 24 miles on the eight day how many miles would tim need to drive to make the median amount of miles that
Rainbow [258]

Answer:

the answer would be she would drive 192 miles

7 0
2 years ago
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