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Sonja [21]
3 years ago
12

Jennifer spends 1/4 of the day at school then 3/4 with her friends how much time does she do in a day​

Mathematics
1 answer:
Basile [38]3 years ago
3 0
She spends 1/4 of her day at school, this would be 8 hours out of 24 hours. which would be 8/24=1/4. therefore she spends 14 hours with her friends (3/4)
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Step-by-step explanation:

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Answer:

A. (h+(h-2) =14)...

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VladimirAG [237]
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6 0
4 years ago
The cost of a week long vacation in a city has a mean of 1000 and a variance of 1200. The city imposes a tax which will raise al
matrenka [14]

Answer:

The coefficient of variation after the tax is imposed is 0.033

Step-by-step explanation:

Given

\mu =1000 --- mean

\sigma^2 = 1200 --- variance

tax = 10\%

Required

The coefficient of variation

The coefficient of variation is calculated using:

CV = \frac{\sqrt{\sigma^2}}{\mu}

After the tax, the new mean is:

\mu_{new} = \mu * (1 + tax)

\mu_{new} = 1000 * (1 + 10\%)

\mu_{new} = 1100

And the new variance is:

\sigma^2_{new} = \sigma^2 * (1 + tax)

\sigma^2_{new} = 1200 * (1 + 10\%)

\sigma^2_{new} = 1320

So, we have:

CV = \frac{\sqrt{\sigma^2}}{\mu}

CV = \frac{\sqrt{1320}}{1100}

CV = \frac{36.33}{1100}

CV = 0.033

6 0
3 years ago
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
Talja [164]

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

#SPJ10

6 0
2 years ago
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