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dezoksy [38]
3 years ago
6

9.06 - 3.6 × 1.6 + 0.32

Mathematics
2 answers:
Inessa [10]3 years ago
5 0

Answer:

3.62

Step-by-step explanation:

Bidmas

Brackets Indices Division Multiplication Addition Subtraction

9.06 - 3.6 × 1.6 + 0.32

Multiplication first

9.06 - (3.6 × 1.6) + 0.32

9.06 - 5.76 + 0.32

Then you can do addition and subtraction in either order as they're both equal.

(9.06 - 5.76) + 0.32

3.3 + 0.32

3.62

slava [35]3 years ago
3 0

Answer: 3.6

Step-by-step explanation:

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An article contained the following observations on degree of polymerization for paper specimens for which viscosity times concen
devlian [24]

Answer:

(a) A 95% confidence interval for the population mean is [433.36 , 448.64].

(b) A 95% upper confidence bound for the population mean is 448.64.

Step-by-step explanation:

We are given that article contained the following observations on degrees of polymerization for paper specimens for which viscosity times concentration fell in a certain middle range:

420, 425, 427, 427, 432, 433, 434, 437, 439, 446, 447, 448, 453, 454, 465, 469.

Firstly, the pivotal quantity for finding the confidence interval for the population mean is given by;

                              P.Q.  =  \frac{\bar X-\mu}{\frac{s}{\sqrt{n} } }  ~ t_n_-_1

where, \bar X = sample mean = \frac{\sum X}{n} = 441

            s = sample standard deviation = \sqrt{\frac{\sum (X-\bar X)^{2} }{n-1} }  = 14.34

            n = sample size = 16

            \mu = population mean

<em>Here for constructing a 95% confidence interval we have used One-sample t-test statistics as we don't know about population standard deviation.</em>

<em />

<u>So, 95% confidence interval for the population mean, </u>\mu<u> is ;</u>

P(-2.131 < t_1_5 < 2.131) = 0.95  {As the critical value of t at 15 degrees of

                                             freedom are -2.131 & 2.131 with P = 2.5%}  

P(-2.131 < \frac{\bar X-\mu}{\frac{s}{\sqrt{n} } } < 2.131) = 0.95

P( -2.131 \times {\frac{s}{\sqrt{n} } } < {\bar X-\mu} < 2.131 \times {\frac{s}{\sqrt{n} } } ) = 0.95

P( \bar X-2.131 \times {\frac{s}{\sqrt{n} } } < \mu < \bar X+2.131 \times {\frac{s}{\sqrt{n} } } ) = 0.95

<u>95% confidence interval for</u> \mu = [ \bar X -2.131 \times {\frac{s}{\sqrt{n} } } , \bar X +2.131 \times {\frac{s}{\sqrt{n} } } ]

                                      = [ 441-2.131 \times {\frac{14.34}{\sqrt{16} } } , 441+2.131 \times {\frac{14.34}{\sqrt{16} } } ]

                                      = [433.36 , 448.64]

(a) Therefore, a 95% confidence interval for the population mean is [433.36 , 448.64].

The interpretation of the above interval is that we are 95% confident that the population mean will lie between 433.36 and 448.64.

(b) A 95% upper confidence bound for the population mean is 448.64 which means that we are 95% confident that the population mean will not be more than 448.64.

6 0
3 years ago
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Margarita [4]

Answer:

15 divided by 3 = 5

Step-by-step explanation:

21 divided by 3 = 7

6 divided by 3 = 2

Have a Good Day : )

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3 years ago
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The answer would be- P=$116.07 because you have to x all the numbers then add some
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Aquí está mejor <br> Cómo simplificar esta expresión
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Answer:

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Decimal: 89.75

Step-by-step explanation:

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If you walked 2 3/4 miles on Monday and then walked 3 1/3 miles on Tuesday, how many miles did you walk during those two days?
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6 miles that is rounded up
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