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djyliett [7]
4 years ago
10

Simplify the expression -2b-6+3b-2 b+4 5b-8 b-8 -b-8

Mathematics
1 answer:
sdas [7]4 years ago
7 0

Answer:

b-8

Step-by-step explanation:

  • Subtract -2 from -6 to get -8

  • subtract -2b from 3b to get b

  • Simplify to b-8
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The shape of the solution region for the system (picture) can be described as which of the following? Select all that apply.
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Rectangle and parallelogram

It will have two pairs of parallel sides. 
7 0
3 years ago
A machine in the student lounge dispenses coffee. The average cup of coffee is supposed to contain 7.0 ounces. A random sample o
Elenna [48]

Answer:

t=\frac{7.4-7}{\frac{0.7}{\sqrt{7}}}=1.512    

The degrees of freedom are

df=n-1=7-1=6  

And the p value for this case is:

p_v =2*P(t_{(6)}>1.512)=0.181  

The p value is a higher value and using a significance levels of 5% or 10% we see that the p value is higher than the significance level and then we FAIL to reject the null hypothesis and we don't have enough evidence to conclude that the true mean is different from 7 ounces.

Step-by-step explanation:

Information provided

\bar X=7.4 represent the sample mean

s=0.7 represent the sample standard deviation

n=7 sample size  

\mu_o 7 represent the value to verify

t would represent the statistic

p_v represent the p value

System of hypothesis

We want to verify if the average amount of coffee per cup is different from 7 ounces, the system of hypothesis would be:  

Null hypothesis:\mu = 7  

Alternative hypothesis:\mu \neq 7  

The statistic is given by:

t=\frac{\bar X-\mu_o}{\frac{s}{\sqrt{n}}}  (1)  

Replacing the info given we got:

t=\frac{7.4-7}{\frac{0.7}{\sqrt{7}}}=1.512    

The degrees of freedom are

df=n-1=7-1=6  

And the p value for this case is:

p_v =2*P(t_{(6)}>1.512)=0.181  

The p value is a higher value and using a significance levels of 5% or 10% we see that the p value is higher than the significance level and then we FAIL to reject the null hypothesis and we don't have enough evidence to conclude that the true mean is different from 7 ounces.

7 0
3 years ago
According to an NRF survey conducted by BIGresearch, the average family spends about $237 on electronics (computers, cell phones
Usimov [2.4K]

Answer:

(a) Probability that a family of a returning college student spend less than $150 on back-to-college electronics is 0.0537.

(b) Probability that a family of a returning college student spend more than $390 on back-to-college electronics is 0.0023.

(c) Probability that a family of a returning college student spend between $120 and $175 on back-to-college electronics is 0.1101.

Step-by-step explanation:

We are given that according to an NRF survey conducted by BIG research, the average family spends about $237 on electronics in back-to-college spending per student.

Suppose back-to-college family spending on electronics is normally distributed with a standard deviation of $54.

Let X = <u><em>back-to-college family spending on electronics</em></u>

SO, X ~ Normal(\mu=237,\sigma^{2} =54^{2})

The z score probability distribution for normal distribution is given by;

                                 Z  =  \frac{X-\mu}{\sigma}  ~ N(0,1)

where, \mu = population mean family spending = $237

           \sigma = standard deviation = $54

(a) Probability that a family of a returning college student spend less than $150 on back-to-college electronics is = P(X < $150)

        P(X < $150) = P( \frac{X-\mu}{\sigma} < \frac{150-237}{54} ) = P(Z < -1.61) = 1 - P(Z \leq 1.61)

                                                             = 1 - 0.9463 = <u>0.0537</u>

The above probability is calculated by looking at the value of x = 1.61 in the z table which has an area of 0.9463.

(b) Probability that a family of a returning college student spend more than $390 on back-to-college electronics is = P(X > $390)

        P(X > $390) = P( \frac{X-\mu}{\sigma} > \frac{390-237}{54} ) = P(Z > 2.83) = 1 - P(Z \leq 2.83)

                                                             = 1 - 0.9977 = <u>0.0023</u>

The above probability is calculated by looking at the value of x = 2.83 in the z table which has an area of 0.9977.

(c) Probability that a family of a returning college student spend between $120 and $175 on back-to-college electronics is given by = P($120 < X < $175)

     P($120 < X < $175) = P(X < $175) - P(X \leq $120)

     P(X < $175) = P( \frac{X-\mu}{\sigma} < \frac{175-237}{54} ) = P(Z < -1.15) = 1 - P(Z \leq 1.15)

                                                         = 1 - 0.8749 = 0.1251

     P(X < $120) = P( \frac{X-\mu}{\sigma} < \frac{120-237}{54} ) = P(Z < -2.17) = 1 - P(Z \leq 2.17)

                                                         = 1 - 0.9850 = 0.015

The above probability is calculated by looking at the value of x = 1.15 and x = 2.17 in the z table which has an area of 0.8749 and 0.9850 respectively.

Therefore, P($120 < X < $175) = 0.1251 - 0.015 = <u>0.1101</u>

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What is "tangent theta equals 0.255"
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Answer:

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Step-by-step explanation:

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