Hii I need the 7th and 8th question asap will mark brainliest 100% to who ever answers first and right thank you

One of your employees is bidding on a carpet installation job. They estimate that it will take 3 hours to install 12 square yard

Charra [1.4K]

Answer:

No, the bid is not correct.

Step-by-step explanation:

One of your employees is bidding on a carpet installation job.

They estimate that it will take 3 hours to install 12 square yards of carpeting.

we know that 1 square yard= 9 square foot.

12 square yard= 12×9 square foot=108 square foot

i.e. it takes 3 hours to carpet 108 square foot.

Hence time taken to carpet 1 square foot= $\dfrac{3}{108}$ hour

Now the dimension of room is:

11' 6"× 12' 9" i.e. we convert both the units to foot as:

1 foot= 12 inch

11'6"=11+(6/12)=11.5 foot.

and 12'9"=12+(9/12)=12.75 foot.

Hence, dimension of room=11.5 foot×12.75 foot

Hence area of room=11.5×12.75=146.625 square foot.

Time to carpet 146.625 square foot=

$\dfrac{3}{108}\times 146.625$ hour

=4.0729 hour

But it is given that it takes 12.3 hours to install the carpet.

Hence, the calculations were wrong.

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3 years ago

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The results of a common standardized test used in psychology research is designed so that the population mean is 155 and the sta

galina1969 [7]

Answer:

The value 155 is zero standard deviations from the [population] mean, because $\\ x = \mu$ , and therefore $\\ z = 0$ .

Step-by-step explanation:

The key concept we need to manage here is the z-scores (or standardized values), and we can obtain a z-score using the next formula:

$\\ z = \frac{x - \mu}{\sigma}$ [1]

Where

z is the z-score.
x is the raw score: an observation from the normally distributed data that we want standardize using [1].
$\\ \mu$ is the population mean.
$\\ \sigma$ is the population standard deviation.

Carefully looking at [1], we can interpret it as the distance from the mean of a raw value in standard deviations units. When the z-score is negative indicates that the raw score, x, is below the population mean, $\\ \mu$ . Conversely, a positive z-score is telling us that x is above the population mean. A z-score is also fundamental when determining probabilities using the standard normal distribution.

For example, think about a z-score = 1. In this case, the raw score is, after being standardized using [1], one standard deviation above from the population mean. A z-score = -1 is also one standard deviation from the mean but below it.

These standardized values have always the same probability in the standard normal distribution, and this is the advantage of using it for calculating probabilities for normally distributed data.

A subject earns a score of 155. How many standard deviations from the mean is the value 155?

From the question, we know that:

x = 155.
$\\ \mu = 155$ .
$\\ \sigma = 50$ .

Having into account all the previous information, we can say that the raw score, x = 155, is zero standard deviations units from the mean. The subject earned a score that equals the population mean. Then, using [1]:

$\\ z = \frac{x - \mu}{\sigma}$

$\\ z = \frac{155 - 155}{50}$