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sveta [45]
3 years ago
6

Learning Task 1: Give the value and the place value of the underlined

Mathematics
1 answer:
galina1969 [7]3 years ago
5 0

Answer:

Value place value

1. 0.016. hundredths

2. 0009. ten thousandths

3. 00011. ten thousandths

4. 0.00093. ten thousandths

5.0004. ten thousandths

Step-by-step explanation:

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Question 1<br> Determine the midpoint of the segment with endpoint (-9,3) and (7,-8).<br> Question 2
mario62 [17]

Answer:

(-1, -2.5)

Step-by-step explanation:

the midpoint of a segment is (\frac{x1+x2}{2} ,\frac{y1+y2}{2}), given points (x1, y1) and (x2, y2)

midpoint=(\frac{-9+7}{2}, \frac{3-8}{2} ) = (\frac{-2}{2}, \frac{-5}{2}  ) = (-1, -2.5)

6 0
3 years ago
Read 2 more answers
Rockwell hardness of pins of a certain type is known to have a mean value of 50 and a standard deviation of 1.8. (Round your ans
Alenkinab [10]

Answer:

a) 0.011 = 1.1% probability that the sample mean hardness for a random sample of 17 pins is at least 51

b) 0.0001 = 0.1% probability that the sample mean hardness for a random sample of 45 pins is at least 51

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal probability distribution

Problems of normally distributed samples are solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the zscore of a measure X is given by:

Z = \frac{X - \mu}{\sigma}

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean \mu and standard deviation \sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}.

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

In this problem, we have that:

\mu = 50, \sigma = 1.8

(a) If the distribution is normal, what is the probability that the sample mean hardness for a random sample of 17 pins is at least 51?

Here n = 17, s = \frac{1.8}{\sqrt{17}} = 0.4366

This probability is 1 subtracted by the pvalue of Z when X = 51. So

Z = \frac{X - \mu}{\sigma}

By the Central Limit Theorem

Z = \frac{X - \mu}{s}

Z = \frac{51 - 50}{0.4366}

Z = 2.29

Z = 2.29 has a pvalue of 0.9890

1 - 0.989 = 0.011

0.011 = 1.1% probability that the sample mean hardness for a random sample of 17 pins is at least 51

(b) What is the (approximate) probability that the sample mean hardness for a random sample of 45 pins is at least 51?

Here n = 17, s = \frac{1.8}{\sqrt{45}} = 0.2683

Z = \frac{X - \mu}{s}

Z = \frac{51 - 50}{0.0.2683}

Z = 3.73

Z = 3.73 has a pvalue of 0.9999

1 - 0.9999 = 0.0001

0.0001 = 0.1% probability that the sample mean hardness for a random sample of 45 pins is at least 51

8 0
3 years ago
Solve the formula for C thx if u answer!!!
kati45 [8]

Answer: The answer is C = -P + R

3 0
1 year ago
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25m/s to miles/h <br>Can anyone solve it?<br>With explanation if you can
Dimas [21]

25 meters per second x 60 seconds = 1500 meters per minute

1500 meters per minute x 60 minutes per hour = 90,000 meters per hour

1 mile = 1609.34 meters

90000/1609.34 = 55.92 miles per hour

 round answer to either 55.9 or 56 mph depending on what you need.

6 0
3 years ago
Roberto wants to reduce a drawing that is 12 inches long by 9 inches wide. If his new drawing is 8 inches long, how wide will it
Bess [88]

Answer: It would be 6 inches wide.


Step-by-step explanation: Well two thirds of 12 in. is 8in. So  two thirds of 9in. would be 6 inches.


6 0
3 years ago
Read 2 more answers
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