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blondinia [14]
3 years ago
5

Complete the table below for the function y = 5x - 2.

Mathematics
1 answer:
inn [45]3 years ago
6 0
Well I’ll just make my own table
Key/legend: when y = 0 x = -2
X=|-3 |-2 | -1| 0|1 |2|3 |4 |5 |
Y=|17 |-12|-7|-2|3|8|13|18|23|
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If I had know ill,I would gone to visit you sentence using appropriate conditional classe​
quester [9]

Answer:

was this supposed to be funny lol

Step-by-step explanation:

5 0
3 years ago
ANSWER THIS!!!!!!!!!!
cluponka [151]

Answer:

r = sqrt( 3V/( pih))

Step-by-step explanation:

V = 1/3 pi  r^2 h

Solving for r

Multiply each side by 3

3V =  pi r^2h

Divide each side by  pi h

3V/( pi h)  = r^2

Take the square root of each side

sqrt( 3V/ (pi h) )= sqrt( r^2)

sqrt( 3V/ (pi h)) = r

4 0
2 years ago
A researcher reports survey results by stating that the standard error of the mean is 25 the population standard deviation is 40
bezimeni [28]

Answer:

a) A sample of 256 was used in this survey.

b) 45.14% probability that the point estimate was within ±15 of the population mean

Step-by-step explanation:

This question is solved using the normal probability distribution and the central limit theorem.

Normal probability distribution

When the distribution is normal, we use 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.

a. How large was the sample used in this survey?

We have that s = 25, \sigma = 400. We want to find n, so:

s = \frac{\sigma}{\sqrt{n}}

25 = \frac{400}{\sqrt{n}}

25\sqrt{n} = 400

\sqrt{n} = \frac{400}{25}

\sqrt{n} = 16

(\sqrt{n})^2 = 16^2[tex][tex]n = 256

A sample of 256 was used in this survey.

b. What is the probability that the point estimate was within ±15 of the population mean?

15 is the bounds with want, 25 is the standard error. So

Z = 15/25 = 0.6 has a pvalue of 0.7257

Z = -15/25 = -0.6 has a pvalue of 0.2743

0.7257 - 0.2743 = 0.4514

45.14% probability that the point estimate was within ±15 of the population mean

3 0
3 years ago
what measuring tool did ancient mathematics have and how do they compare to the measuring tools we have today?​
german

Answer:

Search it up my guy itsthere

Step-by-step explanation:

3 0
3 years ago
(-31/2)-(-41/4)=-7/2-(17/4)=
Andrew [12]
Just forget about the first half, and just do the second half. It’s way easier. Answer is -7.75
6 0
3 years ago
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