All categories

3 years ago

Jerry is comparing –8 and –10 on a number line. Which is true regarding their locations on the number line?

Mathematics

2 answers:

zubka84 [21]3 years ago

6 0

Answer: THE CORRECT ANSWER IS (D.–8 is less than –10 because –8 is to the right of –10 on a number line.)

plz give brainliest

anygoal [31]3 years ago

3 0

They are a distance of 2 away from each other

You might be interested in

Please help me ;-;

Hitman42 [59]

Answer:

Step-by-step explanation:

Based on the table, the left and the right side have a pattern. When 3 is added to the left side, the right side is multiplied by 6. Since 12 multiplied by 6 is 72, the missing number is 72.

7 0

3 years ago

Read 2 more answers

g In R simulate a sample of size 20 from a normal distribution with mean µ = 50 and standard deviation σ = 6. Hint: Use rnorm(20

Illusion [34]

Answer:

> a<-rnorm(20,50,6)

> a

[1] 51.72213 53.09989 59.89221 32.44023 47.59386 33.59892 47.26718 55.61510 47.95505 48.19296 54.46905

[12] 45.78072 57.30045 57.91624 50.83297 52.61790 62.07713 53.75661 49.34651 53.01501

Then we can find the mean and the standard deviation with the following formulas:

> mean(a)

[1] 50.72451

> sqrt(var(a))

[1] 7.470221

Step-by-step explanation:

For this case first we need to create the sample of size 20 for the following distribution:

$X\sim N(\mu = 50, \sigma =6)$

And we can use the following code: rnorm(20,50,6) and we got this output:

> a<-rnorm(20,50,6)

> a

[1] 51.72213 53.09989 59.89221 32.44023 47.59386 33.59892 47.26718 55.61510 47.95505 48.19296 54.46905

[12] 45.78072 57.30045 57.91624 50.83297 52.61790 62.07713 53.75661 49.34651 53.01501

Then we can find the mean and the standard deviation with the following formulas:

> mean(a)

[1] 50.72451

> sqrt(var(a))

[1] 7.470221

5 0

3 years ago

How do i do this? it doesn't make sense

Genrish500 [490]

Answer:

The answer is B. 581/90

Step-by-step explanation:

just divide 581 by 90 and you'll find that it is equivelent to 6.45

Hope that helps!

5 0

2 years ago

Read 2 more answers

Hi! I would like help on this, I’m a first-timer on brainly! The answer choices are:

sergeinik [125]

Answer:

Step-by-step explanation:

No matter what value you multiply a, the fraction will remain unchanged. That is because you can divide an a out from the numerator and the denominator. Thus, doubling a has no affect on the fraction, and in fact, u can simplify it to just bc. Now, if you halve b, it will simply just halve the actual value. When you halve b, you are simply executing (1/2)(b)(c). Therefore, you can rearrange the expression to be (1/2)(bc), which is just halving bc. If you decrease by 1/2, it's the same thing as being half of the value it was before. Therefore, the answer is b.

5 0

3 years ago

A manufacturer of chocolate candies uses machines to package candies as they move along a filling line. Although the packages ar

Elenna [48]

Answer:

We conclude that the mean amount packaged is equal to 8.17 ounces.

Step-by-step explanation:

We are given that in a particular sample of 50 packages, the mean amount dispensed is 8.171 ounces, with a sample standard deviation of 0.052 ounces.

Let $\mu$ = population mean amount packaged.

So, Null Hypothesis, $H_0$ : $\mu$ = 8.17 ounces {means that the mean amount packaged is equal to 8.17 ounces}

Alternate Hypothesis, $H_A$ : $\mu\neq$ 8.17 ounces {means that the mean amount packaged is different from 8.17 ounces}

The test statistics that will be used here is One-sample t-test statistics because we don't know about the population standard deviation;

T.S. = $\frac{\bar X-\mu}{\frac{s}{\sqrt{n} } }$ ~ $t_n_-_1$

where, $\bar X$ = sample mean amount dispensed = 8.171 ounces

s = sample standard deviation = 0.052 ounces

n = sample of packages = 50

So, the test statistics = $\frac{8.171-8.17}{\frac{0.052}{\sqrt{50} } }$ ~ $t_4_9$

= 0.1359

The value of t-test statistics is 0.1359.

Also, the P-value of test-statistics is given by;

the meaning of the p-value is that the p-value is the probability of obtaining a sample mean that is equal to or more extreme than 0.001 ounces away from8.17 if the null hypothesis is true.

P-value = P( $t_4_9$ > 0.136) = More than 40% {from the t-table}

Since the P-value of our test statistics is more than the level of significance of 0.01, so we have insufficient evidence to reject our null hypothesis as it will not fall in the rejection region.

Therefore, we conclude that the mean amount packaged is equal to 8.17 ounces.

6 0

3 years ago