What number do you get when you multiply all of the numbers on a telephone's number pad?

1 answer:

7 0

Assuming that the telephone's number pad has the numbers 0,1,2,3,4,5,6,7,8,9 the product will be 0

You might be interested in

A store has apples on sale for $14.00 for 4 pounds. If an apple is approximately 5 ounces, how many apples can you buy for $84.0

adelina 88 [10]

For blank 1:
$14 for 4 pounds. so 84/14= 6, then 6x4= 24. 24 pounds of apples
For blank 2:
If an apple is approx 5 ounces, 16/5 isn't a whole number, but 15/5 is, so 3, There are about 3 apples in each pound
For blank 3:
3 apples in each pound, and you can buy 24 pounds, 3x24=72

4 0

3 years ago

Read 2 more answers

ali wants to buy a piano the piano measures 19/4 feet long she has a space 5 feet long for the paino in her house. does she have

IceJOKER [234]

Yes. This is because 19/4 as a mixed number is 4 3/4. 4 3/4 < 5. It might be a tight fit but she has enough room

Please vote the brainliest!

8 0

3 years ago

Use the information provided to determine a 95% confidence interval for the population variance. A researcher was interested in

Leno4ka [110]

Answer:

The 95% confidence interval for the population variance is (8.80, 32.45).

Step-by-step explanation:

The (1 - α)% confidence interval for the population variance is given as follows:

$\frac{(n-1)\cdot s^{2}}{\chi^{2}_{\alpha/2}}\leq \sigma^{2}\leq \frac{(n-1)\cdot s^{2}}{\chi^{2}_{1-\alpha/2}}$

It is provided that:

n = 20

s = 3.9

Confidence level = 95%

⇒ α = 0.05

Compute the critical values of Chi-square:

$\chi^{2}_{\alpha/2, (n-1)}=\chi^{2}_{0.05/2, (20-1)}=\chi^{2}_{0.025,19}=32.852\\\\\chi^{2}_{1-\alpha/2, (n-1)}=\chi^{2}_{1-0.05/2, (20-1)}=\chi^{2}_{0.975,19}=8.907$

*Use a Chi-square table.

Compute the 95% confidence interval for the population variance as follows:

$\frac{(n-1)\cdot s^{2}}{\chi^{2}_{\alpha/2}}\leq \sigma^{2}\leq \frac{(n-1)\cdot s^{2}}{\chi^{2}_{1-\alpha/2}}$

$\frac{(20-1)\cdot (3.9)^{2}}{32.852}\leq \sigma^{2}\leq \frac{(20-1)\cdot (3.9)^{2}}{8.907}\\\\8.7967\leq \sigma^{2}\leq 32.4453\\\\8.80\leq \sigma^{2}\leq 32.45$