I think there are 125 heart stickers and 375 star stickers. 20/4 = 5, so there are 5 heart stickers per sheet. there are 25 sheets in the package, 5 x 25 = 125. if the remaining stickers on a sheet are stars then there are 15 star stickers per sheet. 15 x 25 = 375.
Precision is a measure of how close a value is to the
ideal value. In this case, we calculate the difference to know what is the
closest to 4 g:
4.05 – 4 = 0.05
3.98 – 4 = -0.02
4.021 – 4 = 0.021
We can see that the value of 3.98g has the lowest
difference and is therefore the closest to 4g. Hence the most precise is:
<span>3.98 g</span>
Answer:
<u>Michelle has 17 pencils</u>
Step-by-step explanation:
Number of pencils Leslie has = 8 (She has 9 fewer pencils than Michelle)
Number of pencils Michelle has = 9 more than Leslie
How many pencils does Michelle have?
If Leslie has 8 and she has 9 fewer than Michelle, then:
Michelle has 9 more than Leslie
<u>Michelle has 9 + 8 = 17 pencils</u>
Do it in ratio form, 30/10=x/4, 30*4=120/10=12. it will be 12 centimeters long
Answer:
We know that In 1990, the mean duration of long-distance telephone calls originating in one town was 7.2 minutes. And we want to test if the mean duration of long-distance phone calls has changed from the 1990 mean of 7.2 minutes (alternative hypothesis) and the complement rule would represent the null hypothesis.
The correct system of hypothesis are:
Null hypothesis: 
Alternative hypothesis: 
So then the best option for this case would be:
H0: μ = 7.2 minutes Ha: μ ≠ 7.2 minutes
Step-by-step explanation:
We know that In 1990, the mean duration of long-distance telephone calls originating in one town was 7.2 minutes. And we want to test if the mean duration of long-distance phone calls has changed from the 1990 mean of 7.2 minutes (alternative hypothesis) and the complement rule would represent the null hypothesis.
The correct system of hypothesis are:
Null hypothesis: 
Alternative hypothesis: 
So then the best option for this case would be:
H0: μ = 7.2 minutes Ha: μ ≠ 7.2 minutes
And in order to test the hypothesis we can use a one sample t test or z test depending if we know the population deviation or not