1. Subtract the largest number with the smallest number... e.g. 100 - 25
2. Divide the range by 5 and 10... e.g 75/10= 7.5 75/5=15
3. Pick the number between 5 and 10... e.g. 7.5
4. Round to the largest whole number... e.g. 8
5. Add 8 to the smallest number of the range 5 times... e.g. 25 + 8, 33 +8, etc
6. You'll want to have it so the previous number becomes your beginning of your intervals... e.g. 25-33, 33-41, 41-49, 49-57, 57-65.
6. Fill your histogram
<span>Jamie bought a hand cover fiction book with $32.99 price.
She has a coupon that has a 15% off.
The store offers 20% off
x= how much will she save?
=> 20% = 20/100
=> .20
=> 15% = 15/100
=> .15
=> .20 + .15
=> .35
=> The amount is 32.99, multiply this by .35
=> 32.99 x .35
=> 11.5465 – She saved $11.55
=> 32.99 – 11.5465
=> 21.4435 – She only paid 21.4435 for her hand cover fiction book that she
bought.</span>
<span>
</span>
The answer to your question is c
Answer: room 101 and room 107
Step-by-step explanation:
In room 101, the ratio of boys to girls is 16:12. This is further simplified to its lowest fraction by dividing by 4. It becomes 4:3
In room 104, the ratio of boys to girls is 20:9. This cannot be further simplified to its lowest fraction.
In room 107, the ratio of boys to girls is 12:9. This is further simplified to its lowest fraction by dividing by 3. It becomes 4:3
Therefore, room 101 and room 107 have the same ratio.
Answer:
"A Type I error in the context of this problem is to conclude that the true mean wind speed at the site is higher than 15 mph when it actually is not higher than 15 mph."
Step-by-step explanation:
A Type I error happens when a true null hypothesis is rejected.
In this case, as the claim that want to be tested is that the average wind speed is significantly higher than 15 mph, the null hypothesis has to state the opposite: the average wind speed is equal or less than 15 mph.
Then, with this null hypothesis, the Type I error implies a rejection of the hypothesis that the average wind speed is equal or less than 15 mph. This is equivalent to say that there is evidence that the average speed is significantly higher than 15 mph.
"A Type I error in the context of this problem is to conclude that the true mean wind speed at the site is higher than 15 mph when it actually is not higher than 15 mph."
