Answer: 2/15
Step-by-step explanation:
2 red
2 blue
2 white
6 total
2/6 chance of getting red (1/3)
2/5 chance of getting blue next
2/5*1/3 = 2/15
I think. Sorry if I’m wrong.
Answer:y=7x+y
Step-by-step explanation:
against wind the speed = x-y
distance traveled = 2460
2460/x-y= 6
6x-6y= 2460
x-y=410...........1
..
with wind speed = x+y
distance is same 2460
2460/x+y=5
5x+5y=2460
x+y=492............2
..
Add equation 1 & 2
x-y+x+y=410+492
2x=902
x= 451 mph speed of plane in still air.
..
Plug the value of x in equation 1
451-y=410
y=451-410
y=40 mph the speed of wind
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Your feed back about the solution is very important in improvement.
Answer: <span>This is an example of correlation but not causation.
Explanation:
The statement "when more apples grew in the backyard, the pet cat stayed indoors for a longer time" is an excellent example to explain the difference between causation and correlation.
Is the very fact that the apples grew in the backyard what makes the pet cat stay indoors longer?
Sure, you know it isn't. Sure there is another cause that influence both the growing of apples and the time the pet cats stay indoor. So, there is not a causality relationship.
Given that some fact is influencing both phenomena, you find that they behave in a way that one permits predict the other, which is what correlation indicates, but not that one is the cause of the other.
When you know the cause you might change the final behavior, but when you know that the variables are correlated you just can use one to predict the other.
In this example, if you see that more apples grow in the backyard you can predict that the cat pets will stay indoors for a longer time, but you can do nothing to modify the time the pet cats stay indoors because you do not the reason why they are doing that.
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Answer:
The data is skewed to the bottom and contains an outlier.
Step-by-step explanation:
1. Test for outlier
An outlier is a point that is more than 1.5IQR below Q1 or above Q3.
IQR = Q3 - Q1 = 74 - 51 = 23
1.5 IQR = 1.5 × 23 = 34.5
51 - 15 = 36 > 1.5IQR
The point at 15 is an outlier.
2. Test for normal distribution
The median is not in the middle of the box.
Rather, it cuts the box into two unequal parts, so the data does not have a normal distribution.
3. Test for skewness
The longer part is to the left of the median, so the data is skewed left.