A common misconception in statistics is confusing correlation with causation. If two events are correlated, it merely means that they share the same behaviour over time, but it doesn't imply in any way that those event are related by a common cause, or even worse, that one implies the other.
You can find several (even humorous) counter examples online. For example, if you plot the number of reported pirates assault against the global temperature in the last years, you'll se that temperature is rising (unfortunately...) while pirates are almost disappearing.
One could observe this strong negative correlation and claim that hotter climate has solved the pirate issue. Of course this is a joke, but it explains why you shouldn't confuse correlation with causation.
Answer:
Step-by-step explanation:
Your question is not complete.
According to what do we validate with the equation.
add more info in the question because all of them can be true without any condition given or validation.
Answer:
35
Step-by-step explanation:
4 x 15 = 60
-4 x 5 = - 20
-1 x 5 = -5
60 - 20 - 5 = 35
First one; substitute x into the equation and see if the result equal y in the coordinate
Answer:
34
Step-by-step explanation:
The mean is calculated as
mean = 
let x be the missing frequency, then
Total frequency × midpoint
= (16 × 2) + 7x + (20 × 12) + (10 × 17) = 32 + 7x + 240 + 170 = 442 + 7x
Total frequency = 16 + x + 20 + 10 = 46 + x, thus
= 8.5 ( cross- multiply )
442 + 7x = 8.5(46 + x)
442 + 7x = 391 + 8.5x ( subtract 8.5x from both sides )
442 - 1.5x = 391 ( subtract 442 from both sides )
- 1.5x = - 51 ( divide both sides by - 1.5 )
x = 34
The missing frequency is 34
