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.
You divid it by two my dude
Answer:
<h2>The time needed is 10 months.</h2>
Step-by-step explanation:
The given points are (0, 3500) and (5, 1750).
First, we use the formula below to find the slope of the line
Which means the function is deacrasing with a ratio of 350 feet per month.
Now, we use the slope and one point to find the equation
This linear function shows that the situation started at the y-intecept (0, 3500), which means the month 0 had already 3500 feet. In other words, the total distance is 3500 feet. Now, the x-intercept will tell us the time needed to travel that distance.
Therefore, the time needed is 10 months.
Riley has 4 flavors
caleb had 2 flavors
4-2 equals 2
