Actually, two separate points are enough to determine the line.
There are many ways, but probably you aren't in a statistics class, but in an algebra class. Step 1 plot all the data points on a coordinate plane graph (x-y graph) Step 2 estimate a line 'close' to points. Step 3 use 2 points ON THE LINE (these do not need to be data points) Step 4 find slope of line using points from step 3 Step 5 use point-slope formula to write the equation.
the average
y=(1/(sqrt(2*22/7)))*((e)power-((X squred)/2))
(the number of data points between 5 and 12)/(the total number of data points)
False
There are no "following" data!
-1.5
There are many ways, but probably you aren't in a statistics class, but in an algebra class. Step 1 plot all the data points on a coordinate plane graph (x-y graph) Step 2 estimate a line 'close' to points. Step 3 use 2 points ON THE LINE (these do not need to be data points) Step 4 find slope of line using points from step 3 Step 5 use point-slope formula to write the equation.
You could, but you need to decide what the point of doing so would be!
A graph is more informative than an equation because a graph is easier to interpret visually, and find all the points and line them up, rather than just a slope which shows no points(data).
The graph showed the results from his experiment. You can graph the data points to see what type of curve your equation defines.
by figuring out the equation
the average
you have to beet all misions on legendary. and you cant start at check points or else you loose your data.-SPARTAN2787 xbox live
Average is the sum of all data points divided by the number of data points. Median is the data point that is exactly halfway between the lowest and highest data points.
y=(1/(sqrt(2*22/7)))*((e)power-((X squred)/2))
To propagate error when averaging data points, calculate the standard error of the mean by dividing the standard deviation of the data by the square root of the number of data points. This accounts for the uncertainty in the individual data points and provides a measure of the uncertainty in the average.