The method used to calculated the best straight line through a set of data is called linear regression. It is also called the least squares method. I've included two links. I know the wikipedia link is a bit complicated. The slope and intercept are calculated based on "minimum least squares." If I draw a line through the set if points, for every x value in the data set I will have a y value and a predicted y value (y-hat) based on the straight line. The error (E) is this case is the predicted y minus the actual y. Linear regression finds the slope and intercept of the equation that minimizes the sum of the square of the errors. Mathematically this is stated as: Min z = sum (yi - y-hat)^2 To hand calculate a linear regression line wold take some time. The second link that I've included shows how to calculated this using excel.
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invers tangent(slope)
Yes, but not at the level of mathematics you are at. In elementary statistics, the line of best fit (if it exists) is always a straight line representing a linear relationship between two variables. The equation of the line is most often calculated using the least squares method. [This minimises the sum of the squares of the vertical differences between the values "predicted" by the line and those actually recorded. The process always leads to a straight line. However, in more advanced statistics, you will learn about transformations. If the relationship between two variables, X and Y, is an inverse relationship, then the relationship between 1/X and Y is linear and you can fit a linear best fit line to the data set given by 1/X and Y. This can then be used to calculate the best fit inverse curve.
Acceleration = Final velocity - Initial velocity / time
Yes. If it is not straight, then it is not a line.
There are very many summary statistics and the answer depends on which of the ones that are appropriate you are interested in.