x & y
If you are given 2 data points, you can do (y1-y2)/(x1-x2) with the points. Given two intercepts, you can assume points based on the intercepts (if the x-intercept is 7, then one data point is (7,0). Then you can do the above once you do the same for the y-intercept.
The y-Variable
The data points would be .4 and .21
Interpolation is a method of constructing new data points within the range of a discrete set of known data points. Basically it's a way of estimating certain values, based on information that is already given.
= -1 + 5x
If you are given 2 data points, you can do (y1-y2)/(x1-x2) with the points. Given two intercepts, you can assume points based on the intercepts (if the x-intercept is 7, then one data point is (7,0). Then you can do the above once you do the same for the y-intercept.
The y-Variable
The data points would be .4 and .21
a line of best fit
The mode is the number of repeated data points. There is not a mode in the data you have given.
Interpolation is a method of constructing new data points within the range of a discrete set of known data points. Basically it's a way of estimating certain values, based on information that is already given.
= -1 + 5x
A data point that is much larger or smaller than most of the other points in a given data set is called an outlier. Outliers can significantly affect statistical analyses and interpretations, often skewing results and leading to misleading conclusions. They may arise from variability in the data or may indicate measurement errors. Identifying and understanding outliers is crucial for accurate data analysis.
the average
The range of a set of data points is merely subtracting the lowest number from the highest number given in that set. For example, a data set that contains the points 4 ,7, 9, 20, 6, and 11, has the range of 20 - 4, or 16.
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.
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.