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If most of them lie below the line, then that line isn't the best fit. The exact layout depends on what definition you use for "best fit", but any definition will produce a line that has roughly the same number of data points on each side of it.
Yes. The exception arises when you have outliers.
The straight line that best fits the data on a coordinate plane is the Line Of Best Fit.
The equation of the regression line is calculated so as to minimise the sum of the squares of the vertical distances between the observations and the line. The regression line represents the relationship between the variables if (and only if) that relationship is linear. The equation of this line ensures that the overall discrepancy between the actual observations and the predictions from the regression are minimised and, in that respect, the line is the best that can be fitted to the data set. Other criteria for measuring the overall discrepancy will result in different lines of best fit.
Find (or calculate) the equation of the line. Select any value of x. Calculate the corresponding value for y using the equation. Then (x, y) is a point on the same line.
If most of them lie below the line, then that line isn't the best fit. The exact layout depends on what definition you use for "best fit", but any definition will produce a line that has roughly the same number of data points on each side of it.
False
True. In a data plot, the line of best fit represents the average trend of the data. Therefore, approximately half of the data points should lie below the line of best fit and half should lie above it if the data is evenly distributed.
Yes. The exception arises when you have outliers.
A trend line is graphed from a linear, exponential, logarithmic or other equation, and trys to fit the sorted data that you have. But it may or may not be correlated. The line of best fit is the trend line that best fits your data, having a high correlation. R closer to 1.
A straight line equation
A trend equation is a regression equation that models the relationship between a variable and time. It is used to identify and forecast trends in data over time, helping to predict future values based on historical patterns. Trend equations can be linear or nonlinear, depending on the nature of the data being analyzed.
There is no equation there but the slope of the line is the number that multiplies x in the straight line equation y = mx + b whereas m is the slope and b is the y intercept
The straight line that best fits the data on a coordinate plane is the Line Of Best Fit.
Equation of a straight line is: y = mx+c whereas m is the slope and c is the y intercept
That of course would depend on the straight line equation that has not been given and so therefore an answer is not possible.
By finding the line of best fit and using the straight line equation formula.