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2. Explain how a line of best fit can be used to make predictions. You explanation should be at least 3-4 sentences and include at least 6 of the following words.
-line of best fit
- slope
-y-intercept
- prediction
-ordered pair
-independent variable
-dependent variable
- x axis
- y axis

Sagot :

A line of best fit is a straight line drawn through a scatter plot of data points that best represents the relationship between the independent variable (x-axis) and the dependent variable (y-axis). The equation of this line typically takes the form [tex]\( y = mx + b \)[/tex], where [tex]\( m \)[/tex] is the slope and [tex]\( b \)[/tex] is the y-intercept. By using the line of best fit, we can make predictions about the dependent variable for given values of the independent variable. For any given [tex]\( x \)[/tex] value, we can substitute this value into the equation to find the corresponding [tex]\( y \)[/tex] value, which represents our prediction. This method allows us to estimate outcomes for new data within the range of the observed data, based on the apparent trend shown by the ordered pairs plotted on the graph.