you research the cost of a gallon of gasoline over several years to look for trends the table shows the data you have collected what is the equation of the line of best fit how much would you expect to pay for gasoline in 2029
a)y=0.538x+1.36; $33.10
b) y=0.289x+1.75:$18.80
C y=0.052x+1.75;$4.82
d) y=0.25x+1.36;$2.84
i think x is the year im confused as to how the number with $ comes into play
Since I have no idea what the data were, I cannot tell which is the line of best fit.
The $ number is the result you get when plugging some value into the equation. Presumably it is the price of some given quantity of gasoline.
To find the equation of the line of best fit, you need to perform a linear regression analysis on the data. However, since you haven't provided the data table, we cannot determine the exact equation at this time.
Generally, the equation of a line is represented as y = mx + b, where y is the dependent variable, x is the independent variable, m is the slope of the line, and b is the y-intercept. By performing a linear regression analysis, you can find the values of m and b that best fit the data points.
Once you have the equation of the line, you can use it to predict the cost of gasoline in 2029. By plugging the value of x as 2029 into the equation, you can solve for y, which represents the predicted price of gasoline.
As for the options given, each option represents a different equation of the line of best fit and a predicted price for gasoline in 2029. To determine the correct option, you would need the actual data and perform the linear regression analysis.