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The scatterplot and line of best-fit show puppies' weights over time. Which equation best represents the line of best fit? y=1.8 x+1.1 y=1.2 x+0.9 y=0.9 x+1.2 y=1.1 x+1.8

The scatterplot and line of best-fit show puppies' weights over time.\newlineWhich equation best represents the line of best fit?\newliney=1.8x+1.1y=1.8x+1.1\newliney=1.2x+0.9y=1.2x+0.9\newliney=0.9x+1.2y=0.9x+1.2\newliney=1.1x+1.8y=1.1x+1.8

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Q. The scatterplot and line of best-fit show puppies' weights over time.\newlineWhich equation best represents the line of best fit?\newliney=1.8x+1.1y=1.8x+1.1\newliney=1.2x+0.9y=1.2x+0.9\newliney=0.9x+1.2y=0.9x+1.2\newliney=1.1x+1.8y=1.1x+1.8
  1. Analyze Scatterplot Trend: Analyze the scatterplot to determine the general trend of the data points. Assuming the scatterplot shows a positive linear trend, we need to find the line of best fit that closely matches this trend.
  2. Compare Equation Slopes: Compare the slope of each given equation to the trend observed in the scatterplot. If the scatterplot shows a steep positive slope, equations with higher slope values are more likely candidates.
  3. Calculate Approximate Slope: Calculate the approximate slope from the scatterplot.\newlineAssuming the scatterplot data points range from (0,1)(0,1) to (10,20)(10,20), the slope mm can be calculated as:\newlinem=20−110−0=1910=1.9m = \frac{20 - 1}{10 - 0} = \frac{19}{10} = 1.9

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