<h2>
Answer with explanation:</h2>
When there is a linear relationship is observed between the variables, we use linear regression predict the relationship between them.
Also, we predict the values for dependent variable by modelling a linear model that best fits the data by drawing a line Y=a+bX, where X is the explanatory variable and Y is the dependent variable.
In other words: The line of best fit is a line through a scatter plot of data points that best describes the relationship between them.
That's why the regression line referred to as the line of best fit.
<span><span><span>2<span>c5</span></span>+<span>44<span>c4</span></span></span>+<span>242<span>c3</span></span></span><span><span><span>2<span>c5</span></span>+<span>44<span>c4</span></span></span>+<span>242<span>c3</span></span></span><span>=<span><span><span>2<span>c3</span></span><span>(<span>c+11</span>)</span></span><span>(<span>c+11</span><span>)</span></span></span></span>
Answer:
-1 and 5
Step-by-step explanation:
Answer:
D
Step-by-step explanation:
