Answer: the anwser is 5 trust me
Step-by-step explanation:
<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.
Answer:
neither
Step-by-step explanation:
<em>Both statements are correct.</em>
If matrix 1 has dimensions (r1, c1) and matrix 2 has dimensions (r2, c2), their product can be formed if c1 = r2. The resulting product matrix will have dimensions (r1, c2).
Answer:
$26.25
Step-by-step explanation:
multiply 350 by 0.075
Answer:
18
Step-by-step explanation:
18 x 8.3 = 149.4
