<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.
1:
3*3=8 ;
8*3=23
23*3=68
68*3=204
1.3,8,23,68,204 ...
2.
2*3=6
6*3=18
18*3=54
2, 6,18,54
multiply all on 3)
X=37/5
or 7.4 in decimal form
The probability that the card is a football card is 20 out of 50 or 40%
the probability that the card is a basketball card is 10 out of 50 or 20%
