Question

Fit a straight line to following data x o. 1 2 3. 4 y 1.0. 1.8. 3.3. 4.5. 6.3.

Answer 1

Answer:

ur question is n

ot correct frn.plz explain again

Answer 2

Answer:

The straight line to fit the given data is found to be: $y=1.33x+0.72$

Explanation:

The data given is of two arrays as shown in the attached table.

We know that the equation for the line of regression that fits the given data is given by:

$y=a+bx$

where $a$ and $b$ are given by the following expressions:

$b=\frac{(n\times \sum x_iy_i)-(\sum x_i \sum y_i)}{(n\times \sum x_i^2)-(\sum x_i)^2}$

$a=\frac{\sum y_i-b(\sum x_i)}{n}$

Using the values from the attached table, we get the value of slope (b), as:

$b=\frac{(5\times 47.100)-(10\times 16.9)}{(5\times 30)-100}$

which we gives us:

$b=1.33$

Similarly, using the values of table to find the value of intercept (a), we get:

$a=\frac{16.9-10(1.33)}{5}$

which gives us:

$a=0.72$

Which gives us the line of best fit as:

$y=1.33x+0.72$

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