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Use the table of values to find the line of regression and if justified at the 0.05 significance level, use it to find the predicted quality score of a TV set with a price of $1900. If the data does not suggest linear correlation, then use the average quality score as a prediction.
Price: 2,300, 1,800, 2,500, 2,700, 2,000, 1,700, 1,500, 2,700
Quality Score: 74, 73, 70, 66, 63, 62, 52, 68

Respuesta :

shallomisaiah19

Answer:

Step-by-step explanation:

no          x                y                   xy                               x²

1           2300         74             170200                      5290000

2          1800          73             131400                      3240000

3          2500         70             175000                     6250000

4          2700         66             178200                     7290000

5          2000         63             126000                     4000000

6          1700          62             105400                     2890000

7           1500         52              78000                      2250000

8           2700        68              183600                    7290000

Total   17200         528           1147800                   38500000

Mean of x is

[tex]\bar x = \frac{17200}{8} =2150[/tex]

Mean of y is

[tex]\bar y = \frac{528}{8} =66[/tex]

From the table above

we find [tex]\hat B_1[/tex]

[tex]\hat B_1=\frac{\sum xy- \bar x \sum y}{\sum x^2- n \barx^2} \\\\=\frac{1147800-2150(528)}{38500000-8(2150)^2} \\\\=\frac{1147800-1135200}{38500000-36980000} \\\\=\frac{12600}{1520000} \\\\=0.008289[/tex]

so [tex]\hat b_0[/tex] is

[tex]\hat b_0=\bar y-\bar B_1 x\\\\=66-0.008289(2150)\\\\=66-17.82135\\\\=48.17865[/tex]

The line of regression is

The price x is 1900

[tex]\hat y =\hat B_0+\hat B_1x\\\\=48.17865+0.008289\times1900\\\\=48.17865+15.7491\\\\=63.928[/tex]

The line of regression is 63.928

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