A study was carried out to relate sales revenue y (in thousands of dollars) to advertising expenditure x (also in thousands of dollars) for fast-food outlets during a 3 month period. A sample of 15 outlets yielded the accompanying summary quantities. = = 1438.30 Σ - - 14.30 ΣΥ - 1438.30 Σχ2 = 13.95 X Σγ2 = 140,355 Σχ = 1388.20 -2401.87 -2 - 561.45 Σε - γ2 = 24 Σε (a) What proportion of observed variation in sales revenue can be attributed to the linear relationship between revenue and advertising expenditure? (Give the answer to three decimal places.) 0.766 (b) Calculate s₂ and sы. (Give the answers to four decimal places.) Se Sb = 6.5718 = 11.6661 (c) Obtain a 90% confidence interval for b, the average change in revenue associated with a $1000 (that is, 1 unit) increase in advertising expenditure. (Give the answers to three decimal places.) (32.977 × 74.296 × )

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A study was carried out to relate sales revenue y (in thousands of dollars) to advertising expenditure x (also in thousands of dollars) for fast-food outlets during a 3 month period. A sample of 15 outlets yielded
the accompanying summary quantities.
=
= 1438.30
Σ - - 14.30 ΣΥ - 1438.30 Σχ2 = 13.95
X
Σγ2 = 140,355 Σχ
= 1388.20
-2401.87 -2 - 561.45
Σε - γ2 = 24
Σε
(a) What proportion of observed variation in sales revenue can be attributed to the linear relationship between revenue and advertising expenditure? (Give the answer to three decimal places.)
0.766
(b) Calculate s₂ and sы. (Give the answers to four decimal places.)
Se
Sb
= 6.5718
= 11.6661
(c) Obtain a 90% confidence interval for b, the average change in revenue associated with a $1000 (that is, 1 unit) increase in advertising expenditure. (Give the answers to three decimal places.)
(32.977
×
74.296
× )
Transcribed Image Text:A study was carried out to relate sales revenue y (in thousands of dollars) to advertising expenditure x (also in thousands of dollars) for fast-food outlets during a 3 month period. A sample of 15 outlets yielded the accompanying summary quantities. = = 1438.30 Σ - - 14.30 ΣΥ - 1438.30 Σχ2 = 13.95 X Σγ2 = 140,355 Σχ = 1388.20 -2401.87 -2 - 561.45 Σε - γ2 = 24 Σε (a) What proportion of observed variation in sales revenue can be attributed to the linear relationship between revenue and advertising expenditure? (Give the answer to three decimal places.) 0.766 (b) Calculate s₂ and sы. (Give the answers to four decimal places.) Se Sb = 6.5718 = 11.6661 (c) Obtain a 90% confidence interval for b, the average change in revenue associated with a $1000 (that is, 1 unit) increase in advertising expenditure. (Give the answers to three decimal places.) (32.977 × 74.296 × )
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