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The results of the simple linear regression are provided below. Based on results below, interpret the p-value for testing whether B exceeds 0. * ŷ = -2,700 + 20x Sxy = 65, two – tailed p – value = 0.034 (for testing A %3D

The results of the simple linear regression are provided below. Based on results below, interpret the p-value for testing whether B exceeds 0. * ŷ = -2,700 + 20x Sxy = 65, two – tailed p – value = 0.034 (for testing A %3D

Trigonometry (MindTap Course List)
Trigonometry (MindTap Course List)
8th Edition
ISBN:9781305652224
Author:Charles P. McKeague, Mark D. Turner
Publisher:Charles P. McKeague, Mark D. Turner
Chapter4: Graphing And Inverse Functions
Section: Chapter Questions
Problem 6GP: If your graphing calculator is capable of computing a least-squares sinusoidal regression model, use...
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The large national bank charges local companies for using their services. A bank official reported the results of a regression analysis designed to predict the bank's charges (Y), measured in RM per month for services rendered to local companies. One independent variable used to predict service charge to a company is the the company's sales revenue (X), measured in millions of RM. Data for 21 companies who use the bank's services were used to fit the model. The results of the simple linear regression are provided below. Based on results below, interpret the p-value for testing whether B exceeds 0. * ŷ = -2,700 + 20X Sxy = 65, two – tailed p – value = 0.034 (for testing B1 There is sufficient evidence (at the alpha = 0.05) to conclude that sales revenue (X) is a useful linear predictor of service charge (Y). There is insufficient evidence (at the alpha = 0.10) to conclude that sales revenue (X) is a useful linear predictor of service charge (Y). O Sales revenue (X) is a poor predictor of service charge (Y). For every RM1 million increase in sales revenue, we expect a service charge to increase RM0.034.
Transcribed Image Text:The large national bank charges local companies for using their services. A bank official reported the results of a regression analysis designed to predict the bank's charges (Y), measured in RM per month for services rendered to local companies. One independent variable used to predict service charge to a company is the the company's sales revenue (X), measured in millions of RM. Data for 21 companies who use the bank's services were used to fit the model. The results of the simple linear regression are provided below. Based on results below, interpret the p-value for testing whether B exceeds 0. * ŷ = -2,700 + 20X Sxy = 65, two – tailed p – value = 0.034 (for testing B1 There is sufficient evidence (at the alpha = 0.05) to conclude that sales revenue (X) is a useful linear predictor of service charge (Y). There is insufficient evidence (at the alpha = 0.10) to conclude that sales revenue (X) is a useful linear predictor of service charge (Y). O Sales revenue (X) is a poor predictor of service charge (Y). For every RM1 million increase in sales revenue, we expect a service charge to increase RM0.034.
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