For many countries tourism is an important source of revenue. Data are collected on the number of foreign visitors to a country (in millions) and total tourism revenue (in billions of dollars) for a sample of 10 countries. Below is the regression analysis output with tourism revenue as the dependent variable. Based the calculated t-statistic (which you need to calculate) for the slope, we can conclude at the .05 level of significance that Regression Analysis: Tourism ($ bill) versus Visitors (mill) The regression equation is Tourism ($ bill) = 21.5 + 0.295 Visitors (mill) Predictor Constant Coef 21.464 Visitors (mill) 0.29497 SE Coef 3.462 0.07917 wwwwwww S = 2.58307 R-Sq = 63.4% T P a. We reject the null hypothesis and conclude that the regression equation is significant. b. We accept the null hypothesis and conclude that the regression equation is significant. Oc. We accept the null hypothesis and conclude that the regression equation is not significant. O d. We reject the null hypothesis and conclude that the regression equation is not significant. e. Not enough information is given to arrive at a conclusion.
For many countries tourism is an important source of revenue. Data are collected on the number of foreign visitors to a country (in millions) and total tourism revenue (in billions of dollars) for a sample of 10 countries. Below is the regression analysis output with tourism revenue as the dependent variable. Based the calculated t-statistic (which you need to calculate) for the slope, we can conclude at the .05 level of significance that Regression Analysis: Tourism ($ bill) versus Visitors (mill) The regression equation is Tourism ($ bill) = 21.5 + 0.295 Visitors (mill) Predictor Constant Coef 21.464 Visitors (mill) 0.29497 SE Coef 3.462 0.07917 wwwwwww S = 2.58307 R-Sq = 63.4% T P a. We reject the null hypothesis and conclude that the regression equation is significant. b. We accept the null hypothesis and conclude that the regression equation is significant. Oc. We accept the null hypothesis and conclude that the regression equation is not significant. O d. We reject the null hypothesis and conclude that the regression equation is not significant. e. Not enough information is given to arrive at a conclusion.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Transcribed Image Text:For many countries tourism is an important source of revenue. Data are collected on the number of foreign visitors to a country (in
millions) and total tourism revenue (in billions of dollars) for a sample of 10 countries. Below is the regression analysis output with tourism
revenue as the dependent variable. Based the calculated t-statistic (which you need to calculate) for the slope, we can conclude at the .05
level of significance that
Regression Analysis: Tourism ($ bill) versus Visitors (mill)
The regression equation is
Tourism ($ bill) = 21.5 + 0.295 Visitors (mill)
Predictor
Constant
Coef
21.464
Visitors (mill) 0.29497
SE Coef
3.462
0.07917
wwwwwww
S = 2.58307
R-Sq = 63.4%
T P
a. We reject the null hypothesis and conclude that the regression equation is significant.
b. We accept the null hypothesis and conclude that the regression equation is significant.
Oc. We accept the null hypothesis and conclude that the regression equation is not significant.
O d. We reject the null hypothesis and conclude that the regression equation is not significant.
e. Not enough information is given to arrive at a conclusion.
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