Question 1 A research wants to find out the relationship between the tuition in
ID: 2922349 • Letter: Q
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Question 1 A research wants to find out the relationship between the tuition in universities and the graduate rate Here is the output from data analysis. SUMMARY OUTPUT ression Statistics Multiple R R Square Adjusted R Square Standard Error 0.58832511 0.346126435 0.339454256 3450.412801 100 ANOVA MS Regression Residual Total 1 617602688.8 617602688.8 51.87606974 1.22163E-10 98 1166724152 11905348.49 99 1784326841 t Stat P-value Lower 95% r 95% Intercept Graduation Rate Coefficients Standard Error 14090.22209 1197.343915 11.76789886 1.87172E-20 11714.13206 16466.31212 164.5355232 22 84421 7202504408 1.22163E-10 119 2019319 209.8691145 1. Based on the above output, is the model significant/important? Explain why or why not. Based on the above output, can we claim that each of the parameter is significant? Explain why or why not. 2. 3. Is it a reliable model? How much variation is explained by this model? 4. What is the equation from the output? 5 University of Washington's graduate rate in 2015 is 61, what is the estimated tuition in University of Washington in 2015?Explanation / Answer
Answer to the question is as follows:
1. If the Significance F value is .05, then we can say that the model is significant. Since, F value is 1.22163E^-10 which is less than .05 , we conclude that model is significant
2. The only param Graduation Rate has a pvalue less than .05, indicating the the param is significant
3. It is not a very reliable model as the Rsquare is on the lower side. An Rsquare of just .346 means that 34.6% of the variation in tuition fees is being explained by the Graduation Rate.
4. The equation is 14090.22209 + 164.5355*Graudation Rate = Tuition
5. If in 2015 grad.rate = 61, then Tuition in 2015 is 61*164.5355+14090.22209 = $24,126.89
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