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Content * OneNote x 1 Rachael @ Seneca x b do i round up sample size - B x + G https:/learn.senecacollege.ca/ultra/courses/_645984_1/cloutline X Remaining Time:
Content * OneNote x 1 Rachael @ Seneca x b do i round up sample size - B x + G https:/learn.senecacollege.ca/ultra/courses/_645984_1/cloutline X Remaining Time: 19 minutes, 09 seconds. Less than half of the time remains. Question Completion Status: Question 12 I points Saveit What is the independent variable using the table below showing the regression of happiness and wealth? SUMMARY OUTPUT Regression Statistics Multiple R 0.12185 R Square 0.03177 Adjusted R Square 0.02722 Standard Error D.06799 Observations Coefficients Intercept 9.5111 Happiness 9.1659 Happiness Intercept Wealth Oit's written y = a + bx) In Excel, "Multiple R" = coefficient of correlation Timed Test This test has a time limit of 1 hour and 50 minutes.You will be notified when time expires, and you may continue or submit. Warnings appear when half the time, 5 minutes, 1 minute, and 30 seconds remain. Multiple Attempts This test allows 2 attempts. This is attempt number 1. Force Completion Once started, this test must be completed in one sitting. Do not leave the test before clicking Save and Submit. Your answers are saved automatically. Remaining Time: 19 minutes, 39 seconds. Less than half of the time remains. Question Completion Status; Moving to another question will save this response. Question 9 of 25 Question 9 1 points Save Answer The claim for a marketing campaign is that 0.26 clients respond, and you want to prove it is less. Your survey of 264 clients showed 66 respond. Test the hypothesis at a 1 % level of significance, Calculate the Critical Decision Rule. Moving to another question will save this response. Question 9 of 25 USC 9 0 P W R T U Q abD Content OneNote x Rachael @ Seneca x b do i round up sample size - B x |+ G @ https:/learn.senecacollege.ca/ultra/courses/_645984_1/cl/outline X Remaining Time: 19 minutes, 01 second. Less than half of the time remains, Question Completion Status: 1 20 30 4 53 65 719 85 9 105 170 125 135 145 156 165 175 181 195 201 211 2215 235 245 2515 What is the equation using the table below showing the regression of profits and assets? SUMMARY OUTPUT Regression Statistics Multiple R 0.9818 R Square 0.9639 Adjusted R Square 0.9552 Standard Error 3.7981 Observations Coefficients Intercept 13.1174. Assets 0.5688 y = 13.1174 + 0,56BB(assets) O y = 13.1174 + 3.7981(assets) y = 13.1174 + 0.5688(profits) Q y = 0.5688 + 13.1174(profits)X Remaining Time: 18 minutes, 16 seconds. Less than half of the time remains. Question Completion Status: 1 20 30 4 5 69 71 8 9 105 115 125 20 141 156 150 173 181 190 204 210 271 2319 241 256 Question 21 1 points Saved Interpret the coefficient of correlation using the table below? SUMMARY OUTPUT Regression Statistics Multiple R 0.99085 R Square 0.98177 Adjusted R Square 0.97722 Standard Error 2.96799 Observations Coefficients Intercept 3.19861 X Variable 1 1.03439 3.1986 is the determination of the interception 98.177% of the change in the y variable is explained by this x variable the correlation is strong and positive in direction .) 98.085% of the change in the y variable is explained by our x variable S 8 9 5 2 P U R WContent * OneNote X Rachael @ Seneca x. | L do i round up sample size - But x | + G https://learn.senecacollege.ca/ultra/courses/_645984_1/cl/outline to X Remaining Time: 17 minutes, 54 seconds. Less than half of the time remains. Question Completion Status: 74 25 31 4 50 69 76 81 9 106 116 120 131 141 151 161 174 180 19 201 21 225 236 245 250 Click Submit to complete this assessment. Question 25 of 25 Question 25 1 points Saved Interpret the coefficient of determination using the table below? SUMMARY OUTPUT Regression Statistics Multiple R 0.9917 R Square 0.9834 Adjusted R Square 0.9772 Standard Error 2.9781 Observations Coefficients Intercept 6.7476 X Variable 1 1.6674 99.17% of the change in the y variable is explained by our x variable 6.7476 is the determination of the interception )the correlation is strong and positive in direction 98.34% of the change in the y variable is explained by this x variable
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