The city's transportation department is interested in studying the relationship between the temperature and the number of passengers that ride the main bus line in order to better serve their customers. The manager recorded the temperature at the beginning of the hour, and then had a bus driver record the number of passengers that boarded the bus throughout the hour. Their findings are listed below. Temperature(X) Passengers(Y) 42 273 37 249 46 285 30 223 48 299 43 274 43 275 46 288 46 286 49 298 Use the above information to obtain a least-squares regression equation, and find r. Slope Intercept Correlation Coefficient (r)
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Mean of X (Temperature) = $\frac{273 + 249 + 285 + 223 + 299 + 274 + 275 + 288 + 286 + 298}{10} = \frac{2750}{10} = 275$ Mean of Y (Passengers) = $\frac{274 + 275 + 288 + 286 + 298}{5} = \frac{1421}{5} = 284.2$ Show more…
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The city's transportation department is interested in studying the relationship between the temperature and the number of passengers that ride the main bus line in order to better serve their customers. The manager recorded the temperature at the beginning of the hour, and then had a bus driver record the number of passengers that boarded the bus throughout the hour. Their findings are listed below.
Frank D.
The city's transportation department is interested in studying the relationship between the outside temperature and the number of passengers that ride the main bus line in order to better serve their customers. The manager recorded the temperature at the beginning of the hour and then had a bus driver record the number of passengers that boarded the bus throughout the hour. Calculate the Pearson's correlation coefficient for the dataset below and interpret what that means. temperature passengers 95.3 25 96.7 28 82.9 24 93.4 29 81.6 25 94.4 23 87.7 22 91.8 27 97.5 32 87.8 28 1) The correlation is 0.494 . There is a moderate negative linear association between temperature and passengers . 2) The correlation is -0.494 . There is a moderate negative linear association between temperature and passengers . 3) The correlation is -0.494 . There is a moderate positive linear association between temperature and passengers . 4) The correlation is 0.494 . There is a moderate positive linear association between temperature and passengers . 5) The correlation is 0.494 . There is a perfect positive linear association between temperature and passengers .
T. L.
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