Altitude, x |
Speed of sound, y |
|
00 |
1116.41116.4 |
|
55 |
1097.51097.5 |
|
1010 |
1075.71075.7 |
|
1515 |
1055.61055.6 |
|
2020 |
1036.81036.8 |
|
2525 |
1016.91016.9 |
|
3030 |
994.6994.6 |
|
3535 |
969.7969.7 |
|
4040 |
968.8968.8 |
|
4545 |
968.8968.8 |
|
5050 |
968.8968.8 |
(a) D is the plot you should select
(b) -0.971
(c) inverse linear relation
Altitude, x Speed of sound, y 00 1116.41116.4 55 1097.51097.5 1010 1075.71075.7 1515 1055.61055.6 2020 1036.81036.8...
How do you determine if there is sufficient evidence or if there is a significant linear correlation? The accompanying table shows eleven altitudes (in thousands of feet) and the speeds of sound in feet per second) at these altitudes. Complete parts (a) through (d) below. Click here to view the data table. Click here to view the table of critical values for the Pearson correlation coefficient. (a) Display the data in a scatter plot. Choose the correct graph below. OA...
Data on the fuel consumption ?y of a car at various speeds ?x is given. Fuel consumption is measured in mpg, and speed is measured in miles per hour. Software tells us that the equation of the least‑squares regression line is ?̂ =55.3286−0.02286?y^=55.3286−0.02286x Using this equation, we can add the residuals to the original data. Speed 1010 2020 3030 4040 5050 6060 7070 8080 Fuel 38.138.1 54.054.0 68.468.4 63.663.6 60.560.5 55.455.4 50.650.6 43.843.8 Residual −17.00−17.00 −0.87−0.87 13.7613.76 9.199.19 6.316.31 1.441.44...