Suppose that the average monthly low temperatures for a small town are shown in the table. Month 2. 3. 4567 S9 10 11 12 Temperature ("F) |19 27 38 45 57 62 65 58 51 41 33 25 Model this data using fox) -a sin(bix - c) + d. Use the sine regression feature to do this. Approximate all values to one decimal place. O a fox) - 22.5sin (0.5(x+ 1.6)) + 40.7 fox) = 22.5sin (0.5(x + 3.2)) + 40.7 %3D fox)= 22.5sin (1.25(x + 1.6)) + 40.7 fix) = 25.7sin (0.5(x + 1.6)) + 32.5

A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y).The results of the regression were :ŷ=a+bx a=20.874 b=-0.638 r2=0.894916 r=-0.946 Use this to predict the number of situps a person who watches 8 hours of TV can do (to one decimal place)  _________

You estimated a regression with the following output.         Source |       SS           df       MS      Number of obs   =       246 -------------+----------------------------------   F(1, 244)       =  16642.70        Model |   187647307         1   187647307   Prob > F        =    0.0000     Residual |  2751112.55       244  11275.0514   R-squared       =    0.9856 -------------+----------------------------------   Adj R-squared   =    0.9855        Total |   190398419       245  777136.405   Root MSE        =    106.18   ------------------------------------------------------------------------------            Y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval] -------------+----------------------------------------------------------------            X |   13.79687    .106947   129.01   0.000     13.58621    14.00753        _cons |   17.60822   9.208341     1.91   0.057    -.5297613     35.7462…

Use the scatterplot to determine the most likely regression equation. NORMAL FLOAT AUTO REAL RADIAN MP D = 4 + 2x None of these D = - 3x +5 It depends 1 D=5 -x 2