Please I need help solving this questions:

(1)

The decline of salmon fisheries along the Columbia River in Oregon has caused great concern among commercial and recreational fishermen. The paper 'Feeding of Predaceous Fishes on Out-Migrating Juvenile Salmonids in John Day Reservoir, Columbia River' (Trans. Amer. Fisheries Soc. (1991: 405-420)) gave the accompanying data on y = maximum size of salmonids consumed by a northern squaw fish (the most abundant salmonid predator) and x = squawfish length, both in mm. Use the following statistics to give the equation of the least squares regression line.

x= 525.050,y= 298.607,s_x= 16.236,s_y= 12.300,r= 0.9768

(2)Suppose that the LSRL for the appraised value (in thousands of dollars) and number of rooms for houses in East Meadow, New York is = 19.718x+ 74.80. Predict the price of a 11 room house (in thousands of dollars).

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(3) Select the equation of the least squares line for the data: (27.2, 1.50), (26.0, 3.75), (28.0, .75), (24.8, 7.50), (24.0, 6.75), (22.0, 9.75), (23.2, 7.50).

(4) Suppose you have the following data:

x123456y443729212514

and the LSRL isy

^

=5.543x+47.73

. Find the residual value forx= 1.

(5) If the LSRL relating the independent variablexand the dependent variableyfor a given problem is = 2x+ 3, then an increase of 1 unit inxis associated with an increase of how many units iny?

(6) The decline of salmon fisheries along the Columbia River in Oregon has caused great concern among commercial and recreational fishermen. The paper 'Feeding of Predaceous Fishes on Out-Migrating Juvenile Salmonids in John Day Reservoir, Columbia River' (Trans. Amer. Fisheries Soc. (1991: 405-420) gave the accompanying data on y = maximum size of salmonids consumed by a northern squaw fish (the most abundant salmonid predator) and x = squawfish length, both in mm. Here is the computer software printout of the summary:

Coefficients:EstimateStd. Errort valuePr(> |t|)(Intercept)90.02016.7025.3900.000Length0.7010.04415.7980.000

Using this information, give the equation of the least squares regression line.