A block of mass m1=6.6 kg rests on a frictionless horizontal surface. A second block of mass m2=9.4 kg hangs from an ideal cord of negligible mass, which runs over an ideal pulley and then is connected to the side of the first block. The blocks are released from rest. How far will block 1 move during the 1.1 second interval?

A merry-go-round is a common piece of playground equipment. A 3.0-mm-diameter merry-go-round, which can be modeled as a disk with a mass of 220 kg, is spinning at 24 rpm. John runs tangent to the merry-go-round at 5.6 m/s, in the same direction that it is turning, and jumps onto the outer edge. John's mass is 30 kg.

A sprinter accelerates from rest to a top speed with an acceleration whose magnitude is 3.72 m/s2. After achieving top speed, he runs the remainder of the race without speeding up or slowing down. The total race is fifty meters long. If the total race is run in 7.85 s, how far does he run during the acceleration phase?

Programming language: C++  

suggested software: Code::Blocks

Develop an algorithm and write a C++ program that computes the final score of a baseball game. Use a loop to read the number of runs scored by both teams during each of nine innings. Display the final score afterward.

Submit your design, code, and execution result

via file, if possible

The starter motor of a car engine draws a current of 180A from the battery. The copper wire to the motor is 5.40mm in diameter and 1.2 m long. The starter motor runs for 0.960s until the car engine starts. How much charge passes through the starter motor? How far does an electron travel along the wire while the starter motor is on?

Use the given data set to complete parts​ (a) through​ (c) below.​ (Use

alphaαequals=​0.05.)

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Click here to view a table of critical values for the correlation coefficient.

a. Construct a scatterplot. Choose the correct graph below.

A.

04812160481216xy

A scatterplot has a horizontal x-scale from 0 to 16 in increments of 2 and a vertical y-scale from 0 to 10 in increments of 1. Eleven points are plotted with approximate coordinates as follows: (4, 1); (5, 1.4); (6, 1.6); (7, 2); (8, 2.4); (9, 3); (10, 3.6); (11, 4.2); (12, 4.8); (13, 6); (14, 8).

B.

04812160481216xy

A scatterplot has a horizontal x-scale from 0 to 16 in increments of 2 and a vertical y-scale from 0 to 10 in increments of 1. Ten points are plotted with approximate coordinates as follows: (4, 3.2); (6, 6.2); (7, 7.2); (8, 8.2); (9, 8.8); (10, 9.2); (11, 9.2); (12, 9.2); (13, 8.8); (14, 8.2).

C.

04812160481216xy

A scatterplot has a horizontal x-scale from 0 to 16 in increments of 2 and a vertical y-scale from 0 to 10 in increments of 1. Eleven points are plotted with approximate coordinates as follows: (4, 6); (5, 5.6); (6, 5); (7, 4.6); (8, 4); (9, 3.6); (10, 3); (11, 2.6); (12, 2); (13, 1.6); (14, 1).

D.

04812160481216xy

A scatterplot has a horizontal x-scale from 0 to 16 in increments of 2 and a vertical y-scale from 0 to 16 in increments of 2. Eleven points are plotted with approximate coordinates as follows: (4, 5.4); (5, 5.8); (6, 6); (7, 6.4); (8, 6.8); (9, 7.2); (10, 7.4); (11, 7.8); (12, 8.2); (13, 12.8); (14, 8.8).

b. Find the linear correlation​ coefficient, r, then determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables.

The linear correlation coefficient is

requals=nothing.

​(Round to three decimal places as​ needed.)

Using the linear correlation coefficient found in the previous​ step, determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables. Choose the correct answer below.

A.There is

sufficientsufficient

evidence to support the claim of a nonlinear correlation between the two variables.

B.There is

insufficientinsufficient

evidence to support the claim of a nonlinear correlation between the two variables.

C.There is

insufficientinsufficient

evidence to support the claim of a linear correlation between the two variables.

D.There is

sufficientsufficient

evidence to support the claim of a linear correlation between the two variables.

c. Identify the feature of the data that would be missed if part​ (b) was completed without constructing the scatterplot. Choose the correct answer below.

A.

The scatterplot does not reveal a perfect​ straight-line pattern, and contains one outlier.

B.

The scatterplot reveals a perfect​ straight-line pattern and does not contain any outliers.

C.

The scatterplot reveals a perfect​ straight-line pattern, except for the presence of one outlier.

D.

The scatterplot does not reveal a perfect​ straight-line pattern.

Consider the natural log transformation (“ln” transformation) of variables labour cost (L_COST), and total number of rooms per hotel (Total_Rooms). 4.1 Use the least squares method to estimate the regression coefficients b0 and b1 for the log-linear model 4.2 State the regression equation 4.3 Give the interpretation of the regression coefficient b1. 4.4 Give an interpretation of the coefficient of determination R2. Also, test the significance of your model using the F-test. How, does the value of the coefficient of determination affect the outcome of the above test? Test whether a 1% increase of the total number of rooms per hotel can increase the labour cost by more than 0.20%? Use the 5% level of significance for this test.

Consider the natural log transformation (“ln” transformation) of variables labour cost (L_COST), and total number of rooms per hotel (Total_Rooms). 4.1 Use the least squares method to estimate the regression coefficients b0 and b1 for the log-linear model 4.2 State the regression equation 4.3 Give the interpretation of the regression coefficient b1. 4.4 Give an interpretation of the coefficient of determination R2. Also, test the significance of your model using the F-test. How, does the value of the coefficient of determination affect the outcome of the above test?Test whether a 1% increase of the total number of rooms per hotel can increase the labour cost by more than 0.20%? Use the 5% level of significance for this test.

Consider the natural ln transformation (“ln” transformation) of variables labour cost (L_COST), and total number of rooms per hotel (Total_Rooms).

4.1 Use the least squares method to estimate the regression coefficients b0 and b1 for the log-linear model

4.2 State the regression equation 4.3 Give the interpretation of the regression coefficient b1. Give an interpretation of the coefficient of determination R2. Also, test the significance of your model using the F-test. How, does the value of the coefficient of determination affect the outcome of the above test?

4.4.Test whether a 1% increase of the total number of rooms per hotel can increase the labour cost by more than 0.20%? Use the 5% level of significance for this test.

You have just arrived at a SnappyPrints Inc., a maker of photo printers.  You are working in the Financial Planning department and have joined a team conducting capital budgeting analysis. Snappy is considering two new projects. Project Mini Printer (PMP) and Project High Speed Printer (HSP).  The WACC is 10%.  

                                   0                      1                      2                      3

                                   |                      |                      |                      |

Project PMP ($    -150                   40                   75                   100

Project PHS ($)   -150                   65                   75                    85

Answer the following questions:

14.  What is the payback period?  Find the discounted and regular paybacks for the Projects.

15.  What is the difference between the regular and discounted payback methods?

16.  What are the two main disadvantages of discounted payback?  Is the payback method useful in capital budgeting decisions?  Explain.

Upon further analysis, SnappyPrints believes that sales of the new High-Speed Printer would cannibalize the sales of its existing I-Phone Rapid Print Accessory by 50%, resulting in lost annual cash flow of $25.  

17. How can we define/what do we call this effect?
18. Should this effect be included in the cash flow projections?   
19. If so, which project should be accepted?