Do heavier cars really use more gasoline? Suppose a car is chosen at random. Let x be the weight of the car (in hundreds of pounds), and let y be the miles per gallon (mpg). x 29 43 30 47 23 40 34 52 y 30 22 23 13 29 17 21 14

Complete parts (a) through (e), given Σx = 298, Σy = 169, Σx2 = 11,788, Σy2 = 3849, Σxy = 5906, and r ≈ −0.889.

(a) Draw a scatter diagram displaying the data.

(b) Verify the given sums Σx, Σy, Σx2, Σy2, Σxy, and the value of the sample correlation coefficient r. (Round your value for r to three decimal places.) Σx = Σy = Σx2 = Σy2 = Σxy = r =

(c) Find x, and y. Then find the equation of the least-squares line y hat = a + bx. (Round your answers for x and y to two decimal places. Round your answers for a and b to three decimal places.) x = y = y hat = + x (

d) Graph the least-squares line. Be sure to plot the point (x, y) as a point on the line. WebAssign Plot WebAssign Plot WebAssign Plot WebAssign Plot

(e) Find the value of the coefficient of determination r2. What percentage of the variation in y can be explained by the corresponding variation in x and the least-squares line? What percentage is unexplained? (Round your answer for r2 to three decimal places. Round your answers for the percentages to one decimal place.) r2 = explained % unexplained % (f) Suppose a car weighs x = 45 (hundred pounds). What does the least-squares line forecast for y = miles per gallon? (Round your answer to two decimal places.) mpg

Swifty Company purchased a delivery truck for $26,000 on January 1, 2020. The truck has an expected salvage value of $1,000, and is expected to be driven 100,000 miles over its estimated useful life of 10 years. Actual miles driven were 12,800 in 2020 and 12,000 in 2021.

Calculate depreciation expense per mile under units-of-activity method. (Round answer to 2 decimal places, e.g. 0.50.)

Depreciation expense

$

per mile

eTextbook and Media

List of Accounts

Compute depreciation expense for 2020 and 2021 using (1) the straight-line method, (2) the units-of-activity method, and (3) the double-declining-balance method. (Round depreciation cost per unit to 2 decimal places, e.g. 0.50 and depreciation rate to 0 decimal places, e.g. 15%. Round final answers to 0 decimal places, e.g. 2,125.)

				Depreciation Expense
				2020		2021
(1)		Straight-line method		$		$
(2)		Units-of-activity method		$		$
(3)		Declining-balance method		$		$

eTextbook and Media

List of Accounts

Assume that Swifty uses the straight-line method. Prepare the journal entry to record 2020 depreciation. (Credit account titles are automatically indented when amount is entered. Do not indent manually. If no entry is required, select "No Entry" for the account titles and enter 0 for the amounts. Round answers to 0 decimal places, e.g. 2,125.)

Account Titles and Explanation	Debit	Credit

eTextbook and Media

List of Accounts

Assume that Swifty uses the straight-line method. Show how the truck would be reported in the December 31, 2020, balance sheet. (Round answers to 0 decimal places, e.g. 2,125.)

SWIFTY COMPANY Partial Balance Sheet                                                                       December 31, 2020For the Month Ended December 31, 2020For the Year Ended December 31, 2020
			$
AddLess:
			$

MAT 152 Lab 4   

Show your work, where appropriate. Remember that you do not have to show any work for what you enter into your graphing calculator.

CITY is the city fuel consumption in miles per gallon and HWY is the highway fuel consumption in miles per gallon.

Car			City (x)		Hwy (y)
	Acura RL	18		26
	Audi A6	21		29
	Buick LaCrosse	20		30
	Chrysler 300	17		25
	Infiniti M35	18		25
	Mazda 3	26		32
	Mercury Gr Marq	17		25
	Nissan Altima	23		29
	Pontiac G6	22		32
	Toyota Avalon	22		31

For parts A – C, find each of them. (There is no work required since your graphing calculator gives you these values.)                  Round each number to 3 decimal places.  

1. the linear regression equation:

2.    the correlation coefficient, r:

3. the coefficient of determination, r2:

4. Interpret r by explaining this value (from #2 above) in a COMPLETE sentence.
   

There is a _______________ _______________ linear correlation between city and

Choose strong or weak.    Choose positive or negative.

highway fuel consumption.

5. Interpret r2 by explaining this value (from #3 above) in a COMPLETE sentence by filling in the blanks:

_________ % of the variation in _______________ mileage can be explained by the

                Change r2 to a %.                                  Choose city or highway.

                regression equation.

            _________% of the variation is unexplained.

6. Determine if there is a significant linear relationship between city and highway fuel consumption at α=0.05 by completing the hypothesis test steps below.                                                                                                                                                 (Use LinRegTTest.)   

1. H₀:

H_a:

2. Calculate the test statistic: t = ___________                  Round to 3 decimal places.

3. Calculate the p-value: ____________                              Round to 4 decimal places.

4. Select the correct decision: Reject H₀                 or         Fail to Reject H₀

5. Conclusion: (Explain in terms of if there is a significant linear relationship or not).

Do heavier cars really use more gasoline? Suppose a car is chosen at random. Let x be the weight of the car (in hundreds of pounds), and let y be the miles per gallon (mpg).
x 27 42 31 47 23 40 34 52

y 33 21 24 13 29 17 21 14

Complete parts (a) through (e), given Σx = 296, Σy = 172, Σx2 = 11,652, Σy2 = 4042, Σxy = 5917, and r ≈ −0.911. (a) Draw a scatter diagram displaying the data.

(b) Verify the given sums Σx, Σy, Σx2, Σy2, Σxy, and the value of the sample correlation coefficient r. (Round your value for r to three decimal places.)

Σx =2 Σy =3 Σx2 =4 Σy2 =5 Σxy =6 r =7

(c) Find x, and y. Then find the equation of the least-squares line = a + bx. (Round your answers for x and y to two decimal places. Round your answers for a and b to three decimal places.) x = ___ y = ___ = y____ + ____x

(d) Graph the least-squares line. Be sure to plot the point (x, y) as a point on the line.

(e) Find the value of the coefficient of determination r2. What percentage of the variation in y can be explained by the corresponding variation in x and the least-squares line? What percentage is unexplained? (Round your answer for r2 to three decimal places. Round your answers for the percentages to one decimal place.)

r2 = _______ explained _____ % unexplained ______ %

(f) Suppose a car weighs x = 39 (hundred pounds). What does the least-squares line forecast for y = miles per gallon? (Round your answer to two decimal places.) ________mpg

Green Thumb Gardening is a small gardening service that uses activity-based costing to estimate costs for pricing and other purposes. The proprietor of the company believes that costs are driven primarily by the size of customer lawns, the size of customer garden beds, the distance to travel to customers, and the number of customers. In addition, the costs of maintaining garden beds depends on whether the beds are low maintenance beds (mainly ordinary trees and shrubs) or high maintenance beds (mainly flowers and exotic plants). Accordingly, the company uses the five activity cost pools listed below:

Activity Cost Pool	Activity Measure
Caring for lawn	Square feet of lawn
Caring for garden beds–low maintenance	Square feet of low maintenance beds
Caring for garden beds–high maintenance	Square feet of high maintenance beds
Travel to jobs	Miles
Customer billing and service	Number of customers

The company already has completed its first stage allocations of costs and has summarized its annual costs and activity as follows:

  

Activity Cost Pool	Estimated Overhead Cost		Expected Activity
Caring for lawn	$	77,800	170,000	square feet of lawn
Caring for garden beds–low maintenance	$	30,400	29,000	square feet of low maintenance beds
Caring for garden beds–high maintenance	$	64,630	23,000	square feet of high maintenance beds
Travel to jobs	$	3,600	20,000	miles
Customer billing and service	$	7,500	30	customers

Activity Cost Pool	Activity Rate
Caring for lawn		per square ft of lawn
Caring for garden beds—low maintenance		per square ft of low maintenance beds
Caring for garden beds—high maintenance		per square ft of high maintenance beds
Travel to jobs		per mile
Customer billing and service		per customer

Amy Richardson had been a well-paid sales manager of a major hotel chain for 15 years. Due to a hotel owner's illness, Amy was offered the opportunity to purchase a hotel near a seaside vacation area she had often visited. After obtaining a lawyer and a financial accountant to assist her, Amy did an analysis of the most recent financial statements of the hotel. Since the hotel had consistently shown a profit during the past few years, Amy thought that the price of the hotel was reasonable, so she decided to purchase the hotel. She resigned her position, obtained a loan, and purchased the hotel.

During the first year as a hotel manager, Amy received an offer from a tour operator who proposed to guarantee a considerable number of room reservations, including during the off-season. However, she turned down the offer because the tour operator asked for a 20% price reduction compared to the regular room rate. A few weeks later, she decided to shut down the restaurant, located in the main building of the hotel, in order to save expenses. With regard to general expenses, she was particularly concerned with the high room cleaning and service costs. On the sales side, although the reservations for the cheaper standard rooms were a bit sluggish, the more expensive large-size superior rooms had a very good occupancy rate of over 90%.

The following year, there was a severe economic downturn and also a very bad weather season that reduced the number of guests and also caused a resulting mold situation in the hotel building that required expensive repair work. Amy ran short of cash, became emotionally distraught, and eventually had to sell the hotel at a significant loss.

Question: Using Relevant Costs To Make Short-Term Decisions explain potential management errors that Amy had made and could have helped her to improve decision-making and the financial results of the business.

You are applying for a data job, and your assignment is to analyze the following data set for monthly average temperatures at St Catherines in the programming language R.

(a) Prepare some plots that visualize the data.

(b) Find the appropriate time series model and fit the data. Explain your choice of parameters.

(c) Make predictions for the next 3 years, plot these predictions.

(d) Summarize your findings.

The Data is provided below. Please show the R codes as well. Thank you!

"Month","Average monthly temperatures St Cathrines"

“1980-01", 3.3

“1980-02", 5.5

“1980-03", 0.5

“1980-04", 7.4

“1980-05", 14.4

“1980-06", 16.6

“1980-07", 21.8

“1980-08", 22.8

“1980-09", 16.9

“1980-10", 8.4

“1980-11", 3.4

“1980-12", 4.3

“1981-01", 7.6

“1981-02", 0.6

“1981-03”, 1.6

“1981-04", 8.5

“1981-05", 12.4

“1981-06", 19.2

“1981-07", 22.1

“1981-08", 20.7

“1981-09", 16.0

“1981-10", 7.7

“1981-11", 4.5

“1981-12", 1.3

“1982-01", 7.7

“1982-02", 5.3

“1982-03", 0.3

“1982-04", 5.7

“1982-05", 14.0

“1982-06", 15.9

“1982-07", 21.9

“1982-08", 18.4

“1982-09", 15.9

“1982-10", 11.2

“1982-11", 5.8

“1982-12", 3.0

“1983-01", 2.3

“1983-02", 1.6

“1983-03", 1.9

“1983-04", 6.5

“1983-05", 11.6

“1983-06", 19.6

“1983-07", 23.3

“1983-08”, 21.5

“1983-09", 17.5

“1983-10", 10.8

“1983-11", 4.9

“1983-12", 4.2

“1984-01", 6.1

“1984-02", 0.4

“1984-03", 3.0

“1984-04", 7.5

“1984-05", 11.0

“1984-06", 19.6

“1984-07", 21.0

“1984-08", 22.0

“1984-09", 15.4

“1984-10", 11.3

“1984-11", 4.6

“1984-12", 0.9

“1985-01", 6.0

“1985-02", 4.0

“1985-03", 2.3

“1985-04", 8.7

“1985-05", 14.3

“1985-06", 17.0

“1985-07", 21.1

“1985-08", 20.7

“1985-09", 18.3

“1985-10”, 10.9

“1985-11", 4.9

“1985-12", 3.2

“1986-01", 3.6

“1986-02", 4.8

“1986-03", 1.9

“1986-04", 8.1

“1986-05", 15.0

“1986-06", 17.7

“1986-07", 21.9

“1986-08", 19.7

“1986-09", 16.1

“1986-10", 10.4

“1986-11", 2.9

“1986-12", 0.4

“1987-01”, 3.1

“1987-02", 3.7

“1987-03", 2.7

“1987-04", 9.0

“1987-05", 15.0

“1987-06", 20.2

“1987-07", 23.5

“1987-08", 20.3

“1987-09", 16.8

“1987-10", 8.3

“1987-11", 5.3

“1987-12", 1.1

“1988-01", 3.3

“1988-02", 4.5

“1988-03”, 1.1

“1988-04", 6.7

“1988-05", 14.6

“1988-06", 18.4

“1988-07", 23.7

“1988-08", 22.2

“1988-09", 16.4

“1988-10", 8.4

“1988-11", 6.0

“1988-12", 1.1

“1989-01", 0.7

“1989-02", 4.7

“1989-03", 0.3

“1989-04", 5.6

“1989-05", 13.2

“1989-06", 19.2

“1989-07", 22.2

“1989-08", 20.7

“1989-09", 16.8

“1989-10", 11.1

“1989-11", 3.7

“1989-12", 7.5

“1990-01", 0.7

“1990-02", 1.8

“1990-03", 2.1

“1990-04”, 8.9

“1990-05", 12.1

“1990-06", 19.4

“1990-07", 21.5

“1990-08", 21.0

“1990-09", 16.2

“1990-10", 10.7

“1990-11", 5.8

“1990-12", 0.6

“1991-01", 3.9

“1991-02", 0.6

“1991-03", 2.9

“1991-04", 9.1

“1991-05", 16.8

“1991-06", 20.6

“1991-07", 22.1

“1991-08", 21.8

“1991-09", 16.4

“1991-10", 11.4

“1991-11", 4.2

“1991-12”, 0.1

“1992-01", 2.5

“1992-02", 2.1

“1992-03", 0.1

“1992-04", 6.1

“1992-05", 12.8

“1992-06", 16.9

“1992-07", 18.8

“1992-08", 18.9

“1992-09", 15.9

“1992-10", 8.5

“1992-11", 4.2

“1992-12", 0.3

“1993-01", 1.8

“1993-02", 6.8

“1993-03”, 1.7

“1993-04", 7.4

“1993-05", 12.7

“1993-06", 17.8

“1993-07", 22.4

“1993-08", 21.7

“1993-09", 15.1

“1993-10", 9.0

“1993-11", 3.9

“1993-12", 1.7

“1994-01”, 9.1

“1994-02", 6.2

“1994-03", 0.2

“1994-04", 8.2

“1994-05", 11.6

“1994-06", 19.3

“1994-07", 22.2

“1994-08", 19.6

“1994-09", 16.4

“1994-10", 10.6

“1994-11", 6.8

“1994-12", 1.0

“1995-01", 1.2

“1995-02", 5.7

“1995-03", 3.0

“1995-04", 5.2

“1995-05", 13.6

“1995-06", 20.0

“1995-07", 22.1

“1995-08", 21.9

“1995-09", 15.4

“1995-10”, 12.0

“1995-11", 2.4

“1995-12", 3.4

“1996-01", 5.2

“1996-02", 4.4

“1996-03", 2.0

“1996-04", 6.0

“1996-05", 12.2

“1996-06", 19.4

“1996-07", 20.5

“1996-08”, 21.7

“1996-09", 17.3

“1996-10", 10.7

“1996-11", 2.4

“1996-12", 0.8

“1997-01", 4.1

“1997-02", 0.9

“1997-03", 0.4

“1997-04", 6.2

“1997-06", 20.0

“1997-07", 20.7

“1997-08", 19.6

“1997-09", 16.3

“1997-10", 10.1

“1997-11", 3.3

“1997-12", 0.5

“1998-01", 0.6

“1998-02", 0.7

“1998-03", 3.3

“1998-04", 9.0

“1998-05", 16.9

“1998-06", 19.5

“1998-07", 21.8

“1998-08”, 22.1

“1998-09", 19.0

“1998-10", 11.6

“1998-11", 6.1

“1998-12", 2.5

“1999-01", 4.7

“1999-02", 0.5

“1999-03", 0.7

“1999-04", 8.1

“1999-05”, 15.4

“1999-06", 21.2

“1999-07", 24.6

“1999-08", 20.3

“1999-09", 18.5

“1999-10”, 10.6

“1999-11", 6.8

“1999-12", 0.5

"Trydint" bubble-gum company claims that 3 out of 10 people prefer their gum to "Eklypse". Test their claim at the 99 confidence level. The null and alternative hypothesis in symbols would be: H 0 : p ≤ 0.3 H 1 : p > 0.3 H 0 : μ = 0.3 H 1 : μ ≠ 0.3 H 0 : μ ≥ 0.3 H 1 : μ < 0.3 H 0 : μ ≤ 0.3 H 1 : μ > 0.3 H 0 : p = 0.3 H 1 : p ≠ 0.3 H 0 : p ≥ 0.3 H 1 : p < 0.3 The null hypothesis in words would be: The average of people that prefer Trydint gum is not 0.3. The proportion of all people that prefer Trydint gum is less than 0.3. The proportion of people in a sample that prefers Trydint gum is 0.3. The proportion of people in a sample that prefer Trydint gum is not 0.3 The proportion of all people that prefer Trydint gum is greater than 0.3. The proportion of all people that prefer Trydint gum is 0.3 The average of people that prefer Trydint gum is 0.3. Based on a sample of 280 people, 58 said they prefer "Trydint" gum to "Eklypse". The point estimate is: (to 3 decimals) The 99 % confidence interval is: to (to 3 decimals) Based on this we: Reject the null hypothesis Fail to reject the null hypothesis

Trydint" bubble-gum company claims that 8 out of 10 people prefer their gum to "Eklypse". Test their claim at the 95 confidence level.

The null and alternative hypothesis in symbols would be:

• A)H0:p≤0.8H
  H1:p>0.8
• B)H0:p≥0.8
  H1:p<0.8
• C)H0:p=0.8
  H1:p≠0.8
• D)H0:μ=0.8
  H1:μ≠0.8
• E)H0:μ≤0.8
  H1:μ>0.8
• F)H0:μ≥0.8
  H1:μ<0.8

The null hypothesis in words would be:

A)The proportion of all people that prefer Trydint gum is 0.8

B)The average of people that prefer Trydint gum is not 0.8.

C)The proportion of all people that prefer Trydint gum is less than 0.8.

D)The average of people that prefer Trydint gum is 0.8.

E)The proportion of people in a sample that prefer Trydint gum is not 0.8

F)The proportion of all people that prefer Trydint gum is greater than 0.8.

G)The proportion of people in a sample that prefers Trydint gum is 0.8.

Based on a sample of 340 people, 252 said they prefer "Trydint" gum to "Eklypse".
The point estimate is: (to 3 decimals)
The 95 % confidence interval is: ____to_______ (to 3 decimals)

Based on this we:

A)Reject the null hypothesis

B)Fail to reject the null hypothesis

Using Loops for the Hotel Occupancy calculator.

You will write a program that calculates the occupancy of a hotel. Rules: 1# The hotel must have more than 2 floors and less than or equal 5 floors. 2# Each floor in the hotel can have a different number of rooms on the floor. 3# You must set the number of occupied rooms. Again, there must less rooms occupied than the number of rooms. 4# Using the total number of rooms and the total number of occupied rooms calculate the occupancy rate of the hotel. 5# Every input into this program must be checked to see if the numbers are valid.

JAVA