Listed below are amounts of court income and salaries paid to the town justices. All amounts are in thousands of dollars. Construct a​ scatterplot, find the value of the linear correlation coefficient​ r, and find the​ P-value using

alphaαequals=0.05.

Is there sufficient evidence to conclude that there is a linear correlation between court incomes and justice​ salaries? Based on the​ results, does it appear that justices might profit by levying larger​ fines?

Court_Income   Justice_Salary
64.0   31
404.0   45
1566.0   93
1131.0   55
270.0   46
253.0   60
112.0   26
150.0   27
30.0   19

What are the null and alternative​ hypotheses?

A.

Upper H 0H0​:

rhoρnot equals≠0

Upper H 1H1​:

rhoρequals=0

B.

Upper H 0H0​:

rhoρequals=0

Upper H 1H1​:

rhoρgreater than>0

C.

Upper H 0H0​:

rhoρequals=0

Upper H 1H1​:

rhoρnot equals≠0

D.

Upper H 0H0​:

rhoρequals=0

Upper H 1H1​:

rhoρless than<0

Construct a scatterplot. Choose the correct graph below.

A.

08001600050100Court IncomeJustice Salary

A scatterplot has a horizontal scale labeled “Court Income” from 0 to 1600 in intervals of 200 and a vertical scale labeled “Justice Salary” from 0 to 100 in intervals of 10. Nine points are plotted with approximate coordinates as follows: (260, 84); (420, 24); (640, 56); (760, 86); (880, 48); (900, 34); (1040, 86); (1260, 46); (1480, 18).

B.

08001600050100Court IncomeJustice Salary

A scatterplot has a horizontal scale labeled “Court Income” from 0 to 1600 in intervals of 200 and a vertical scale labeled “Justice Salary” from 0 to 100 in intervals of 10. Nine points are plotted with approximate coordinates as follows: (40, 20); (60, 32); (120, 26); (160, 28); (260, 60); (280, 46); (400, 46); (1140, 56); (1560, 94).

C.

08001600050100Court IncomeJustice Salary

A scatterplot has a horizontal scale labeled “Court Income” from 0 to 1600 in intervals of 200 and a vertical scale labeled “Justice Salary” from 0 to 100 in intervals of 10. Nine points are plotted with approximate coordinates as follows: (140, 14); (140, 36); (340, 42); (660, 54); (740, 66); (900, 74); (1280, 90); (1320, 14); (1420, 74).

D.

08001600050100Court IncomeJustice Salary

A scatterplot has a horizontal scale labeled “Court Income” from 0 to 1600 in intervals of 200 and a vertical scale labeled “Justice Salary” from 0 to 100 in intervals of 10. Nine points are plotted with approximate coordinates as follows: (220, 84); (220, 80); (360, 80); (400, 70); (580, 84); (740, 58); (1080, 62); (1120, 30); (1420, 44).

The linear correlation coefficient r is

nothing.

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

The test statistic t is

nothing.

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

The​ P-value is

nothing.

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

Because the​ P-value is

▼

less

greater

than the significance level

0.050.05​,

there

▼

is not

is

sufficient evidence to support the claim that there is a linear correlation between court incomes and justice salaries for a significance level of

alphaαequals=0.050.05.

Based on the​ results, does it appear that justices might profit by levying larger​ fines?

A.

It does not appear that justices might profit by levying larger fines.

B.

It does appear that justices might profit by levying larger fines.

C.

It appears that justices profit the same despite the amount of the fines.

D.

It does appear that justices might profit by issuing smaller fines.

Listed below are amounts of court income and salaries paid to the town justices. All amounts are in thousands of dollars. Construct a​ scatterplot, find the value of the linear correlation coefficient​ r, and find the​ P-value using alphaequals0.05. Is there sufficient evidence to conclude that there is a linear correlation between court incomes and justice​ salaries? Based on the​ results, does it appear that justices might profit by levying larger​ fines?

Court Income 64.0 402.0 1567.0 1131.0 273.0 251.0 112.0 150.0 32.0 Justice Salary 31 45 92 58 48 60 26 27 19

What are the null and alternative​ hypotheses?

A.

Upper H 0H0​:

rhoρequals=0

Upper H 1H1​:

rhoρless than<0

B.

Upper H 0H0​:

rhoρnot equals≠0

Upper H 1H1​:

rhoρequals=0

C.

Upper H 0H0​:

rhoρequals=0

Upper H 1H1​:

rhoρnot equals≠0

D.

Upper H 0H0​:

rhoρequals=0

Upper H 1H1​:

rhoρgreater than>0

Construct a scatterplot. Choose the correct graph below.

A.

08001600050100Court IncomeJustice Salary

A scatterplot has a horizontal scale labeled “Court Income” from 0 to 1600 in intervals of 200 and a vertical scale labeled “Justice Salary” from 0 to 100 in intervals of 10. Nine points are plotted with approximate coordinates as follows: (260, 84); (420, 24); (640, 56); (760, 86); (880, 48); (900, 34); (1040, 86); (1260, 46); (1480, 18).

B.

08001600050100Court IncomeJustice Salary

A scatterplot has a horizontal scale labeled “Court Income” from 0 to 1600 in intervals of 200 and a vertical scale labeled “Justice Salary” from 0 to 100 in intervals of 10. Nine points are plotted with approximate coordinates as follows: (220, 84); (220, 80); (360, 80); (400, 70); (580, 84); (740, 58); (1080, 62); (1120, 30); (1420, 44).

C.

08001600050100Court IncomeJustice Salary

A scatterplot has a horizontal scale labeled “Court Income” from 0 to 1600 in intervals of 200 and a vertical scale labeled “Justice Salary” from 0 to 100 in intervals of 10. Nine points are plotted with approximate coordinates as follows: (40, 20); (60, 32); (120, 26); (160, 28); (260, 60); (280, 48); (400, 46); (1140, 58); (1560, 92).

D.

08001600050100Court IncomeJustice Salary

A scatterplot has a horizontal scale labeled “Court Income” from 0 to 1600 in intervals of 200 and a vertical scale labeled “Justice Salary” from 0 to 100 in intervals of 10. Nine points are plotted with approximate coordinates as follows: (140, 14); (140, 36); (340, 42); (660, 54); (740, 66); (900, 74); (1280, 90); (1320, 14); (1420, 74).The linear correlation coefficient r is

nothing.

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

The test statistic t is

nothing.

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

The​ P-value is

nothing.

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

Because the​ P-value is

▼

less

greater

than the significance level

0.050.05​,

there

▼

is not

is

sufficient evidence to support the claim that there is a linear correlation between court incomes and justice salaries for a significance level of

alphaαequals=0.050.05.

Based on the​ results, does it appear that justices might profit by levying larger​ fines?

A.

It appears that justices profit the same despite the amount of the fines.

B.

It does appear that justices might profit by levying larger fines.

C.

It does appear that justices might profit by issuing smaller fines.

D.

It does not appear that justices might profit by levying larger fines.

Click to select your answer(s).

As part of a study designed to compare hybrid and similarly equipped conventional vehicles, a group tested a variety of classes of hybrid and all-gas model cars and sport utility vehicles (SUVs). Suppose the following data show the miles-per-gallon rating obtained for two hybrid small cars, two hybrid midsize cars, two hybrid small SUVs, and two hybrid midsize SUVs; also shown are the miles per gallon obtained for eight similarly equipped conventional models.

At the α = 0.05 level of significance, test for significant effects due to class, type, and interaction.

Find the value of the test statistic for class. (Round your answer to two decimal places.)

Find the p-value for class. (Round your answer to three decimal places.)

p-value =

State your conclusion about class.

Because the p-value ≤ α = 0.05, class is not significant.Because the p-value > α = 0.05, class is significant.    Because the p-value > α = 0.05, class is not significant.Because the p-value ≤ α = 0.05, class is significant.

Find the value of the test statistic for type. (Round your answer to two decimal places.)

Find the p-value for type. (Round your answer to three decimal places.)

p-value =

State your conclusion about type.

Because the p-value > α = 0.05, type is significant.Because the p-value ≤ α = 0.05, type is significant.    Because the p-value > α = 0.05, type is not significant.Because the p-value ≤ α = 0.05, type is not significant.

Find the value of the test statistic for interaction between class and type. (Round your answer to two decimal places.)

Find the p-value for interaction between class and type. (Round your answer to three decimal places.)

p-value =

State your conclusion about interaction between class and type.

Because the p-value ≤ α = 0.05, interaction between class and type is not significant.Because the p-value ≤ α = 0.05, interaction between class and type is significant.    Because the p-value > α = 0.05, interaction between class and type is significant.Because the p-value > α = 0.05, interaction between class and type is not significant.

You may need to use the appropriate technology to answer this question.

Consider the following data on price ($) and the overall score for six stereo headphones tested by a certain magazine. The overall score is based on sound quality and effectiveness of ambient noise reduction. Scores range from 0 (lowest) to 100 (highest).

(a)

The estimated regression equation for this data is

ŷ = 25.933 + 0.301x,

where x = price ($) and y = overall score. Does the t test indicate a significant relationship between price and the overall score? Use α = 0.05.

Find the value of the test statistic. (Round your answer to three decimal places.)

Find the p-value. (Round your answer to four decimal places.)

p-value =

(b)

Test for a significant relationship using the F test. Use α = 0.05.

Find the value of the test statistic. (Round your answer to two decimal places.)

Find the p-value. (Round your answer to three decimal places.)

p-value =  

(c)

Show the ANOVA table for these data. (Round your p-value to three decimal places and all other values to two decimal places.)

Calculate a 90​%

confidence interval for the difference between the two population proportions.

Sample1 n1=200 x1=40

sample 2 n2=150 x2=27

___≤​(p1−p2​≤______

(b) Find the value of the chi-square statistic for the sample. (Round the expected frequencies to at least three decimal places. Round the test statistic to three decimal places.)

PART A (MAX 500 words in total)

Effective 2019, the new accounting standard on leasing, AASB16 Leases, will replace the existing leases standard, AASB117. It will remove the classification of leases that has been used for decades and which divides leases into operating and financial leases from the perspective of lessees. The new standard requires leases that were formerly known as operating leases (and were kept off balance sheet) to be recognised for balance sheet proposes (both an asset and a liability will be recognised).

Required:

Evaluate how total assets, total liability and equity would be affected by the new accounting standard on leasing from the perspective of lessees. (5 marks)

The changed standard means that leases with a short-term (e.g., several months) will appear on a balance sheet of lessees, as will leases with a long-term (e.g., multiple years). Discuss whether this new approach is consistent or inconsistent with the definitions of assets and liabilities included within the IASB Conceptual Framework. (5 marks)

PART B (MAX 500 words in total)

Microsoft historically followed the practice of recognizing 25% of revenue from its Windows software over three or four years as it promises future upgrades and add-ons. With the launch of Vista in 2008, it changed the policy to record most of the revenue in the period in which the software was sold. In the third quarter for fiscal year 2008, Microsoft reported an increase in earnings of 65%. The increase came from sales of the new Vista program and also from the acceleration in revenue recognition.

Required:

Critically evaluate the revenue recognition policy adopted by Microsoft in accordance with AASB15 Revenue from Contracts with Customers. (5 marks)

Explain the decision of management to change the revenue recognition policy in terms of the debt hypothesis of Positive Accounting Theory. (5 marks)

Data from 2010 & 2011, in millions (source: Billboard Magazine):

Company            Annual Revenue Market Valuation

Spotify                145 3,000

Warner Music     2,888                   3,300

Live Nation         5,600                   1,700

Pandora 241 1,300

EMI                    1,800                   1,900

3a) Find the correlation between annual revenue and market valuation. Is it statistically significant?

3b) Why is the correlation between revenue and market valuation so low?.

Cane Company manufactures two products called Alpha and Beta that sell for $180 and $145, respectively. Each product uses only one type of raw material that costs $6 per pound. The company has the capacity to annually produce 118,000 units of each product. Its unit costs for each product at this level of activity are given below:

The company considers its traceable fixed manufacturing overhead to be avoidable, whereas its common fixed expenses are deemed unavoidable and have been allocated to products based on sales dollars.

12. What contribution margin per pound of raw material is earned by Alpha and Beta? (Round your answers to 2 decimal places.)

13. Assume that Cane’s customers would buy a maximum of 92,000 units of Alpha and 72,000 units of Beta. Also assume that the company’s raw material available for production is limited to 300,000 pounds. How many units of each product should Cane produce to maximize its profits?

15. Assume that Cane’s customers would buy a maximum of 92,000 units of Alpha and 72,000 units of Beta. Also assume that the company’s raw material available for production is limited to 300,000 pounds. Up to how much should it be willing to pay per pound for additional raw materials? (Round your answer to 2 decimal places.)

Cicchetti Corporation uses customers served as its measure of activity. The following report compares the planning budget to the actual operating results for the month of December:

Required:

Prepare the company's flexible budget performance report for December. Select each variance as favorable (F), unfavorable (U) or "None".