Brett and Lisa file taxes under the married filing jointly status. Lisa is a sales manager for an auto parts company and Brett takes care of their 3 children. In 2018, Lisa receives a promotion associated with a move to a new division located over 500 miles from their existing home. The cost to move their household items is $8,700. Lisa's employer reimburses her for $3,000 of those costs and also pays $2,100 for airfare for the entire family to fly to the new destination. Lisa's moving expenses deduction for 2018 is:
a.$5,700
b.$3,600
c.$0
d.$8,700
e.None of these choices are correct.
Ellen supports her family as a self-employed attorney. She reports $90,000 of income on her Schedule C and pays $8,000 for health insurance for her family, $2,500 for dental insurance, $4,000 for health insurance for her 23-year-old daughter who is no longer a dependent, and $3,000 for disability insurance for herself. What is Ellen's self-employed health insurance deduction?
a.$10,500
b.$12,000
c.$13,500
d.$14,500
e.$8,000
Over the years, Monica contributed $15,000 to a Roth IRA opened 10 years ago. The IRA has a current value of $37,500. She is 54 years old and takes a distribution of $25,000. How much of the distribution will be taxable to Monica?
a.$10,000
b.$0
c.$37,500
d.$15,000
e.$25,000
Jody is a physician (not covered by a retirement plan) with a salary of $40,000 from the hospital where she is employed. She supports her husband, Andre, who sells art work and has no earned income. Both are in their twenties. What is the maximum total amount that Jody and Andre may contribute to their IRAs and deduct for the 2018 tax year?
a.$5,000
b.$5,500
c.$11,000
d.$10,000
e.None of these choices are correct.
In: Accounting
Waterbury Insurance Company wants to study the relationship between the amount of fire damage and the distance between the burning house and the nearest fire station. This information will be used in setting rates for insurance coverage. For a sample of 30 claims for the last year, the director of the actuarial department determined the distance from the fire station (x) and the amount of fire damage, in thousands of dollars (y). The MegaStat output is reported below.
| ANOVA table | ||||||
| Source | SS | df | MS | F | ||
| Regression | 1,865.5782 | 1 | 1,865.5782 | 39.56 | ||
| Residual | 1,320.4934 | 28 | 47.1605 | |||
| Total | 3,186.0716 | 29 | ||||
| Regression output | |||
| Variables | Coefficients | Std. Error | t(df=28) |
| Intercept | 13.7523 | 3.0957 | 3.672 |
| Distance–X | 6.3449 | 7.279 | 6.3 |
a-1. Write out the regression equation. (Round your answers to 3 decimal places.)
How much damage would you estimate for a fire 7 miles from the nearest fire station? (Round your answer to the nearest dollar amount.)
c-1. Determine the coefficient of determination. (Round your answer to 3 decimal places.)
c-2. Fill in the blank below. (Round your answer to one decimal place.)
d-1. Determine the correlation coefficient. (Round your answer to 3 decimal places.)
d-3. How did you determine the sign of the correlation coefficient?
e-1. State the decision rule for 0.01 significance level: H0 : ρ = 0; H1 : ρ ≠ 0. (Negative value should be indicated by a minus sign. Round your answers to 3 decimal places.)
e-2. Compute the value of the test statistic for the hypothesis of β1. (Round your answer to 2 decimal places.)
e-3. Is there any significant relationship between the distance from the fire station and the amount of damage? Use the 0.01 significance level.
In: Statistics and Probability
Many drivers of cars that can run on regular gas actually buy premium in the belief that they will get better gas mileage. To determine if there is evidence to support this claim, 10 cars were used in a company fleet in which all of the cars ran on regular gas. Each car was filled first with either regular or premium gasoline, decided by a coin toss, and the mileage was recorded for a tank full. Then, the mileage was recorded again for the same cars for a tank full of the other kind of gasoline. The results are listed below in miles per gallon: Car # 1 2 3 4 5 6 7 8 9 10 Regular 16 20 21 22 23 22 27 25 27 28 Premium 19 20 24 19 25 25 26 26 28 28
The test of the variances at .10 reveals that we reject the null hypothesis. Yes or no
There is a statistically significant difference between the mean of regular gas and the mean of premium gas as evidenced by the respective sample means. Yes or no
The standard error of the mean difference is 1.969 Yes or no'
For the test of the means at .05, we fail to reject the null hypothesis. Yes or no
For the test of the means at .05, the decision is reject the null hypothesis. yes or no
For the test of the means at .05, the final conclusion within the context of the scenario is that there is sufficient evidence to indicate that regular and premium get about the same gas mileage. Yes or no
For the 2-tail test of the confidence interval, the confidence interval contains 0 . Yes or no
For the 2-tail test of the confidence interval, the decision is to fail to reject the null b/c 0 is not in the interval. Yes or no
For the 2-tail test of the confidence interval, the evidence is because 0 is in the interval. Yes or no
Because we failed to reject the null hypothesis, this indicates that there is no difference in gas mileage between premium and regular. Yes or no
In: Statistics and Probability
Stacking pennies to the moon
Be sure to state your assumptions and define your estimations. Include justification for these.
Use these facts (do not look up additional facts to help):
What you should be paying attention to in order to earn a good grade:
You might want to have someone else read it after you are done to make sure that your process is clear.
In: Physics
When Bob moved to a new city after he changed jobs in
2017, he drove 100 miles and paid a professional mover $1,500. His
new employer reimbursed him $600 for these expenses. Assuming his
move related closely to the start of his new job and he met the
time and distance tests, what amount may he claim as an
above-the-line adjustment for moving expenses?
Carolina passed away in 2017. Her granddaughter, Olivia,
is the court-appointed personal representative for Carolina's
estate. While sorting through her grandmother's documents, Olivia
determines that, although Carolina timely filed her 2014 return,
she neglected to claim all the deductions for which she was
eligible. In January 2018, Olivia seeks your tax expertise on this
matter. What can she do?
Vanessa filed her 2015 return on April 18, 2016. On July 14, 2016, she received an IRS notice stating she owed an additional $2,200 because of an error on her 2015 return. On August 1, 2016, she paid the balance due without disputing the notice. Later, she realized she qualified for a credit that would have reduced this liability. Ordinarily, the last day Vanessa could file an amended 2015 return to claim this credit would be _________.
Darrell did not have all the information he needed to
file his 2016 return by the original due date, so he requested a
tax-filing extension on April 18, 2017. He then filed the return
and paid his balance due on September 28, 2017. Darrell later
discovers he neglected to claim a credit for which he was eligible.
Under ordinary circumstances, what is the last day he could amend
this return?
In: Accounting
To become an effective leader, learning to use influence tactics comfortably is inevitable. If you use influence tactics naturally, without giving them much thought, there is still more to learn. For example, even a great leader such as Elton Musk might be even more effective with employees if he were more conciliatory toward those people he perceived to be of average intelligence. Being conciliatory fits the influence tactics of being charming and consulting with others. In order for many influence tactics to work well, such as being a hands-on leader or joking and kidding, the regular physical presence of a leader is valuable. Some CEOs today attempt to conduct much of their work digitally, and perhaps even live in a city 3,000 miles away from company headquarters. The lowly visible leader not only loses influence but also might be dismissed. A case in point is Federica Marchionni was forced out as CEO of Land’s End Inc. She had attempted to bring about broad changes at the catalog retailer that annoyed employees and turned away shoppers. The former Ferrari executive was never able to influence employees to accept her vision of a more fashionable Land’s End. A point of contention was that Marchionni spent about one week a month at the company’s Wisconsin headquarters, preferring instead to work out of an office in the garment district of New York.
Discussion Questions and Activities
1.Which of the influence tactics described in this chapter do you think are the most important for a person his or her first leadership assignment? Explain your reasoning.
2.Assume that as their leader, you wanted to influence minimum wage workers in an order-fulfillment center to work faster. Which one or two influence tactics are likely to be effective?
3.How might a business owner use the technique of tapping social norms to influence his or her employees to lead a healthier lifestyle?
In: Economics
Consider one of the subset regression models for each data set obtained in Problem Set 4 and answer the following questions. (i) Draw the scatter plot matrix, residual vs. predictor variable plots and added variable plots. Comment on the regression model based on these plots. (ii) Draw the normal-probability plot and comment. (iii) Draw the correlogram and comment. (iv) Detect leverage points from the data. (v) Compute Cook’s distance statistics and detect all outlier points from the data. (vi) Compute DFFITS statistics and detect all outlier points from the data. (vii) Compute DFBETAS statistics and comment.
Two data sets are given for the following variables. 30 observations on 11 variables – Miles/(US) gallon, Number of cylinders, Displacement (cu.in.), Gross horsepower, Rear axle ratio, Weight (1000 lbs), 1/4 mile time, Engine (0 = Vshaped, 1 = straight), Transmission (0 = automatic, 1 = manual), Number of forward gears, Number of carburettors. This data set is available in R as “mtcars” under the package datasets. (2) 54 observations on the 10 surgical aspects. This data set is available in R as “SurgicalUnit” under the package ALSM. Answer the following questions for each data sets. (i) Find out appropriate models among all possible subset regression models based on the criteria of adjusted R-square, Mallow’s statistic, AIC and BIC. (ii) Use the forward selection approach to find the appropriate subset regression model. (iii) Use the backward elimination approach to find the appropriate subset regression model. (iv) Use the stepwise selection approach to find the appropriate subset regression model. (v) Comment on the performance of the subset regression models obtained in (i)-(iv).
In: Statistics and Probability
Consider one of the subset regression models for each data set obtained in Problem Set 4 and answer the following questions. (i) Draw the scatter plot matrix, residual vs. predictor variable plots and added variable plots. Comment on the regression model based on these plots. (ii) Draw the normal-probability plot and comment. (iii) Draw the correlogram and comment. (iv) Detect leverage points from the data. (v) Compute Cook’s distance statistics and detect all outlier points from the data. (vi) Compute DFFITS statistics and detect all outlier points from the data. (vii) Compute DFBETAS statistics and comment.
Two data sets are given for the following variables. 30 observations on 11 variables – Miles/(US) gallon, Number of cylinders, Displacement (cu.in.), Gross horsepower, Rear axle ratio, Weight (1000 lbs), 1/4 mile time, Engine (0 = Vshaped, 1 = straight), Transmission (0 = automatic, 1 = manual), Number of forward gears, Number of carburettors. This data set is available in R as “mtcars” under the package datasets. (2) 54 observations on the 10 surgical aspects. This data set is available in R as “SurgicalUnit” under the package ALSM. Answer the following questions for each data sets. (i) Find out appropriate models among all possible subset regression models based on the criteria of adjusted R-square, Mallow’s statistic, AIC and BIC. (ii) Use the forward selection approach to find the appropriate subset regression model. (iii) Use the backward elimination approach to find the appropriate subset regression model. (iv) Use the stepwise selection approach to find the appropriate subset regression model. (v) Comment on the performance of the subset regression models obtained in (i)-(iv).
In: Statistics and Probability
ack, a geologist, opened a business organized as a C corporation called Geo-Jack (GJ) in January of this year. Jack is the sole shareholder. Assume GJ reports on a calendar year and uses the accrual method of accounting. For each item below, indicate its effect on Jack’s taxable income and you must clearly indicate whether it is positive or negative. (0.5 points each, 4 points total)
In January, GJ rented a small business office about 12 miles from Jack’s home. GJ paid $14,000, which represented a damage deposit of $6,000 plus rent for two years ($4,000 annually).
______________
GJ earned and collected $300,000 performing geological-related services and selling its specialized digging tool.
______________
GJ purchased some new equipment in February for $53,700. It claimed depreciation on these assets during the year in the amount of $4,510.
______________
GJ paid Jack’s father $12,000 for services that would have cost no more than $7,000 if Jack had hired any other local business to perform the services. While Jack’s dad was competent, he does not command such a premium from his other clients.
______________
In an attempt to get his name and new business recognized, GJ paid $9,000 for a one-page ad in the Geologic Survey. It also paid $11,000 in radio ads to be run through the end of December.
Section (circle one): 12:30 / 2:00 / 3:30
______________
In November, GJ’s office was broken into and equipment valued at $6,000 was stolen. The tax basis of the equipment was $6,500. GJ received $4,000 of insurance proceeds from the theft.
______________
GJ incurred a $5,000 fine from the state government for digging in an unauthorized digging zone.
______________
GJ reimbursed employee-salespersons $4,200 for meals involving substantial business discussion.
______________
In: Accounting
One of my recent papers examine important and timely research questions using a field experiment approach in eBay auctions: (i) Can merchandise return policy (MRP; liberalness in the MRP) increase consumers’ willingness to pay? and (ii) is the marginal impact of MRP diminishing? In this study we created three brand new eBay seller profiles, all with zip-codes located within five miles of each other in a college town in the U.S. The eBay stores received exactly the same product description, pictures, outbound shipping policies, etc. The only difference among the three sellers was the extent of liberalness in the MRP and we chose to operationalize MRP liberalness in terms of the time window during which the customer is allowed to return the purchased product. The most conservative MRP (Storefront 1 and 1a) involved a 15-day return window. According to trade publications, this return condition is more conservative than retail-industry averages. Storefront2 and 2a received a 30-day return window, which corresponds closely with retail-industry averages. Finally, Storefront3 and 3a received a 60-day return window, which is more liberal than many retailers offer at this point. The other elements of the return remained constant across the three storefronts. Therefore, in terms of overall return-policy liberalness, it could be argued that Storefront1/1a < Storefront 2/2a < Storefront 3/3a . It is important to note that it is very common in my data that we observe a customer’s bidding behavior in several auctions. [Question] During the revision stage of the journal publication process, one of the reviewer’s comment was that the I may use a fixed effects model to control for unobserved individual fixed effects. Do you agree or disagree with the above statement? Please explain with details.
In: Statistics and Probability