Analyze if the statements that are presented below are True or False. You MUST justify your answer to get credit. Answers without justification (even if they are correct) will be given zero marks.
(a) In any Pareto-optimal allocation of a two-good economy, each consumer has to consume a positive amount of both goods.
(b) A monopolist never produces on the elastic segment of its average revenue curve.
(c) If a firm’s production exhibits increasing returns to scale, then the firm’s marginal costs are decreasing and below its average costs.
(d) Maroon Theater practices third-degree price discrimination and sells tickets to three groups of customers: students, regular customers and senior citizens. The inverse demand of the three groups is linear. Furthermore, the students’ and senior citizens’ elasticities of demand for tickets are −4 and −3, respectively. Because the price charged to regular customers is greater than the price charged to senior citizens, we know with certainty that the ticket price for students will be lower than the ticket price for regular customers.
In: Economics
A statistical program is recommended. You may need to use the appropriate appendix table or technology to answer this question.
The owner of a theater would like to predict weekly gross revenue as a function of advertising expenditures. Historical data for a sample of eight weeks follow.
| Weekly Gross Revenue ($1,000s) |
Television Advertising ($1,000s) |
Newspaper Advertising ($1,000s) |
|---|---|---|
| 96 | 5.0 | 1.5 |
| 90 | 2.0 | 2.0 |
| 95 | 4.0 | 1.5 |
| 92 | 2.5 | 2.5 |
| 95 | 3.0 | 3.3 |
| 94 | 3.5 | 2.3 |
| 94 | 2.5 | 4.2 |
| 94 | 3.0 | 2.5 |
(a)
Find an estimated regression equation relating weekly gross revenue (in thousands of dollars) to television and newspaper advertising (in thousands of dollars). (Let x1 represent television advertising, x2 represent newspaper advertising, and y represent weekly gross revenue. Round your numerical values to two decimal places.)
ŷ =
Plot the standardized residuals against ŷ.
does the residual plot support the assumptions about ε? Explain
In: Statistics and Probability
Suppose that the sitting back-to-knee length for a group of adults has a normal distribution with a mean of μ=24.0 in. and a standard deviation of σ=1.1 in. These data are often used in the design of different seats, including aircraft seats, train seats, theater seats, and classroom seats. Instead of using 0.05 for identifying significant values, use the criteria that a value x is significantly high if P(x or greater) ≤0.01 and a value is significantly low if P(x or less) ≤0.01. Find the back-to-knee lengths separating significant values from those that are not significant. Using these criteria, is a back-to-knee length of 26.3 in. significantly high?
***Find the back-to-knee lengths separating significant values from those that are not significant.
Back-to-knee lengths greater than ____ in. and less than _____ nothing in. are not significant, and values outside that range are considered significant.
(Round to one decimal place as needed.)
***A back-to-knee length of 25.3 in. ______ [is or is not] significantly high because it is _______ [Inside or outside] the range of values that are not considered significant.
In: Statistics and Probability
Majer Corporation makes a product with the following standard costs:
| Standard Quantity or Hours | Standard Price or Rate | Standard Cost Per Unit | |
| Direct materials | 6.5 ounces | $4.00 per ounce | $26.00 |
| Direct labor | 0.5 hours | $16.00 per hour | $8.00 |
| Variable overhead | 0.5 hours | $4.00 per hour | $2.00 |
The company reported the following results concerning this product in February.
| Originally budgeted output | 5,500 units |
|---|---|
| Actual output | 8,300 units |
| Raw materials used in production | 30,600 ounces |
| Actual direct labor-hours | 1,960 hours |
| Purchases of raw materials | 33,000 ounces |
| Actual price of raw materials | $72.90 per ounce |
| Actual direct labor rate | $82.40 per hour |
| Actual variable overhead rate | $3.20 per hour |
The company applies variable overhead on the basis of direct labor-hours. The direct materials purchases variance is computed when the materials are purchased.
The variable overhead rate variance for February is:
---
Majer Corporation makes a product with the following standard costs:
| Standard Quantity or Hours | Standard Price or Rate | Standard Cost Per Unit | ||
| Direct materials | 6.5 ounces | $3.00 per ounce | $19.50 | |
| Direct labor | 0.7 hours | $12.00 per hour | $8.40 | |
| Variable overhead | 0.7 hours | $3.00 per hour | $2.10 |
The company reported the following results concerning this product in February.
| Originally budgeted output | 5,100 units |
|---|---|
| Actual output | 5,200 units |
| Raw materials used in production | 30,200 ounces |
| Actual direct labor-hours | 1,920 hours |
| Purchases of raw materials | 32,600 ounces |
| Actual price of raw materials | $32.90 per ounce |
| Actual direct labor rate | $42.40 per hour |
| Actual variable overhead rate | $4.20 per hour |
The company applies variable overhead on the basis of direct labor-hours. The direct materials purchases variance is computed when the materials are purchased.
The variable overhead efficiency variance for February is:
---
Majer Corporation makes a product with the following standard costs:
| Standard Quantity or Hours | Standard Price or Rate | Standard Cost Per Unit | ||
| Direct materials | 3.0 ounces | $12.50 per ounce | $37.50 | |
| Direct labor | 0.7 hours | $18.50 per hour | $12.95 | |
| Variable overhead | 0.7 hours | $11.00 per hour | $7.70 |
The company reported the following results concerning this product in February.
| Originally budgeted output | 11,600 units |
|---|---|
| Actual output | 11,400 units |
| Raw materials used in production | 33,640 ounces |
| Actual direct labor-hours | 8,180 hours |
| Purchases of raw materials | 35,240 ounces |
| Actual price of raw materials | $12.25 per ounce |
| Actual direct labor rate | $16.95 per hour |
| Actual variable overhead rate | $9.20 per hour |
The company applies variable overhead on the basis of direct labor-hours. The direct materials purchases variance is computed when the materials are purchased.
The materials price variance for February is:
In: Accounting
J. Morgan of SparkPlug Inc. has been approached to take over a production facility from B.R. Machine Company. The acquisition will cost $1,960,000, and the after-tax net cash inflow will be $330,000 per year for 12 years.
SparkPlug currently uses 10% for its after-tax cost of capital. Tom Morgan, production manager, is very much in favor of the investment. He argues that the total after-tax net cash inflow is more than the cost of the investment, even if the demand for the product is somewhat uncertain. “The project will pay for itself even if the demand is only half the projected level.” Cindy Morgan (corporate controller) believes that the cost of capital should be 13% because of the declining demand for SparkPlug products.
Required:
1. What is the estimated NPV of the project if the after-tax cost of capital (discount rate) is 10%? Use the built-in NPV function in Excel. (Negative amounts should be indicated by a minus sign. Round your answer to the nearest whole dollar amount.)
2. What is the estimated NPV of the project if the after-tax cost of capital (discount rate) is 13%? Use the built-in NPV function in Excel. (Negative amounts should be indicated by a minus sign. Round your answer to the nearest whole dollar amount.)
3. Use the built-in function in Excel to estimate the project’s IRR. (Round your answer to 1 decimal places.)
4. Do a sensitivity analysis by using GOAL SEEK to determine, given estimated cash inflows, the original investment outlay that would result in an IRR of 13%. (Round your answer to nearest whole dollar amount.)
|
In: Finance
| 2016 | 1.4 | 1.0 | 0.9 | 1.1 | 1.0 | 1.0 | 0.8 | 1.1 | 1.5 | 1.6 | 1.7 | 2.1 |
1.3 |
|---|
| 2017 | 2.5 | 2.7 | 2.4 | 2.2 | 1.9 | 1.6 | 1.7 | 1.9 | 2.2 | 2.0 | 2.2 | 2.1 |
2.1 |
|---|
| 2018 | 2.1 | 2.2 | 2.4 | 2.5 | 2.8 | 2.9 | 2.9 | 2.7 | 2.3 | 2.5 | 2.2 | 1.9 |
2.4 |
|---|
| 2019 | 1.6 | 1.5 | 1.9 | 2.0 |
1.8 |
|---|
find the inflation data for the last 3 years:
1. What are your thoughts about the current state of the economy in terms of the historical inflation data for the last 3 years? Discuss either the effects or the types of inflation.
2. Is demand-pull inflation or cost-push inflation or both at play? Explain with examples.
3. Will the future (for instance, 3 years from now) lead to higher
inflation rates or lower? Why or why not?
4. Will the future (for instance, 3 years from now) be more
promising or otherwise for the existing unemployed? Why or why
not?
In: Economics
8/50
AllUnanswered
QUESTION 1
·
1 POINT
A fitness center claims that the mean amount of time that a person spends at the gym per visit is 33 minutes. Identify the null hypothesis, H0, and the alternative hypothesis, Ha, in terms of the parameter μ.
Select the correct answer below:
H0: μ≠33; Ha: μ=33
H0: μ=33; Ha: μ≠33
H0: μ≥33; Ha: μ<33
H0: μ≤33; Ha: μ>33
FEEDBACK
Content attribution- Opens a dialog
QUESTION 2
·
1 POINT
The answer choices below represent different hypothesis tests. Which of the choices are right-tailed tests? Select all correct answers.
Select all that apply:
H0:X≥17.1, Ha:X<17.1
H0:X=14.4, Ha:X≠14.4
H0:X≤3.8, Ha:X>3.8
H0:X≤7.4, Ha:X>7.4
H0:X=3.3, Ha:X≠3.3
FEEDBACK
Content attribution- Opens a dialog
QUESTION 3
·
1 POINT
Find the Type II error given that the null hypothesis, H0, is: a building inspector claims that no more than 15% of structures in the county were built without permits.
Select the correct answer below:
The building inspector thinks that no more than 15% of the structures in the county were built without permits when, in fact, no more than 15% of the structures really were built without permits.
The building inspector thinks that more than 15% of the structures in the county were built without permits when, in fact, more than 15% of the structures really were built without permits.
The building inspector thinks that more than 15% of the structures in the county were built without permits when, in fact, at most 15% of the structures were built without permits.
The building inspector thinks that no more than 15% of the structures in the county were built without permits when, in fact, more than 15% of the structures were built without permits.
FEEDBACK
Content attribution- Opens a dialog
QUESTION 4
·
1 POINT
Suppose a chef claims that her meatball weight is less than 4 ounces, on average. Several of her customers do not believe her, so the chef decides to do a hypothesis test, at a 10% significance level, to persuade them. She cooks 14 meatballs. The mean weight of the sample meatballs is 3.7 ounces. The chef knows from experience that the standard deviation for her meatball weight is 0.5 ounces.
What is the test statistic (z-score) of this one-mean hypothesis test, rounded to two decimal places?
Provide your answer below:
$$Test statistic =−2.24
FEEDBACK
Content attribution- Opens a dialog
QUESTION 5
·
1 POINT
What is the p-value of a right-tailed one-mean hypothesis test, with a test statistic of z0=1.74? (Do not round your answer; compute your answer using a value from the table below.)
z1.51.61.71.81.90.000.9330.9450.9550.9640.9710.010.9340.9460.9560.9650.9720.020.9360.9470.9570.9660.9730.030.9370.9480.9580.9660.9730.040.9380.9490.9590.9670.9740.050.9390.9510.9600.9680.9740.060.9410.9520.9610.9690.9750.070.9420.9530.9620.9690.9760.080.9430.9540.9620.9700.9760.090.9440.9540.9630.9710.977
Provide your answer below:
0.0410
FEEDBACK
Content attribution- Opens a dialog
QUESTION 6
·
1 POINT
Kenneth, a competitor in cup stacking, claims that his average stacking time is 8.2 seconds. During a practice session, Kenneth has a sample stacking time mean of 7.8 seconds based on 11 trials. At the 4% significance level, does the data provide sufficient evidence to conclude that Kenneth's mean stacking time is less than 8.2 seconds? Accept or reject the hypothesis given the sample data below.
Select the correct answer below:
Do not reject the null hypothesis because the p-value 0.0401 is greater than the significance level α=0.04.
Reject the null hypothesis because the p-value 0.0401 is greater than the significance level α=0.04.
Reject the null hypothesis because the value of z is negative.
Reject the null hypothesis because |−1.75|>0.04.
Do not reject the null hypothesis because |−1.75|>0.04.
FEEDBACK
Content attribution- Opens a dialog
QUESTION 7
·
1 POINT
A recent study suggested that 81% of senior citizens take at least one prescription medication. Amelia is a nurse at a large hospital who would like to know whether the percentage is the same for senior citizen patients who go to her hospital. She randomly selects 59 senior citizens patients who were treated at the hospital and finds that 49 of them take at least one prescription medication. What are the null and alternative hypotheses for this hypothesis test?
Select the correct answer below:
{H0:p=0.81Ha:p>0.81
{H0:p≠0.81Ha:p=0.81
{H0:p=0.81Ha:p<0.81
{H0:p=0.81Ha:p≠0.81
FEEDBACK
Content attribution- Opens a dialog
QUESTION 8
·
1 POINT
A researcher claims that the proportion of cars with manual transmission is less than 10%. To test this claim, a survey checked 1000 randomly selected cars. Of those cars, 95 had a manual transmission.
The following is the setup for the hypothesis test:
{H0:p=0.10Ha:p<0.10
Find the test statistic for this hypothesis test for a proportion. Round your answer to 2 decimal places.
Provide your answer below:
$$Test_Statistic=−0.53
FEEDBACK
Content attribution- Opens a dialog
QUESTION 9
·
1 POINT
A medical researcher claims that the proportion of people taking a certain medication that develop serious side effects is 12%. To test this claim, a random sample of 900 people taking the medication is taken and it is determined that 93 people have experienced serious side effects. .
The following is the setup for this hypothesis test:
H0:p = 0.12
Ha:p ≠ 0.12
Find the p-value for this hypothesis test for a proportion and round your answer to 3 decimal places.
The following table can be utilized which provides areas under the Standard Normal Curve:
In: Statistics and Probability
| BrainWeight | BodyWeight |
| 3.385 | 44.5 |
| 0.48 | 15.5 |
| 1.35 | 8.1 |
| 465 | 423 |
| 36.33 | 119.5 |
| 27.66 | 115 |
| 14.83 | 98.2 |
| 1.04 | 5.5 |
| 4.19 | 58 |
| 0.425 | 6.4 |
| 0.101 | 4 |
| 0.92 | 5.7 |
| 1 | 6.6 |
| 0.005 | 0.14 |
| 0.06 | 1 |
| 3.5 | 10.8 |
| 2 | 12.3 |
| 1.7 | 6.3 |
| 2547 | 4603 |
| 0.023 | 0.3 |
| 187.1 | 419 |
| 521 | 655 |
| 0.785 | 3.5 |
| 10 | 115 |
| 3.3 | 25.6 |
| 0.2 | 5 |
| 1.41 | 17.5 |
| 529 | 680 |
| 207 | 406 |
| 85 | 325 |
| 0.75 | 12.3 |
| 62 | 1320 |
| 6654 | 5712 |
| 3.5 | 3.9 |
| 6.8 | 179 |
| 35 | 56 |
| 4.05 | 17 |
| 0.12 | 1 |
| 0.023 | 0.4 |
| 0.01 | 0.25 |
| 1.4 | 12.5 |
| 250 | 490 |
| 2.5 | 12.1 |
| 55.5 | 175 |
| 100 | 157 |
| 52.16 | 440 |
| 10.55 | 179.5 |
| 0.55 | 2.4 |
| 60 | 81 |
| 3.6 | 21 |
| 4.288 | 39.2 |
| 0.28 | 1.9 |
| 0.075 | 1.2 |
| 0.122 | 3 |
| 0.048 | 0.33 |
| 192 | 180 |
| 3 | 25 |
| 160 | 169 |
| 0.9 | 2.6 |
| 1.62 | 11.4 |
| 0.104 | 2.5 |
| 4.235 | 50.4 |
a. Input the data to R and draw a scatter plot, and you can see
that the current scale is not the best for display. You can apply a
log-transformation on both variables. This can be done by using the
log() function, you can put the old data.frame in the parenthesis,
and assign the output a name so that you will have a new data.frame
of the transformed data, something like below
> new.data <- log(old.data)
Draw a scatter plot of the new data, does it look much better?
c. Fit a linear model on the original data. Draw plot the
residual against the predictor using something similar to
> plot(old.data$BodyWeight, lm.fit$res)
What do you think about the assumption that the error term does not
depend on x ?
d. Fit a linear model on the log-transformed data. Draw a plot the residual against the predictor. What do you see now?
Can you please show all work?
In: Statistics and Probability
Please I need it urgently
Currently the company’s capital structure (total capital) is ungeared. However, the owners of Hassen constructions is planning to change their capital structure into a leverage (geared) capital structure as they believe having a debt component in its capital structure will be beneficial to the organization.
The company total capital is RO 300 million which is an equity-based capital structure. The company has two share buyback options available to move into a leverage(geared) capital structure.
Option 1
The company has an option in converting 30% of its equity capital to debt capital at an interest rate of 7%.
Option 2
The company has an option of converting 50% of its equity capital to debt capital at an interest rate of 7.5%
To evaluate the impact on the alternative policies the financial accountant of the company has presented the following data to evaluate the impact on ROE in the current capital structure and the above two given options.
The financial accountant believes that based on the sales forecast the sales could be either weak, average or strong. The probability for the market to be weak is 0.3, average 0.5 and strong 0.2.
The profits before interest and tax (PBIT) , if the market is considered to be weak is RO 30 million, if the market is average the PBIT is 50% greater than the market is weak and if the market is considered to be strong it is 75% greater than if the market is average.
The current applicable tax rate is 25%
Required:
d. Evaluate the factors that Hassen construction should consider when evaluating its capital structure policy.
In: Accounting
Welding fumes are a common occupational exposure. Several different welding fumes can cause similar adverse health effects. Personal sampling of a welding operation at a manufacturing facility produced the following 8-hour time-weighted average (TWA) results for individual metal fumes.
| Metal Fume | Result | OSHA PEL | ACGIH TLV |
|---|---|---|---|
| Antimony | 0.05 mg/m³ | 0.5 mg/m³ | 0.5 mg/m³ |
| Beryllium | 0.00001 mg/m³ | 0.0002 mg/m³ | 0.00005 mg/m³ (I) |
| Cadmium | 0.025 mg/m³ | 0.005 mg/m³ | 0.01 mg/m³ |
| Chromium | 0.02 mg/m³ | 1 mg/m³ | 0.5 mg/m³ |
| Copper | 0.03 mg/m³ | 0.1 mg/m³ | 0.2 mg/m³ |
| Iron Oxide | 0.5 mg/m³ | 10 mg/m³ | 5 mg/m³ (R) |
| Magnesium Oxide | 0.02 mg/m³ | 15 mg/m³ | 10 mg/m³ |
| Molybdenum | 0.003 mg/m³ | 15 mg/m³ | 10 mg/m³ (I) |
| Nickel | 0.25 mg/m³ | 1 mg/m³ | 1.5 mg/m³ (I) |
| Zinc Oxide | 0.3 mg/m³ | 5 mg/m³ | 2 mg/m³ (R) |
(R) Respirable fraction (I) Inhalable fraction
Briefly summarize the primary health effects associated with overexposure to each type of metal fume, including both acute and chronic health effects. Explain what analytical methods you would use for evaluating health hazards in the workplace.
Identify the types of metal fumes that would produce similar health effects on an exposed worker. Assume that each listed metal can cause respiratory irritation. Use the equation in 1910.1000(d)(2)(i) to calculate the equivalent exposure (in relation to OSHA PELS) for the metal fumes with similar health effects based on the “Result” column in the table above. Discuss whether you believe any of the individual metal fume exposures or the combined exposure exceeds an OSHA PEL or an ACGIH TLV.
In: Nursing