Read the case study details below then answer the questions.
Seven-year-old Timothy’s mother takes him to his pediatrician for his annual checkup. His weight is 68 pounds (30.91 kg), plotted at the 95th percentile, and his height is 50 inches (127 cm, 1.27 M), between the 75th and 90th percentiles for his age. Timothy is considered sedentary. His body mass index plots at the 95th percentile for his age. His growth percentiles have been increasing over the last several years. Timothy has a cousin Marley. She is also 7 years old, is considered low active, weighs 69 pound (31.3 Kg) and is 50.5 inches tall (128 cm, 1.28 M). Timothy and Marley have nearly the same Estimated Energy Requirements, 1652 and 1651 Calories per day respectively.
Timothy’s mother expresses concern to the pediatrician about her son’s weight. His older and younger brothers and his cousin Marley are thinner than Timothy. Timothy’s mother is obese, but his father is a normal weight for height. Timothy is in the second grade. He rides the school bus to and from school. He participates in the School Lunch Program at his school. After school, Timothy and his brothers stay in their home with a babysitter until one of their parents returns home from work. Timothy usually watches TV or plays video games after school. His parents leave snack foods—chips, cookies, and sodas—in the house for their sons to have after school. His mother usually prepares their evening meal, which consists of a meat, starch, vegetables, and a dessert item. After dinner, Timothy does his homework and then usually watches more TV with his parents. He usually has a dish of ice cream before going to bed.
In: Nursing
A)
As part of a larger project to study the behavior of stressed-skin panels, a structural component being used extensively in North America, an article reported on various mechanical properties of Scotch pine lumber specimens. Data on the modulus of elasticity (MPa) obtained 1 minute after loading in a certain configuration and 4 weeks after loading for the same lumber specimens is presented here.
| Observation | 1 min | 4 weeks | Difference |
|---|---|---|---|
| 1 | 10,490 | 9,160 | 1330 |
| 2 | 16,620 | 13,250 | 3370 |
| 3 | 17,100 | 14,720 | 2380 |
| 4 | 15,480 | 12,750 | 2730 |
| 5 | 12,960 | 10,120 | 2840 |
| 6 | 17,260 | 14,570 | 2690 |
| 7 | 13,400 | 11,220 | 2180 |
| 8 | 13,900 | 11,100 | 2800 |
| 9 | 13,630 | 11,420 | 2210 |
| 10 | 13,240 | 10,930 | 2310 |
| 11 | 14,370 | 12,110 | 2260 |
| 12 | 11,700 | 8,620 | 3080 |
| 13 | 15,470 | 12,590 | 2880 |
| 14 | 17,840 | 15,090 | 2750 |
| 15 | 14,070 | 10,550 | 3520 |
| 16 | 14,760 | 12,230 | 2530 |
Calculate an upper confidence bound for the true average
difference between 1-minute modulus and 4-week modulus; first check
the plausibility of any necessary assumptions. (Use α =
0.05. Round your answer to two decimal places.)
MPa=_______
B)
It is thought that the front cover and the nature of the first question on mail surveys influence the response rate. An article tested this theory by experimenting with different cover designs. One cover was plain; the other used a picture of a skydiver. The researchers speculated that the return rate would be lower for the plain cover.
| Cover | Number Sent | Number Returned |
|---|---|---|
| Plain | 207 | 102 |
| Skydiver | 214 | 109 |
Does this data support the researchers' hypothesis? Test the relevant hypotheses using α = 0.10 by first calculating a P-value.
Compute the test statistic value and find the P-value. (Round your test statistic to two decimal places and your P-value to four decimal places.)
| z = | |
| P-value = |
C)
Do teachers find their work rewarding and satisfying? An article reports the results of a survey of 396 elementary school teachers and 261 high school teachers. Of the elementary school teachers, 224 said they were very satisfied with their jobs, whereas 125 of the high school teachers were very satisfied with their work. Estimate the difference between the proportion of all elementary school teachers who are satisfied and all high school teachers who are satisfied by calculating a 95% CI. (Use pelementary − phigh school. Round your answers to four decimal places.)
| ( , ) |
In: Statistics and Probability
A magazine reported that at the top 50 business schools in a region, students studied an average of 17.8 hours. Set up a hypothesis test to try to prove that the mean number of hours studied at your school is different from the reported 17.8 hour benchmark. Complete parts (a) through (c) below.
a. State the null and alternative hypotheses. Choose the correct answer below.
A. Upper H 0: alpha not equals 17.8 Upper H 1: alpha equals 17.8
B. Upper H 0: beta not equals 17.8 Upper H 1: beta equals 17.8
C. Upper H 0: muequals17.8 Upper H 1: Upper X overbarnot equals17.8
D. Upper H 0: Upper X overbarequals17.8 Upper H 1: Upper X overbarnot equals17.8
E. Upper H 0: alpha equals 17.8 Upper H 1: beta not equals 17.8
F. Upper H 0: munot equals 17.8 Upper H 1: Upper X overbar equals17.8
G. Upper H 0: alphaequals17.8 Upper H 1: alphanot equals17.8
H. Upper H 0: muequals17.8 Upper H 1: munot equals17.8
I. Upper H 0: Upper X overbarnot equals17.8 Upper H 1: Upper X overbarequals17.8
J. Upper H 0: alphanot equals17.8 Upper H 1: betaequals17.8
K. Upper H 0: munot equals17.8 Upper H 1: muequals17.8
L. Upper H 0: betaequals17.8 Upper H 1: betanot equals17.8
b. What is a Type I error for your test?
A. Concluding that the mean number of hours studied at your school is different from the reported 17.8 hour benchmark when in fact it is different
B. Concluding that the mean number of hours studied at your school is not different from the reported 17.8 hour benchmark when in fact it is different
C. Concluding that the mean number of hours studied at your school is different from the reported 17.8 hour benchmark when in fact it is not different
c. What is a Type II error for your test?
A. Concluding that the mean number of hours studied at your school is not different from the reported 17.8 hour benchmark when in fact it is different
B. Concluding that the mean number of hours studied at your school is different from the reported 17.8 hour benchmark when in fact it is different
C. Concluding that the mean number of hours studied at your school is different from the reported 17.8 hour benchmark when in fact it is not different
In: Math
(1 point) A national sporting good store wishes to use
demographic information to predict its monthly sales, in $1000s.
Thrity-eight, n=38n=38, stores of the chain are randomly chosen
across the country. It is known that each store is approximately
the same size and carries the same merchandise.
The geographic area from which a store draws its customers is known
as the customer base. One of the variables is the percentage of the
customer base who have graduated from high school.
MonthlySalesiMonthlySalesi = β0β0 +
β1PercentHSGradsiβ1PercentHSGradsi + eiei
where
MonthlySalesiMonthlySalesi - is the total sales in month ii, in
$1000s
PercentHSGradsiPercentHSGradsi - is percentage of all customers in
store ii customer base that have graduated from high school
A least-squares regression was ran in R producing the following
output:
Regression Analysis: MonthlySales versus PercentHSGrads
| Predictor | Coef | SD Coef | T | P |
| Constant | -2970 | 1371 | ||
| PercentHSGrads | 59.66 | 17.67 |
S = 802.004 R-Sq =
| Analysis of Variance | |||||
| Source | DF | SS | MS | F | P |
| Regression | 7333350 | ||||
| Residual Error | 23155564 | ||||
| Total | 37 |
Using the partial R output, answer the questions below.
(a) Estimate the model. Use two-decimals your estimation of the
slope term, no decimals in the estimation of the y-intercept.
MonthlySalesiˆMonthlySalesi^ =
equation editor
Equation Editor
+
equation editor
Equation Editor
PercentHSGradsiPercentHSGradsi
(b) What percentage of the variation in a store's monthly sales
cannot be explained by its linear dependency on the percentage of
the customer base that are high school graduates? Enter your answer
as a percentage, using two decimal places.
equation editor
Equation Editor
%
(c) Does the data collected indicate that the monthly sales of a
store can be expressed as a linear function the percentage of high
school graduates in its customer base? Select the correct
statisticaly hypotheses.
A. H0:βˆ1≥0HA:βˆ1<0H0:β^1≥0HA:β^1<0
B. H0:β1=0HA:β1≠0H0:β1=0HA:β1≠0
C. H0:β1=0HA:β1<0H0:β1=0HA:β1<0
D. H0:βˆ1≥0HA:βˆ1≠0H0:β^1≥0HA:β^1≠0
E. H0:β1≥0HA:β1>0H0:β1≥0HA:β1>0
F. H0:βˆ1=0HA:βˆ1>0H0:β^1=0HA:β^1>0
(d) Using the FF-test, test the statistical hypotheses determined
in (c). Find the value of the test statistic, using two decimals in
your answer.
FcalcFcalc =
equation editor
Equation Editor
(e) Testing the statistical hypotheses in (c) at α=0.05α=0.05, you
can conclude from this data that the ? monthly sales of
a store percentage of customer base that are high school
graduates ? can cannot be expressed as
a linear function of the ? monthly sales of a store
percentage of customer base that are high school graduates .
(f) Can you infer from this data that an increase of 1% to the
percentage of high school graduates in the customer based will lead
to an mean/average increase in the store's monthly sales by more
than $50,000?
(i) Find the value of the test statistic, use two decimal places in
your answer.
TcalcTcalc =
equation editor
Equation Editor
(ii) Find the PP-value of the result, using three decimals.
PP-value =
equation editor
Equation Editor
(g) A store located at a local mall has recently discovered that
90% of its customer base has a high school diploma. With 95%
confidence, estimate this store's monthly sales for the current
month.
Note: You will need
∑38i=1PercentHSGradsi=2935.17∑i=138PercentHSGradsi=2935.17 and
∑38i=1PercentHSGrads2i=228777∑i=138PercentHSGradsi2=228777
Lower Bound =
equation editor
Equation Editor
$1000s (use one decimal in your answer)
Upper Bound =
equation editor
Equation Editor
$1000s (use one decimal in your answer)
(h) A residual plot of the regression was consulted.
What does this residual plot say about the condition(s) of the
model? Pick the most appropriate answer.
A. The variance in the monthly sales is not the
same for all stores with different proportions of high school
graduates in their respective customer base.
B. The variance in the monthly sales is the same
for all stores with different proportions of high school graduates
in their respective customer base.
C. The distribution in the monthly sales is
Normally distributed.
D. The distribution in the monthly sales is not
Normally distributed.
E. The variation in the proportion of the customer
base that are high school graduates is the same for all
stores.
F. The variation in the proportion of the customer
based that are high school graduates is not the same for all
stores.
COULD YOU ANSWER ONLY ON QUESTION H, G, E, F
In: Statistics and Probability
Background
Hotel One is one of the two hotels serving Dayville, a small town in the US Midwest. Fifty percent of its customers are out-of-town visitors to the local college, 30 percent are visiting Dayville for business purposes, and the remaining 20 percent of Hotel One’s customers are leisure travelers. The hotel is within one mile from campus, approximately four miles from the city center, and eight miles from the airport. It is easy to reach by car, taxi, or city bus. You are a manager of Hotel One. Your facility consists of 150 rooms, all of which are standard rooms with two double beds. Your only competitor in Dayville, The Other Hotel, has fewer rooms (100), but 20 of their rooms are luxury suites with king beds and a sofa couch (the other 80 are standard rooms with two double beds). This is the extent of the information provided to you at this point.
Assignment
In order to better understand your unit’s operating environment, you are asked to provide your estimate of the demand equation that would account for various factors that affect your customer traffic. This will be done by using regression techniques. The first step in estimating a demand equation is to determine what variables will be used in the regression. Please provide detailed answers to the following questions:
1. What do you think should be the dependent variable in your demand equation? What units of measurement for that variable are you going to adopt? Please provide a detailed explanation for these choices.
2. Please request information about up to five independent (explanatory) variables for your demand equation. For each variable you request, (i) provide reasons why you expect it to be
important for your analysis and (ii) explain the expected sign of the relationship between the proposed independent variable and your proposed dependent variable.
3. Show the exact demand equation you are proposing to estimate.
In: Finance
Trevor is interested in purchasing the local hardware/sporting goods store in the small town of Dove Creek, Montana. After examining accounting records for the past several years, he found that the store has been grossing over $850 per day about 55% of the business days it is open. Estimate the probability that the store will gross over $850 for the following. (Round your answers to three decimal places.)
(a) at least 3 out of 5 business days
(b) at least 6 out of 10 business days
(c) fewer than 5 out of 10 business days
(d) fewer than 6 out of the next 20 business days
If the outcome described in part (d) actually occurred, might it shake your confidence in the statement p = 0.55? Might it make you suspect that p is less than 0.55? Explain.
Yes. This is unlikely to happen if the true value of p is 0.55.
Yes. This is likely to happen if the true value of p is 0.55.
No. This is unlikely to happen if the true value of p is 0.55.
No. This is likely to happen if the true value of p is 0.55.
(e) more than 17 out of the next 20 business days
If the outcome described in part (e) actually occurred, might you suspect that p is greater than 0.55? Explain.
Yes. This is unlikely to happen if the true value of p is 0.55.
Yes. This is likely to happen if the true value of p is 0.55.
No. This is unlikely to happen if the true value of p is 0.55.
No. This is likely to happen if the true value of p is 0.55.
In: Statistics and Probability
Problem 2. Suppose there is only one yoga studio in town. The marginal cost of producing yoga sessions is as follows: MC=12. The yoga studio faces the following market demand function: Q=20-(1/2)P, and marginal revenue MR=40-4Q.
In: Economics
Model: Y = b0+ b1Bedrooms+b2Sqft+ b3Dishwasher Dummy+e
Dishwasher Dummy 1 if Dishwasher
included
0 Otherwise
|
SUMMARY OUTPUT |
Dependent Variable: Apartment Rent ($) |
|||||
|
Regression Statistics |
||||||
|
Multiple R |
0.824 |
|||||
|
R Square |
0.678 |
|||||
|
Adjusted R Square |
0.661 |
|||||
|
Standard Error |
92.757 |
|||||
|
Observations |
60 |
|||||
|
ANOVA |
df |
SS |
MS |
F |
Significance F |
|
|
Regression |
3 |
1015955.29 |
338651.76 |
39.36 |
8.11272E-14 |
|
|
Residual |
56 |
481813.65 |
8603.82 |
|||
|
Total |
59 |
1497768.93 |
||||
|
Coefficients |
Standard Error |
t Stat |
P-value |
Lower 95% |
Upper 95% |
|
|
Intercept |
216.402 |
44.797 |
4.831 |
0.000 |
126.664 |
306.141 |
|
Bedrooms |
59.936 |
27.504 |
2.179 |
0.034 |
4.838 |
115.033 |
|
Square feet area |
0.276 |
0.069 |
3.981 |
0.000 |
0.137 |
0.415 |
|
Dishwasher |
50.00 |
20.923 |
2.389 |
0.047 |
65.000 |
85.000 |
H0:
HA:
Criticalt-value=
Show on a graph:
Are number of bedrooms significant in explaining apartment Rent? Square Feet Area?
In: Statistics and Probability
3. Breakdown of a cartel agreement Consider a town in which only two residents, Sam and Teresa, own wells that produce water safe for drinking. Sam and Teresa can pump and sell as much water as they want at no cost. For them, total revenue equals profit. The following table shows the town's demand schedule for water. Price Quantity Demanded Total Revenue (Dollars per gallon) (Gallons of water) (Dollars) 3.00 0 0 2.75 50 $137.50 2.50 100 $250.00 2.25 150 $337.50 2.00 200 $400.00 1.75 250 $437.50 1.50 300 $450.00 1.25 350 $437.50 1.00 400 $400.00 0.75 450 $337.50 0.50 500 $250.00 0.25 550 $137.50 0 600 0 Suppose Sam and Teresa form a cartel and behave as a monopolist. The profit-maximizing price is $ per gallon, and the total output is gallons. As part of their cartel agreement, Sam and Teresa agree to split production equally. Therefore, Sam's profit is $ , and Teresa's profit is $ . Suppose that Sam and Teresa have been successfully operating as a cartel. They each charge the monopoly price and sell half of the monopoly quantity. Then one night before going to sleep, Sam says to himself, "Teresa and I aren't the best of friends anyway. If I increase my production to 50 gallons more than the cartel amount, I can increase my profit even though her profit goes down. I will do that starting tomorrow." After Sam implements his new plan, the price of water to $ per gallon. Given Teresa and Sam's production levels, Sam's profit becomes $ and Teresa's profit becomes $ . Because Sam has deviated from the cartel agreement and increased his output of water to 50 gallons more than the cartel amount, Teresa decides that she will also increase her production to 50 gallons more than the cartel amount. After Teresa increases her production, Sam's profit becomes $ , Teresa's profit becomes $ , and total profit (the sum of the profits of Sam and Teresa) is now $ . True or False: Based on the fact that both Sam and Teresa increased production from the initial cartel quantity, you know that the output effect was larger than the price effect at that quantity. True False Note that Sam and Teresa started by behaving cooperatively. However, once Sam decided to cheat, Teresa decided to cheat as well. In other words, Teresa's output decisions are based on Sam's actions.
This behavior is an example of
In: Economics
On July 1, 2019, the first day of its 2020 fiscal year, the Town
of Bear Creek issued at par $4,200,000 of 8 percent term bonds to
renovate a historic wing of its main administrative building. The
bonds mature in five years on July 1, 2024. Interest is payable
semiannually on January 1 and July 1.
As illustrated in the table below, a sinking fund is to be
established with equal semiannual additions made on June 30 and
December 31. Cash for the sinking fund additions and the semiannual
interest payments will be transferred from the General Fund shortly
before the due dates. Investment earnings are added to the
investment principal.
|
Fiscal |
Period |
Required |
Expected |
Ending |
|||||||
|
2020 |
1 |
$ |
349,822 |
$ |
0 |
$ |
349,822 |
||||
|
2 |
349,822 |
13,993 |
713,637 |
||||||||
|
2021 |
3 |
349,822 |
28,545 |
1,092,004 |
|||||||
|
4 |
349,822 |
43,680 |
1,485,507 |
||||||||
|
2022 |
5 |
349,822 |
59,420 |
1,894,749 |
|||||||
|
6 |
349,822 |
75,790 |
2,320,361 |
||||||||
|
2023 |
7 |
349,822 |
92,814 |
2,762,997 |
|||||||
|
8 |
349,822 |
110,520 |
3,223,339 |
||||||||
|
2024 |
9 |
349,822 |
128,934 |
3,702,095 |
|||||||
|
10 |
349,822 |
148,084 |
4,200,000 |
||||||||
Required
1. a-1. Prepare journal entries in the debt service fund for the following: (If no entry is required for a transaction/event, select "No Journal Entry Required" in the first account field. Do not round intermediate calculations.)
On July 1, 2019, record the budget for the fiscal year ended June 30, 2020. Include all inter-fund transfers to be received from the General Fund during the year. An appropriation should be provided only for the interest payment due on January 1, 2020.
A, Term Bond Debt Service Fund:
On December 28. 2019, the General Fund transferred $517,882 to the debt service fund. The addition to the sinking fund was immediately invested in 8 percent certificates of deposit.
B1. Tern Bond Debt Service Fund: Record the transfer fro the general fund to the debt service fund
B2. Record the investment in the certificates of deposit.
On December 28, 2019, the city issued checks to bondholders for the interest payment due on January 1, 2020.
C. Term Bond Debt Service Fund:
On June 27, 2020, the General Fund transferred $517, 822 to the debt service fund. The addition for the sinking fund was invested immediately in 8 percent certificates of deposit.
D1. Term Bond Service Fund: Record the transfer from the general fund to the debt service fund.
D2. Record the investment in the certificates of deposit
Actual interest earned on sinking fund investments at year end (june 30, 2020) was the same as the amount budgeted in the table. This interest adds to the sinking fund balance.
E. Term Bond Service Fund
In: Accounting