In: Finance
Case Study: Max
Client Profile: “Max is a 12-year old boy whose father died about 5 years ago. His father experienced periodic episodes of depression during his lifetime. After his father’s death, Max displayed tantrums and became more aggressive toward his toys and people. He took on a serious, almost sad expression. He seemed empty and alone, even when in a room full of people. Max saw a therapist; after a period of play therapy, he stopped being more aggressive than boys his age, began to smile and played with peers.”
“Max’s mother went to work after his father’s death; she now works two jobs. When she is home, she is authoritarian in her parenting style. Recently, Max’s mother snooped around Max’s room and found some morbid pictures that he had drawn (i.e., pictures of funerals, cemeteries, and people being shot or knifed to death). She also found cigarettes; as a consequence, he cannot have any friends visit and he may not leave the house except to go to school.”
Max is not turning in schoolwork and is picking fights at school. In the evening, he plays video games and makes excuses for procrastinating with his homework. He lies awake at night worrying about his homework and things such as failing school, disappointing his mother, not having friends, and wondering if everyone hates him. When his mother tells him he is going to fail school, he responds, ‘I don’t care.’”
The school nurse notices Max’s behavior and becomes concerned, especially since two other students recently attempted suicide. She shares this information with Max’s mother and suggests that a health care provider see Max. His mother takes him to a sliding-fee-scale clinic where a family practice health care provider who volunteers at the clinic sees Max. The health care provider identifies depression as a problem, considers putting Max on medication, but decides instead to have him admitted to a residential treatment center for evaluation and treatment. A clinic social worker finds funding from various sources to cover the cost of treatment at the facility for children and adolescents. The facility has child and adolescent psychiatrists and psychiatric nurses on staff.” [Richardson, B.K. (2007). Case Study Series: Psychiatric Nursing, Clifton Park, NY: Thomson Delmar Learning.]
Case Study: The nurse on the children’s unit of the residential treatment center receives word Max will be admitted for treatment of depression. When Max and his mother arrive, the nurse does an intake interview with Max alone and then with both Max and his mother. Then the nurse interviews his mother and gives her a copy of the parent handbook while someone orients Max to the unit and its rules. Both Max and his mother are asked to sign a form indicating they have read the unit rules and will abide by them. Max’s belongings are inventoried; some are locked up, while he is permitted to keep others. The child psychiatrist prescribes fluoxetine (Prozac) as well as individual and group therapy.
One night, Max gets irritable with the nurse for not letting him stay up past unit bedtime to watch his favorite television show. Max says, “It doesn’t matter because I am just going to kill myself tonight anyway.” The psychiatrist is notified and writes orders for Max to be placed on 1 to 1 observation within eyesight of an assigned staff member at all times. The following day Max learns he cannot go to the recreation building because a unit rule states, “Anyone who threatens to kill himself or herself cannot leave the unit until he or she no longer wishes to kill himself or herself and 24 hours have passed.” Max tells the nurse, “I was just kidding. I really wasn’t going to kill myself.”
Questions
1. Max’s mother tells you (the nurse) about the 2 other students at Max’s school who attempted suicide recently. How should you respond?
2.What data would you gather on Max and his family prior to writing a nursing care plan?
In: Nursing
A survey is divided into three parts:
Part 1 includes socioeconomic status (SES) information; parent’s education, employment status (currently employed yes or no), income level, and receiving free or reduced lunch at school.
In part 2, the questions are regarding the environment at home, time spent watching (playing video games) TV at home, having a TV in their rooms, computer available to do assignments at home, Internet access at home, etc.
part 3, includes questions related to the safety of the neighborhood environment: some examples include if the students walk to school, how safe they feel while walking to and from school, do you feel safe at school? Are there a lot of fights at school? etc.
The purpose of you collecting these data is to create a model that can help to predict academic achievement in high school students using some of these variables.
In: Statistics and Probability
A regression model to predict Y, the state-by-state 2005 burglary crime rate per 100,000 people, used the following four state predictors: X1 = median age in 2005, X2 = number of 2005 bankruptcies per 1,000 people, X3 = 2004 federal expenditures per capita, and X4 = 2005 high school graduation percentage.
| Predictor | Coefficient |
| Intercept | 4,286.0597 |
| AgeMed | -26.986 |
| Bankrupt | 18.5775 |
| FedSpend | -0.0280 |
| HSGrad% | -28.5624 |
(a) Write the fitted regression equation. (Round your answers to 4 decimal places. Negative values should be indicated by a minus sign.)
yˆy^ = + AgeMed + Bankrupt + FedSpend + HSGrad%
(b-1) The 2005 state-by-state crime rate per 100,000
| increases by about 27 as the state median age increases. | |
| decreases by about 27 as the state median age increases. |
(b-2) The 2005 state-by-state crime rate per 100,000
| increases by about 19 for every 1,000 new bankruptcies filed. | |
| decreases by about 19 for every 1,000 new bankruptcies filed. |
(b-3) The 2005 state-by-state crime rate per 100,000
| decreases by 0.028 for each dollar increase in federal funding per person. | |
| increases by 0.028 for each dollar increase in federal funding per person. |
(b-4) The 2005 state-by-state crime rate per 100,000
| decreases by about 29 for each 1% increase in high school graduations. | |
| increases by about 29 for each 1% increase in high school graduations. |
(c) Would the intercept seem to have meaning in this regression?
| No | |
| Yes |
(d) Make a prediction for Burglary when X1= 34 years, X2= 7.2 bankruptcies per 1,000, X3= $5,044, and X4= 84 percent.
Burglary Rate
rev: 09_26_2016_QC_CS-62964, 09_20_2017_QC_CS-101173
In: Statistics and Probability
A regression model to predict Y, the state-by-state 2005 burglary crime rate per 100,000 people, used the following four state predictors: X1 = median age in 2005, X2 = number of 2005 bankruptcies per 1,000 people, X3 = 2004 federal expenditures per capita, and X4 = 2005 high school graduation percentage. Predictor Coefficient Intercept 4,304.4610 AgeMed -26.903 Bankrupt 20.8921 FedSpend -0.0312 HSGrad% -29.1815 (a) Write the fitted regression equation. (Round your answers to 4 decimal places. Negative values should be indicated by a minus sign.) yˆ =_____ + _____ AgeMed + _______ Bankrupt + _____ FedSpend + ______ HSGrad%
(b-1) The 2005 state-by-state crime rate per 100,000
increases by about 27 as the state median age increases.
decreases by about 27 as the state median age increases.
(b-2) The 2005 state-by-state crime rate per 100,000
decreases by about 21 for every 1,000 new bankruptcies filed.
increases by about 21 for every 1,000 new bankruptcies filed.
(b-3) The 2005 state-by-state crime rate per 100,000
decreases by 0.0312 for each dollar increase in federal funding per person.
increases by 0.0312 for each dollar increase in federal funding per person.
(b-4) The 2005 state-by-state crime rate per 100,000
decreases by about 29 for each 1% increase in high school graduations.
increases by about 29 for each 1% increase in high school graduations.
(c) Would the intercept seem to have meaning in this regression?
Yes No
(d) Make a prediction for Burglary when X1 = 30 years, X2 = 5.0 bankruptcies per 1,000, X3 = $5,723, and X4 = 80 percent.
(Round your answers to 4 decimal places.)
Burglary Rate $_______
In: Statistics and Probability
A regression model to predict Y, the state-by-state 2005 burglary crime rate per 100,000 people, used the following four state predictors: X1 = median age in 2005, X2 = number of 2005 bankruptcies per 1,000 people, X3 = 2004 federal expenditures per capita, and X4 = 2005 high school graduation percentage.
| Predictor | Coefficient |
| Intercept | 4,286.0597 |
| AgeMed | -26.986 |
| Bankrupt | 18.5775 |
| FedSpend | -0.0280 |
| HSGrad% | -28.5624 |
(a) Write the fitted regression equation. (Round your answers to 4 decimal places. Negative values should be indicated by a minus sign.)
yˆy^ = + AgeMed + Bankrupt + FedSpend + HSGrad%
(b-1) The 2005 state-by-state crime rate per 100,000
| increases by about 27 as the state median age increases. | |
| decreases by about 27 as the state median age increases. |
(b-2) The 2005 state-by-state crime rate per 100,000
| decreases by about 19 for every 1,000 new bankruptcies filed. | |
| increases by about 19 for every 1,000 new bankruptcies filed. |
(b-3) The 2005 state-by-state crime rate per 100,000
| decreases by 0.028 for each dollar increase in federal funding per person. | |
| increases by 0.028 for each dollar increase in federal funding per person. |
(b-4) The 2005 state-by-state crime rate per 100,000
| decreases by about 29 for each 1% increase in high school graduations. | |
| increases by about 29 for each 1% increase in high school graduations. |
(c) Would the intercept seem to have meaning in this regression?
| No | |
| Yes |
(d) Make a prediction for Burglary when X1= 34 years, X2= 7.2 bankruptcies per 1,000, X3= $5,044, and X4= 84 percent.
Burglary Rate
rev: 09_26_2016_QC_CS-62964, 09_20_2017_QC_CS-1011
In: Statistics and Probability
One evening, Andrea Filer and her daughter were riding their horses along Riley Hill Road, a public highway in the Town of Salem, New York. At the same time, Megan Adams was jogging along the same road with her son in a stroller and two dogs by her side. Filer noticed that her horse's ears flickered and stiffened, apparently hearing sounds from behind. Filer turned and saw Adams. When Adams observed that Filer was having difficulty controlling her horse, she slowed to a walk. While Adams was still about 50 yards behind the riders, one of her dogs barked and the horses both abruptly broke into a canter or a run. Filer, who was not wearing a helmet, fell from her horse seconds later and sustained serious injuries. Plaintiff Filer sued Adams, alleging that Adams was negligent in following the horse riders too elosely and letting her dogs bark, which she claimed spooked the horses. Defendant Adams asserted that Filer, an experienced rider, should have had control of her horse. Adams stated that she was a far enough dis- tance from Filer and that walking with the stroller and the dog's bark were not the proximate cause of Filer's accident. Were Adams's activities the proximate cause of Filer's riding accident? Andrea v. Adams, 966 N.Y.S.2d 553, 106 A.D.3d 1417, 2013 N.Y. App. Div. Lexis 3831 (Appellate Division of the Supreme Court of New York, 2013)
In: Economics
Researchers would like to know whether the proportions of
elementary school children who are obese differ in rural and urban
area. An earlier study found that 50% of urban school children and
45% of rural school children are obese. The researchers select 153
urban school children and 191 rural school children. Suppose
[^(p)]1 and [^(p)]2 denote
sample proportions of urban and rural school children respectively
who are obese.
Answer all the questions below (where appropriate) as a
fraction not as a percentage.
What is the expected proportion of obese among urban school children, i.e. expected value of [^(p)]1? [Answer to two decimal places.]
| A: 0.34 | B: 0.43 | C: 0.50 | D: 0.78 | E: 0.97 |
| Tries 0/3 |
What is the standard deviation of proportion of obese among urban school children, i.e. σ([^(p)]1)? [Answer to four decimal places.]
| A: 0.0404 | B: 0.1299 | C: 0.1494 | D: 0.3599 | E: 0.8455 |
| Tries 0/3 |
What is the expected proportion of obese among rural school children, i.e. expected value of [^(p)]2? [Answer to two decimal places.]
| A: 0.44 | B: 0.45 | C: 0.49 | D: 0.60 | E: 0.98 |
| Tries 0/3 |
What is the standard deviation of proportion of obese among rural school children, i.e. σ([^(p)]2)? [Answer to four decimal places.]
| A: 0.0360 | B: 0.1933 | C: 0.4943 | D: 0.5395 | E: 0.8700 |
| Tries 0/3 |
What is the expected difference of proportions of obese between urban and rural school children, i.e. expected value of [^(p)]1 − [^(p)]2? [Answer to two decimal places.]
| A: 0.02 | B: 0.03 | C: 0.05 | D: 0.07 | E: 0.11 |
| Tries 0/3 |
What is the standard deviation of difference of proportions of obese between urban and rural school children, i.e. σ([^(p)]1 − [^(p)]2)? [Answer to four decimal places.]
| A: 0.0002 | B: 0.0044 | C: 0.0541 | D: 0.4994 | E: 0.8715 |
| Tries 0/3 |
What is the probability that the difference of proportions of obese between urban and rural school children will be larger than 0.10? i.e. find P([^(p)]1 − [^(p)]2 > 0.10). [Answer to four decimal places.]
| A: 0.0451 | B: 0.1778 | C: 0.2705 | D: 0.3058 | E: 0.3746 |
In: Statistics and Probability
John Smith received a scholarship from university of Houston-Down town for $20,000. He used the scholarship for:
Tuition 12,000
Computer 1,000
Books and Supplies 3,000
Meals and lodging 4,000
Determine the effect of the scholarship on John Smith Income
In: Accounting
In a small town in France, the demand curve for wine is given by PD = 124 - 2QD and the supply curve for wine is given by PS = 4 + 2QS. Suppose a price ceiling is imposed on wine at a price of $50. This will cause a _____________(shortage/surplus) of ______________ bottles of wine.
In: Economics