Traditional Views On Stranger Rape Criminology Essay

Traditional Views On Stranger Rape Criminology Essay I prefer to characterize rape simply as a form of torture. Like the torturer, the rapist is motivated by the urge to dominate, humiliate, and destroy his victim. Like a torturer, he does so by using the most intimate acts available to humans sexual ones. Helen Benedict, Virgin or Vamp, 1992 Rape is the act of forced, unwanted sexual assault. It can be a form of sexual harassment or sexual intercourse. This can be done by a stranger, an acquaintance, or a family member. Globally, rape is an occurring crime that victimizes not only women but also children and men too (Starman, 2009).In 1997, according to the Worldwide Sexual Assault Statistics there is a large percentage of sexual assault victims that are less than 15 years old (2005). In 2000, there was a report that in seven different countries, 60% of sexual assault victims know their attackers. In 2001, 1 out of 3 women worldwide has experienced rape or sexual assault (Worldwide Sexual Assault Statistics, 2005). Also, in an intensive study, it was found that in eight different countries, 24.7% experienced sexual violence in dating relationships (Worldwide Sexual Assault Statistics, 2005). Also, the Worldwide Sexual Assault Statistics reported that studies showed that 5-10 percent of men experience sexual assault in th eir childhood days (2005). These statistics imply that rape is a very serious crime. Even family members cannot be excused out of it. According to Susan Estrich, there are two types of rape: traditional rape described to be a violent rape committed by a stranger and non-traditional rape described to be a less violent rape committed by an acquaintance of the victim (qtd. by Shanahan, 1999). Estrich suggested that non-traditional rape requires a less severe punishment compared to the traditional rape (qtd. by Shanahan, 1999). However, this is an unfair line of thinking. Rape is a crime. It is not dependent on who did it and who the victim is. In this paper, the first part will discuss rape and its history. The second part will discuss about and compare the two types of rape: traditional rape and non-traditional rape. Emphasis will be given to the traditional stranger rape case. The third part will discuss the current penalties that are given to the rapists. Emphasis will also be giv en to the traditional stranger rape case. A thorough evaluation of the penalties and its implications will be discussed. The last part will discuss about how this traditional stranger view fails to fairly and accurately represent the true nature of rape as an offence. Rape first appeared on historical texts in the form of early religious texts. Rape is commonly denoted both as abduction and in a sexual sense. In Greek Mythology, some famous stories depicted rape of women and male rape. First is the rape of Europa by Zues, It was written that Europa, a Phoenician princess, was abducted by Zues and they had sexual contact and had children (The Abduction of Europa, 2010). Second, the rape of Ganymede by Zues, the story tells that Zeus fell in love with a Trojan prince named Ganymede. Zues abducted the boy and made him his lover. This myth was even used by Greek philosopher Plato to justify his sexual feelings toward his male pupils (Gibson, 2004). Both of these myths were not treated in negative terms. These rapes went out unpunished because these sexual relationships were starting to be a part of the Greek society. Lastly, the famous rape of Chrysippus by the prince of Thebes named Laios (Atsma, 2008). In the story, Chrysippus killed himself because of his violation (Hubbard, 2006). It was also the first time that one called it a crime, namely the crime of Laius (Carter, 2006). This term is used today as one pertaining to male rape. This is the first depiction of rape as a negative thing. In the early states, mothers were being trapped into a situation wherein they have to stay in limited areas of their homes and stay with other females. This is called gynarchy. Also, women and children were separated from the mens quarters. Thus, men use young boys for sexual intercourse preferably rather than their wives (Xenophon, cited in deMause, no date). Historians argue that in early states, matriarchy is the prevailing view. The state is governed by women. This is why at that time maternal incest was widely spread and common (deMause, n.d.). According to historians, child rape in early states is called love ,or pedophelia translated as love of children, or justifying it as an instance of gay rights that children are not minors (deMause, n.d.). Furthermore, the children are being blamed for being raped. Early scholars, especially Greek scholars believe that children are lonely and needing sex, seductive, and as routinely fellating older men [but] not abused despite ingesting their elders semen but ritually initiated into manhood. (Rousseau, 2007). Also, It was reported that in many early states, boys would be dressed as girls by their mothers and they will work as prostitutes to be raped by priests during religious rituals (Spencer, 1996). Men could pick up boys to be raped at any barbershop, in any boy brothel, at the exit of any of the Roman games (McMullen, 1990 cited by deMause, n.d.). Men regularly went into streets with scissors to make a hole in the trousers of the boy and a small pillow to put in the boys mouth if he should scream. (Schild, 1997). Furthermore, Physicians were reportedly expected to provide lubricants for the anal penetration of boys and also treat the rectal tears that results from being raped (deMause, n.d.). According to Plutarch, boys should think of rape not as a pleasure, but as a duty (Cantarella, 2002, cited by deMause, n.d.). Moreover, in ancient Babylon and Hebrew cultures, raped women are either thrown into the river o r are stoned to death in the cities (Brownmiller, cited by deMause, n.d.). It was also reported that in the early Roman Empire, the castration of boys was a big business used for raping by the aristocracy and by priests (Rousselle, 2009 cited by deMause, n.d.). In the time of the Nazis, rape was used as a political tool in war to produce fear torture, and social control in the states. Examples are the Serbian rape camps, comfort girls in Japan, use of inmates for prostitution in Nazi concentration camps in WWII, mass rapes of Bengali women during the Pakistani/Bengali war, rapes of school girls in Kenya, ass rapes of women by armed forces in Somalia and Guatemala (A History of Sexual Assault, 2009: p. 1). These are facts that are very overwhelming if one thinks of the freedom of people today. These myths, actions and beliefs are very brute and terrifying. In recent years, rape and other forms of sexual assault is associated with harm for a male perpetrator who is related to the female victim. This means that if the rape victim is married, the crime is against her husband; also, if the victim is unmarried, the crime is against her father. Women were treated as property of men. They had no rights in legal and social definitions of rape. It was only in the 60s that the women started to participate and given a chance to voice their opinions and beliefs womens movements (A History of Sexual Assault, 2009: p. 1).Today, rape is considered as a crime punishable by law. Although there are some countries are not very strict regarding their policies and laws such as in India or in Africa. Rape is defined as forced, unwanted sexual assault or sexual intercourse. Furthermore, it was argued that the reason behind the reformation and redefinition of rape, sexual assault, etc. was the feminist movements. Rape is about possession, power, and control (A History of Sexual Assault, 2009: p. 1). In the history of rape, several definitions and sanctions were very poor. Examples are: Rape was defined as forced sexual intercourse only, penile/vagina. If the victim does not acquire injuries, the case will not be prosecuted. All states do not acknowledge marital rape and date rape as serious rape cases. Males are only treated as suspects and cannot be victims, while females are victims only and not perpetrators. Only stranger rape was acknowledged and if no physical injuries or harm were sustained, it will not be acknowledged (A History of Sexual Assault, 2009: p. 2). Only in 2002 was there a big leap in the rape law definitions and sanctions. There are many different reasons behind these rapes. Study of why and where is the point of doing this criminal act will strengthen understanding about what rape is and why it is a crime. According to the GMU Sexual Assault Services (GMU-SAS), approximately 95 percent of reported rapes are committed by men. However, most men do not commit these kinds of crime (The Offender, 2009). GMU-SAS argued that there are many different factors that affect or boost the development of this deviant behavior. Some of these factors are: (One) the offender thinks of the victim as an object that can be manipulated and violated according to his will. (Two) The inability to empathize to other people had resulted from physical, sexual or emotional abuse from the past. According to a study, 70 percent of male sexual assault offenders were sexually and physically abused in their childhood (Lisak, 2002, cited in The Offender, 2009). (Three) The perpetrator believes that sex is equal to violence; that men sh ould be dominant and aggressive, and that women should protect themselves until they take that virtue with the use of force. (Four) The perpetrator strongly holds on the beliefs of dating ritual stereotypes. An example is that sex is a game. The more you have it, whether by force or not, the more points you have. (Five) The perpetrator accepts violence as an act of dealing with conflicts. (Six) Excessive drinking of alcohol may affect the violent attitude of some men (The Offender, 2009). These are just some of the causes that may affect the development of a sexual assault perpetrator. Rape has a wide variety of cases. Rape, in the simplest categorization, is divided into two fields. One, non-stranger rape and two, stranger rape. These are two entirely different stories. Non-traditional rape is defined to be rape wherein the perpetrator is an acquaintance, a friend, a neighbor or even a spouse (Acquaintance or Non-Stranger Rape, 2009). According to the GMU Sexual Assault Services (GMU-SAS), a non-stranger rape is not considered to be a true sexual assault (2009). Most of the time, society today tends to blame the victim for these types of rape. However, GMU-SAS argued that the no woman is exempt from being raped. Any woman can be raped. Also, rape is a very democratic form of violence. Furthermore, rape attacks are 80% wholly and partially planned (Acquaintance or Non-Stranger Rape, 2009: p. 1). Also, studies show that 60-80% of all sexual assaults were done by someone who knows the victims. Also, men can be sexually assaulted too. Most of the male rape victims wer e abused in their childhood or in their teens. Rape is not dependent on the weapon used, gender, virginity and other matters. Rape is about unwanted, forced actions toward a victim (Acquaintance or Non-Stranger Rape, 2009: p. 2). Marital rape is another form of a non-traditional rape. In 1984, marital rapes were not prosecuted in Virginia. It was only in 1986 that a reformation of the law allows prosecution of marital rapes. In recent studies, one out of seven women is being sexually assaulted by their husbands (Marital Rape, 2009).In other words, marriages are not an exemption when it comes to rape. Gang rape can be another form of a non-traditional rape if the sexual perpetrators are known or have a relationship to the victim. This happens when two or more offenders sexually assault a victim. GMU-SAS described gang rape as very different from the traditional acquaintance rape in the sense that men who engage in rapes like these are the ones who cannot commit an individual rape. Fu rthermore, it was said that gang rape is a less perverted type of rape that usually associates the thing as a rite of passage or a proof of masculinity (Helen, cited by GMU-SAS, 2009).These types of rape involve an acquaintance or an existing relationship. Stranger rapes are the crimes that involve total strangers as perpetrators. A report from the Dublin Rape Crisis Centre (DRCC) show that stranger rape is increasing. More than half of all the rape victims are attacked by total complete strangers. The DRCC is alarmed and shocked because of this growing trend. Also, according to their statistics, out of the 51 percent of stranger rape victims, 38 percent said that they were also physically and psychologically abused (cited by Sherry, 2009). According to the Rape, Abuse, Incest National Network (RAINN), stranger rape has three major categories: Blitz sexual assault, Contact sexual assault, and Home invasion sexual assault. Blitz sexual assault is the type of sexual assault that happens rapidly and brutally. The perpetrator is a total stranger and this usually happens at night in public places. Contact sexual assault involves the sudden contact of a stranger perpetrator with the victim and tries to gain his confidence and trust before as saulting the victim. Usually, the perpetrators pick their victims from bars and restaurants; sexual coercion also is used for the initiation of sexual assault. Home invasion sexual assault is the situation wherein the stranger perpetrator breaks in the home of the victim and assaults the victim (Stranger Rape, 2009). Stranger rape is reported to happen in a lesser commonly and less possible to be repeated. Furthermore, it has been an argument that stranger rape is associated with violence and that non-stranger rapes have less violence when it comes to their nature (Shanahan, 1999). This is a rather unequal judgment on the true nature of rape as an offence. Rape is rape. Rape is a crime. It does not matter whether there was violence or less violence. It was further explained that a woman is raped whenever she has sex and feels violated (MacKinnon, cited by Shanahan, 1999). To further explain and evaluate the case of stranger rape, comparison of the harms and effects of both rapes will be discussed. There are many effects of being raped. These are very serious consequences that have lifetime effects on the victim. It was reported that stranger rape has far more complicated and devastating effects for the victim. Stranger rape often results in unwanted pregnancies and sexually transmitted diseases which include HIV and AIDS. Furthermore, violent stranger rape can cause bruises and cuts to the victim, also the absence of condoms that make a larger probability of sexually transmitted diseases (Best, 2005). Raped women are traumatized and stigmatized. In some cultures, different kinds of punishments are given to raped women. Raped women are either abandoned, divorced or be declared as unmarriageable (Best, 2005). Furthermore, many raped women become impregnated; contract sexually transmitted infections, and suffers gynecological injuries that require recons tructive surgery (Best, 2005). These consequences are far more devastating that one can ever imagined. The mental, emotional, physical and psychological tortures for these women are worst. The effects and harms of non-stranger rape are also comparable to the effects of stranger rape. It is not right to say that non-stranger rape is not violent. There is also violence in what they do. Research reports that non-stranger rape or acquaintance rape survivors suffer from depression, anxiety, complications in subsequent relationships, and difficulty of attaining maximum level of sexual satisfaction (Koss Dinero, cited by Curtis, 1997). Also, it is also argued that one of the most serious effects of stranger rape is Posttraumatic Stress Disorder (PTSD). Furthermore, rape and other sexual assaults is the most common cause of PTSD (McFarlane De Girolamo, in van der Kolk, McFarlane, Weisaeth cited by Curtis, 1997). Other effects are miscarriage, stillbirth, infertility, suicidal tendencies, and long-term sexual dysfunction. The effects and harms are just the same as with the stranger rape. There should be no distinction between stranger and non-stranger rape. They are both cri mes. The punishment and law for rape cases will be discussed to further the understanding of the stand and status of both stranger rape and non-stranger rape in representing the true nature of rape as an offence. The legal aspects and comparisons of the traditional sense for both cases is the most effective way in evaluating the extent of which both represents the nature of rape. The legal aspects of traditional rape has five major elements: penetration, force and resistance, non-consent, absence of a spousal relationship (the marital exemption), and a culpable state of mind (mens rea). Only four of the major elements are connected to stranger rape. (1) Sexual intercourse is a requirement for an act to be called rape. Penetration is the, even slightest, insertion of the penis into the vagina. It does not count as rape if the penetration is done with the use of object or the penetration is not done in the vagina. Furthermore, ejaculation is not required. This implies that traditional view of rape is gender-specific that only women can be raped. Today, modern views about rape towards penetration is that penetration is about violence and violation against the morale, physical integrity and sexual autonomy of a person man, woman or child. This means that penetration is forcible penetration of any object to any part of the body of the victim (Rape: Legal Aspects Forcible Rape: Elements of the Offense, n.d.). (2) To be qualified as a rape case, the perpetrator must have exerted force and that the victim has no consent about it. Traditionally, other cases wherein it is considered as forcible rape even without the physical compulsion, are those in which the woman was unconscious, was mentally incompetent, or gave her consent under certain false pretenses. Traditionally, a perpetrator who tricked a victim about false pretenses about marriage and the likes are not to be considered as rape. However, he may be trialed for seduction. Also, rape by submission must be justified by the application of force (Rape: Legal Aspects Forcible Rape: Elements of the Offense, n.d.). It was argued that the justification of force is not self-evident because most people think that sex without consent, even with or without force, is to be called rape (Rape: Legal Aspects Forcible Rape: Elements of the Offense, n.d.). This implies that you if the victim is not forced, there is no rape. That rape is traditionall y interpreted as an act of violence the more force, the more violent, the more credible the rape. Today, several states punish all cases of sexual intercourse without consent and treat force merely as a factor that aggravates the severity of the offense. But there are still people who believe that force is an essential element of rape (Rape: Legal Aspects Forcible Rape: Elements of the Offense, n.d.). (3) Non-consent is another issue of the traditional view of rape. A sexual assault is not considered as rape if the victim consented or did not resist. The act must be against his will. The major drawback of this element is that it tended to encourage a focus on the complainants state of mind, and evidence of her prior sexual experience was often used to insinuate that she wanted to have sex (or deserved whatever treatment she received). Furthermore, the meaning of consent is not clear. Some argued that answering no does not actually mean no. Such difficulties arise that is why, today, some laws provide the elimination of the element of unwillingness or non-consent (Rape: Legal Aspects Forcible Rape: Elements of the Offense, n.d.). (4) Mens Rea is another traditional view of rape. It means that the defendant has a culpable state of mind. This means that the perpetrator must have actual knowledge of what he has done and that he is in a proper state of mind. Furthermore, conviction should require actual awareness of wrongdoing. This implies that the conviction should require proof of criminal negligence (a gross departure from the level of care reasonably expected) and the penalty imposed should be lower than that applied to intentional misconduct. (Rape: Legal Aspects Forcible Rape: Elements of the Offense, n.d.). Clearly, from these traditional views on stranger rape, all of the four traditional elements: penetration, force and resistance, non-consent, and a culpable state of mind (mens rea) do not represent fairly and accurately the true nature of rape as an offence. It is an offence if the person is violated physically, emotionally, mentally, and psychologically. Again, Rape is rape. Rape is a crime. It does not matter who, what, where, when and how. Rape is about the destruction of ones sexual autonomy, of ones pride and dignity, of ones health.

Essay --

Kayla McCarthy Period 2 History Mrs.Dowd 1/6/14 Disagreements Between the North and South Secession between the North and the South was very different. The secession led to the Confederate States of the United States. The Confederate States Constitution closely resembled the Constitution of the United States and it states that it, â€Å"protected and recognized slavery.† The southerners feared that if they did not succeed that an end to their entire way of life was at hand because they felt that they needed to preserve slavery. Succeeding seemed to be the only way of saving slavery. Many other southern states began to succeed when they learned that slavery was going to be removed in the South. For example,Compromise of 1850, Compromise of 1820, the Dred Scott Decision, Raid at Harpers Ferry, â…â€" Compromise, Kansas Nebraska Act, and Missouri Compromise were some of the compromises and decisions made at the time to deal with disagreements many of these people had over slavery(Batten). Slavery was relied on very much in the south because the slaves were their way of making money. The sl...

Forecasting †Simple Linear Regression Applications

STATISTICS FOR MGT DECISIONS FINAL EXAMINATION Forecasting – Simple Linear Regression Applications Interpretation and Use of Computer Output (Results) NAME SECTION A – REGRESSION ANALYSIS AND FORECASTING 1) The management of an international hotel chain is in the process of evaluating the possible sites for a new unit on a beach resort. As part of the analysis, the management is interested in evaluating the relationship between the distance of a hotel from the beach and the hotel’s average occupancy rate for the season. A sample of 14 existing hotels in the area is chosen, and each hotel reports its average occupancy rate.The management records the hotel’s distance (in miles) from the beach. The following set of data is obtained: Distance (miles)0. 10. 10. 20. 30. 40. 40. 50. 60. 7 Occupancy (%)929596908996908385 Continue Distance (miles)0. 70. 80. 80. 90. 9 Occupancy (%)8078767275 Use the computer output to respond to the following questions: a) A simple linear regression was ran with the occupancy rate as the dependent (explained) variable and distance from the beach as the independent (explaining) variable Occpnc=b[pic]+b[pic](Distncy) What is the estimated regression equation?The regression model is: Occpnc = b[pic] + b[pic](Distncy) The estimated regression equation is: OCCUPNC = 99. 61444 – 26. 703 DISTNCY b) Interpret the meaning behind the values you get for both coefficients b[pic] and b[pic]. b[pic]=99. 61444, represent the y-intercept as well as the starting figure for the distance coverage. This is the amount of distance in miles that the hotel is from a beach. b[pic] = 26. 703, represents the percentage of occupancy a hotel has depending on the distance of the hotel from a beach. c) What sort of relationship exists between average hotel occupancy rate and the hotel’s distance from the beach?Does this relationship make sense to you? Why or why not? Both distance and occupancy have a direct relationship. This is true because closer the hotel is to the beach, the higher the chance that the hotel’s occupancy will be greater. If a person is going to stay at a hotel, chances are they are on vacation. People on vacation love to spend time on a beach for relaxation purposes, so it would only make sense that a hotel that is closer to the beach will have a higher occupancy rate. d) Interpret the R-Square value in your computer output R-Squared = 0. 848195 = 84. 8195 ) Predict the expected occupancy rate for a hotel that is (i) one mile from the beach in that area, (ii) one and half miles from the beach. i. OCCUPNC = 99. 61444 – 26. 703 (1) = 99. 61444 – 26. 703 = 72. 911 ii. OCCUPNC = 99. 61444 – 26. 703 (1. 5) = 99. 61444 – 40. 055 = 59. 559 f) In your mind, what other variables contribute positively or negatively to hotel occupancy besides distance from the beach? Other variables that contribute positively or negatively to hotel occupancy besides distance fr om the beach include the distance of restaurants, shopping centers, and airport from the hotel.The closer theses variables are to the hotel the chances the occupancy rate will be higher. In addition, other variables may include what type of amenities that are offered by the hotel, customer service, and rating of the hotel. g) At a level of significance, ? = 0. 01 or 1 percent test the following pair of hypotheses: H[pic]: b[pic]= 0 H[pic]: b[pic]? 0 On the model: Occpnc=b[pic]+b[pic](Distncy) What is your conclusion and why that particular conclusion? COMPUTER OUTPUT – PART 1 INTERNATIONAL HOTEL REGRESSION FUNCTION & ANOVA FOR OCCPNCY OCCPNCY = 99. 61444 – 26. 703 DISTANCER-Squared = 0. 848195 Adjusted R-Squared = 0. 835545 Standard error of estimate = 3. 339362 Number of cases used = 14 Analysis of Variance p-value Source SS df MS F Value Sig Prob Regression 747. 68 1 747. 68390 67. 04880 0. 000002 Residual 133. 82 12 11. 15134 Total 881. 50 13 COMPUTER OUTPUT  œ PART 1 INTERNATIONAL HOTEL REGRESSION COEFFICIENTS FOR OCCPNCY Two-Sided p-value Variable Coefficient Std Error t Value Sig Prob Constant 99. 61444 1. 4107 51. 31933 0. 000000 DISTANCE -26. 70300 3. 26110 -8. 18833 0. 000002 * Standard error of estimate = 3. 339362 Durbin-Watson statistic = 1. 324282 MULTIPLE REGRESSION 2) You want to find out factors that explain an individual’s weekly savings. You are given a set of data below: Sampled WeeklyHouseFoodEntertain/Weekly IndividualIncomeRentExpenseExpenseSavings Case 1$25085952520 Case 2$1907590100 Case 3$4201401204050 Case 4$340120130040 Case 5$2801101003015 Case 6$310801252525 Case 7$5201501405580 Case 8$440175155450 Case 9$36090852095 Case 10$3851051353530Case 11$2058010505 Case 12$26565951515 Case 13$19550801020 Case 14$25090100250 Case 15$4801401604545 A multiple regression was ran with WEEKLY SAVINGS as the DEPENDENT VARIABLE and the rest as the INDEPENDENT VARIABLES. SAVINGS = b[pic][pic]+ b[pic]INCOME + b[pic]RENT + b [pic]FOOD + b[pic]ENTERT a) What is the estimated multiple regression equation? SAVINGS = 23. 14156 + 0. 591446 INCOME – 0. 341793 RENT – 1. 119734 FOOD – 0. 907868 ENTERT b) What relationship exists between (i) SAVINGS and INCOME? , SAVINGS and RENT? , SAVINGS and FOOD expense, SAVINGS and ENTERTAINMENT expense?There are no direct relationship between saving and income, savings and rent, savings and food expense, and savings and entertainment expense. c) Which of the independent (explaining) variables are (is) significant in the multiple regression and which ones are (is) not significant (use ? = 0. 05 level of significance). Are the results in line with Maslow hierarchy of needs? Explain. COMPUTER OUTPUT PART I WEEKLY SAVINGS REGRESSION FUNCTION & ANOVA FOR SAVINGS SAVINGS = 23. 14156 + 0. 591446 INCOME – 0. 341793 RENT – 1. 119734 FOOD – 0. 907868 ENTERT R-Squared = 0. 917562 Adjusted R-Squared = 0. 70454 Standard error of estimate = 10. 9635 Number of cases used = 12 Analysis of Variance p-value Source SS df MS F Value Sig Prob Regression 9364. 86 4 2341. 21 19. 47795 0. 000677 Residual 841. 39 7 120. 198 Total 10206. 250 11 COMPUTER OUTPUT PART II WEEKLY SAVINGS REGRESSION COEFFICIENTS FOR SAVINGS Two-Sidedp-value Variable Coefficient Std Error t Value Sig Prob Constant 23. 14156 18. 34071 1. 26176 0. 247451 INCOME 0. 59145 0. 07388 8. 00526 0. 000091 RENT -0. 4179 0. 19849 -1. 72199 0. 128743 * FOOD -1. 11973 0. 24633 -4. 54565 0. 002650 ENTERT -0. 90787 0. 32460 -2. 79689 0. 026643 * indicates that the variable is marked for leaving Standard error of estimate = 10. 9635 Durbin-Watson statistic = 1. 683103 3) REGRESSION ANALYSIS A business person is trying to estimate the relationship between the price of good X and the sales of good Y of certain groups of staples. Tests in similar cities throughout the country have yielded the data below: PRICE (X)SALES (Y) $2010,300 $259,100 $308,200 $356,500 $405,100 $502,300A simple linear regression of a model SALES(Y) = b[pic] + b[pic]PRICE(X) Was run and the computer output is shown below: PRICE OF X / SALES OF Y REGRESSION FUNCTION & ANOVA FOR SALES(Y) SALES(Y) = 15907. 14 – 269. 7143 PRICE(X) R-Squared = 0. 994999 Adjusted R-Squared = 0. 993749 Standard error of estimate = 230. 9143 Number of cases used = 6 Analysis of Variance p-value Source SS df MS F Value Sig Prob Regression 4. 24350E+07 1 4. 24350E+07 795. 83480 0. 000009 Residual 213285. 70000 4 53321. 43000 Total 4. 26483E+07 5PRICE OF X / SALES OF Y REGRESSION COEFFICIENTS FOR SALES(Y) Two-Sidedp-value Variable Coefficient Std Error t Value Sig Prob Constant 15907. 14000 332. 34250 47. 86370 0. 000001 PRICE(X) -269. 71430 9. 56076 -28. 21054 0. 000009 * Standard error of estimate = 230. 9143 Durbin-Watson statistic = 1. 687953 QUESTIONS a) What is the estimated equation of the model: SALES(Y) = b[pic] + b[pic]PRICE(X)? SALES(Y) = 15907. 14 – 269. 7143 PRICE(X) b) What sort of relationship exists between SALES OF Y and the PRICE OF X? Does this relationship make sense? Why or why not?There is a direct relationship between Sales of Y and the Price of X. The lower the price the higher are the sales. This makes sense because if the price is lower, a person will purchase more items. c) What can you say about GOOD Y and GOOD X (a good can be an item, a commodity, etc. ). Name a pair of good X and good y that can display this kind of relationship. Suppose the price of candy is $0. 50/lb, the sales of the candy versus the same type of candy that is $0. 80/lb would yield more sales because of the price. The price of the candy directly affects sales in this instance because a person would buy more candy at $0. 0/lb versus $0. 80/lb. 4) REGRESSION ANALYSIS A business person is trying to estimate the relationship between the price of good X and the sales of good Z of certain groups of staples. Tests in similar cities throughout the country have yielded the data belo w: PRICE (X)SALES (Z) $153300 $203900 $254750 $305500 $406550 $507250 A simple linear regression of a model SALES (Z) = b[pic] + b[pic]PRICE(X) Was run and the computer output is shown below: PRICE OF X / SALES OF Z REGRESSION FUNCTION & ANOVA FOR SALES(Y) SALES(Z) = 1740. 686 + 115. 5882 PRICE(X) R-Squared = 0. 977573 Adjusted R-Squared = 0. 71966 Standard error of estimate = 255. 2152 Number of cases used = 6 Analysis of Variance p-value Source SS df MS F Value Sig Prob Regression 1. 13565E+07 1 1. 13565E+07 174. 35450 0. 000190 Residual 260539. 20000 4 65134. 80000 Total 1. 16171E+07 5 PRICE OF X / SALES OF Z REGRESSION COEFFICIENTS FOR SALES(Z) p-value Variable Coefficient Std Error t Value Sig Prob Constant 1740. 68600 282. 52800 6. 16111 0. 003522 PRICE(X) 115. 58820 8. 75381 13. 20434 0. 000190 *Standard error of estimate = 255. 2152 Durbin-Watson statistic = 1. 240299 QUESTIONS a) What is the estimated equation of the model: SALES(Z) = b[pic] + b[pic]PRICE(X)? SALES (Z) = 17 40. 686 + 115. 5882 PRICE(X) b) What sort of relationship exists between SALES OF Z and the PRICE OF X? Does this relationship make sense? Why or why not? There is a direct relationship between Sales of Y and the Price of X. The higher the price the higher are the sales. This makes sense as it relates to supply and demand. The higher the demand and for the product and unavailability of the product, the price will go up even though sales may he same due to the price increase the sales amount will be higher. c) What can you say about GOOD Z and GOOD X (a good can be an item, a commodity, etc. ). Give an example of good X and good Z that can display this kind of relationship A prime example that displays this kind of relationship is gas. The price of gas has been going up for sometime now. The demand for it is high, but the supply of is low. Therefore, even though the amount of sales may stay constant, the dollar amount will be higher because the price is higher. Chi-Squared Test #1M&M , makers of Chocolate Candies, conducted a national poll in which more than ten million people indicated their preference for a new color. The tally of this poll resulted in the replacement of tan-colored M&Ms with a new blue color. In the brochure â€Å"Colors,† made available by M&MS Consumer Affairs, the distribution of colors for the plain candies is as follows: BROWNYELLOWREDORANGEGREENBLUE 30%20%20%10%10%10% In a follow-up study two years later, samples of 1-pound bags were used to determine whether the reported percentages were still valid. The following results were obtained (observed) for one sample of 506 plain candiesBROWNYELLOWREDORANGEGREENBLUE 17713579413638 Use a level of significance ( = 0. 05 to determine whether these data support the percentages reported by the company Hint: To obtain the Expected Number of multiply the sample value (506) by each color’s probability, i. e. , E = BROWNYELLOWREDORANGEGREENBLUE 30% (506)20%(506)20%(506)10%(506)10%(506)1 0%(506) Then compute the Chi-Squared. H[pic]: f[pic], f[pic], f[pic], f[pic], f[pic], f[pic] hold previous year’s patterns or percentages H[pic]: At least one frequency differs from the previous year’s pattern or percentages E = 506/6 = 84. 33 [pic]=(177 –84. 33)[pic]/84. 33+(135 – 84. 33)[pic]/84. 33 + (79 – 84. 33)[pic]/84. 33+(41 – 84. 33)[pic]/84. 33)+(36 – 84. 33)[pic]/84. 33+(38 – 84. 33)[pic]/84. 33) ([pic]=101. 937 + 30. 49217 + 0. 333215 + 22. 24069 + 27. 67367 + 25. 4293 ([pic]=208. 106. This is the computed ([pic]-value. ( = 0. 05 d. f. = 6 – 1 = 5. Go to ([pic]-tables at ( = 0. 05, and d. f. = 5, you will get CRITICAL ([pic]-value = 11. 070. Since Computed ([pic]-value is greater than Critical ([pic]-value REJECT NULL H[pic]:P[pic] = P[pic] = P[pic] = P[pic] = P[pic] ALTERNATIVE H[pic]: At least one P is different is correct Forecasting – Simple Linear Regression Applications STATISTICS FOR MGT DECISIONS FINAL EXAMINATION Forecasting – Simple Linear Regression Applications Interpretation and Use of Computer Output (Results) NAME SECTION A – REGRESSION ANALYSIS AND FORECASTING 1) The management of an international hotel chain is in the process of evaluating the possible sites for a new unit on a beach resort. As part of the analysis, the management is interested in evaluating the relationship between the distance of a hotel from the beach and the hotel’s average occupancy rate for the season. A sample of 14 existing hotels in the area is chosen, and each hotel reports its average occupancy rate.The management records the hotel’s distance (in miles) from the beach. The following set of data is obtained: Distance (miles)0. 10. 10. 20. 30. 40. 40. 50. 60. 7 Occupancy (%)929596908996908385 Continue Distance (miles)0. 70. 80. 80. 90. 9 Occupancy (%)8078767275 Use the computer output to respond to the following questions: a) A simple linear regression was ran with the occupancy rate as the dependent (explained) variable and distance from the beach as the independent (explaining) variable Occpnc=b[pic]+b[pic](Distncy) What is the estimated regression equation?The regression model is: Occpnc = b[pic] + b[pic](Distncy) The estimated regression equation is: OCCUPNC = 99. 61444 – 26. 703 DISTNCY b) Interpret the meaning behind the values you get for both coefficients b[pic] and b[pic]. b[pic]=99. 61444, represent the y-intercept as well as the starting figure for the distance coverage. This is the amount of distance in miles that the hotel is from a beach. b[pic] = 26. 703, represents the percentage of occupancy a hotel has depending on the distance of the hotel from a beach. c) What sort of relationship exists between average hotel occupancy rate and the hotel’s distance from the beach?Does this relationship make sense to you? Why or why not? Both distance and occupancy have a direct relationship. This is true because closer the hotel is to the beach, the higher the chance that the hotel’s occupancy will be greater. If a person is going to stay at a hotel, chances are they are on vacation. People on vacation love to spend time on a beach for relaxation purposes, so it would only make sense that a hotel that is closer to the beach will have a higher occupancy rate. d) Interpret the R-Square value in your computer output R-Squared = 0. 848195 = 84. 8195 ) Predict the expected occupancy rate for a hotel that is (i) one mile from the beach in that area, (ii) one and half miles from the beach. i. OCCUPNC = 99. 61444 – 26. 703 (1) = 99. 61444 – 26. 703 = 72. 911 ii. OCCUPNC = 99. 61444 – 26. 703 (1. 5) = 99. 61444 – 40. 055 = 59. 559 f) In your mind, what other variables contribute positively or negatively to hotel occupancy besides distance from the beach? Other variables that contribute positively or negatively to hotel occupancy besides distance fr om the beach include the distance of restaurants, shopping centers, and airport from the hotel.The closer theses variables are to the hotel the chances the occupancy rate will be higher. In addition, other variables may include what type of amenities that are offered by the hotel, customer service, and rating of the hotel. g) At a level of significance, ? = 0. 01 or 1 percent test the following pair of hypotheses: H[pic]: b[pic]= 0 H[pic]: b[pic]? 0 On the model: Occpnc=b[pic]+b[pic](Distncy) What is your conclusion and why that particular conclusion? COMPUTER OUTPUT – PART 1 INTERNATIONAL HOTEL REGRESSION FUNCTION & ANOVA FOR OCCPNCY OCCPNCY = 99. 61444 – 26. 703 DISTANCER-Squared = 0. 848195 Adjusted R-Squared = 0. 835545 Standard error of estimate = 3. 339362 Number of cases used = 14 Analysis of Variance p-value Source SS df MS F Value Sig Prob Regression 747. 68 1 747. 68390 67. 04880 0. 000002 Residual 133. 82 12 11. 15134 Total 881. 50 13 COMPUTER OUTPUT  œ PART 1 INTERNATIONAL HOTEL REGRESSION COEFFICIENTS FOR OCCPNCY Two-Sided p-value Variable Coefficient Std Error t Value Sig Prob Constant 99. 61444 1. 4107 51. 31933 0. 000000 DISTANCE -26. 70300 3. 26110 -8. 18833 0. 000002 * Standard error of estimate = 3. 339362 Durbin-Watson statistic = 1. 324282 MULTIPLE REGRESSION 2) You want to find out factors that explain an individual’s weekly savings. You are given a set of data below: Sampled WeeklyHouseFoodEntertain/Weekly IndividualIncomeRentExpenseExpenseSavings Case 1$25085952520 Case 2$1907590100 Case 3$4201401204050 Case 4$340120130040 Case 5$2801101003015 Case 6$310801252525 Case 7$5201501405580 Case 8$440175155450 Case 9$36090852095 Case 10$3851051353530Case 11$2058010505 Case 12$26565951515 Case 13$19550801020 Case 14$25090100250 Case 15$4801401604545 A multiple regression was ran with WEEKLY SAVINGS as the DEPENDENT VARIABLE and the rest as the INDEPENDENT VARIABLES. SAVINGS = b[pic][pic]+ b[pic]INCOME + b[pic]RENT + b [pic]FOOD + b[pic]ENTERT a) What is the estimated multiple regression equation? SAVINGS = 23. 14156 + 0. 591446 INCOME – 0. 341793 RENT – 1. 119734 FOOD – 0. 907868 ENTERT b) What relationship exists between (i) SAVINGS and INCOME? , SAVINGS and RENT? , SAVINGS and FOOD expense, SAVINGS and ENTERTAINMENT expense?There are no direct relationship between saving and income, savings and rent, savings and food expense, and savings and entertainment expense. c) Which of the independent (explaining) variables are (is) significant in the multiple regression and which ones are (is) not significant (use ? = 0. 05 level of significance). Are the results in line with Maslow hierarchy of needs? Explain. COMPUTER OUTPUT PART I WEEKLY SAVINGS REGRESSION FUNCTION & ANOVA FOR SAVINGS SAVINGS = 23. 14156 + 0. 591446 INCOME – 0. 341793 RENT – 1. 119734 FOOD – 0. 907868 ENTERT R-Squared = 0. 917562 Adjusted R-Squared = 0. 70454 Standard error of estimate = 10. 9635 Number of cases used = 12 Analysis of Variance p-value Source SS df MS F Value Sig Prob Regression 9364. 86 4 2341. 21 19. 47795 0. 000677 Residual 841. 39 7 120. 198 Total 10206. 250 11 COMPUTER OUTPUT PART II WEEKLY SAVINGS REGRESSION COEFFICIENTS FOR SAVINGS Two-Sidedp-value Variable Coefficient Std Error t Value Sig Prob Constant 23. 14156 18. 34071 1. 26176 0. 247451 INCOME 0. 59145 0. 07388 8. 00526 0. 000091 RENT -0. 4179 0. 19849 -1. 72199 0. 128743 * FOOD -1. 11973 0. 24633 -4. 54565 0. 002650 ENTERT -0. 90787 0. 32460 -2. 79689 0. 026643 * indicates that the variable is marked for leaving Standard error of estimate = 10. 9635 Durbin-Watson statistic = 1. 683103 3) REGRESSION ANALYSIS A business person is trying to estimate the relationship between the price of good X and the sales of good Y of certain groups of staples. Tests in similar cities throughout the country have yielded the data below: PRICE (X)SALES (Y) $2010,300 $259,100 $308,200 $356,500 $405,100 $502,300A simple linear regression of a model SALES(Y) = b[pic] + b[pic]PRICE(X) Was run and the computer output is shown below: PRICE OF X / SALES OF Y REGRESSION FUNCTION & ANOVA FOR SALES(Y) SALES(Y) = 15907. 14 – 269. 7143 PRICE(X) R-Squared = 0. 994999 Adjusted R-Squared = 0. 993749 Standard error of estimate = 230. 9143 Number of cases used = 6 Analysis of Variance p-value Source SS df MS F Value Sig Prob Regression 4. 24350E+07 1 4. 24350E+07 795. 83480 0. 000009 Residual 213285. 70000 4 53321. 43000 Total 4. 26483E+07 5PRICE OF X / SALES OF Y REGRESSION COEFFICIENTS FOR SALES(Y) Two-Sidedp-value Variable Coefficient Std Error t Value Sig Prob Constant 15907. 14000 332. 34250 47. 86370 0. 000001 PRICE(X) -269. 71430 9. 56076 -28. 21054 0. 000009 * Standard error of estimate = 230. 9143 Durbin-Watson statistic = 1. 687953 QUESTIONS a) What is the estimated equation of the model: SALES(Y) = b[pic] + b[pic]PRICE(X)? SALES(Y) = 15907. 14 – 269. 7143 PRICE(X) b) What sort of relationship exists between SALES OF Y and the PRICE OF X? Does this relationship make sense? Why or why not?There is a direct relationship between Sales of Y and the Price of X. The lower the price the higher are the sales. This makes sense because if the price is lower, a person will purchase more items. c) What can you say about GOOD Y and GOOD X (a good can be an item, a commodity, etc. ). Name a pair of good X and good y that can display this kind of relationship. Suppose the price of candy is $0. 50/lb, the sales of the candy versus the same type of candy that is $0. 80/lb would yield more sales because of the price. The price of the candy directly affects sales in this instance because a person would buy more candy at $0. 0/lb versus $0. 80/lb. 4) REGRESSION ANALYSIS A business person is trying to estimate the relationship between the price of good X and the sales of good Z of certain groups of staples. Tests in similar cities throughout the country have yielded the data belo w: PRICE (X)SALES (Z) $153300 $203900 $254750 $305500 $406550 $507250 A simple linear regression of a model SALES (Z) = b[pic] + b[pic]PRICE(X) Was run and the computer output is shown below: PRICE OF X / SALES OF Z REGRESSION FUNCTION & ANOVA FOR SALES(Y) SALES(Z) = 1740. 686 + 115. 5882 PRICE(X) R-Squared = 0. 977573 Adjusted R-Squared = 0. 71966 Standard error of estimate = 255. 2152 Number of cases used = 6 Analysis of Variance p-value Source SS df MS F Value Sig Prob Regression 1. 13565E+07 1 1. 13565E+07 174. 35450 0. 000190 Residual 260539. 20000 4 65134. 80000 Total 1. 16171E+07 5 PRICE OF X / SALES OF Z REGRESSION COEFFICIENTS FOR SALES(Z) p-value Variable Coefficient Std Error t Value Sig Prob Constant 1740. 68600 282. 52800 6. 16111 0. 003522 PRICE(X) 115. 58820 8. 75381 13. 20434 0. 000190 *Standard error of estimate = 255. 2152 Durbin-Watson statistic = 1. 240299 QUESTIONS a) What is the estimated equation of the model: SALES(Z) = b[pic] + b[pic]PRICE(X)? SALES (Z) = 17 40. 686 + 115. 5882 PRICE(X) b) What sort of relationship exists between SALES OF Z and the PRICE OF X? Does this relationship make sense? Why or why not? There is a direct relationship between Sales of Y and the Price of X. The higher the price the higher are the sales. This makes sense as it relates to supply and demand. The higher the demand and for the product and unavailability of the product, the price will go up even though sales may he same due to the price increase the sales amount will be higher. c) What can you say about GOOD Z and GOOD X (a good can be an item, a commodity, etc. ). Give an example of good X and good Z that can display this kind of relationship A prime example that displays this kind of relationship is gas. The price of gas has been going up for sometime now. The demand for it is high, but the supply of is low. Therefore, even though the amount of sales may stay constant, the dollar amount will be higher because the price is higher. Chi-Squared Test #1M&M , makers of Chocolate Candies, conducted a national poll in which more than ten million people indicated their preference for a new color. The tally of this poll resulted in the replacement of tan-colored M&Ms with a new blue color. In the brochure â€Å"Colors,† made available by M&MS Consumer Affairs, the distribution of colors for the plain candies is as follows: BROWNYELLOWREDORANGEGREENBLUE 30%20%20%10%10%10% In a follow-up study two years later, samples of 1-pound bags were used to determine whether the reported percentages were still valid. The following results were obtained (observed) for one sample of 506 plain candiesBROWNYELLOWREDORANGEGREENBLUE 17713579413638 Use a level of significance ( = 0. 05 to determine whether these data support the percentages reported by the company Hint: To obtain the Expected Number of multiply the sample value (506) by each color’s probability, i. e. , E = BROWNYELLOWREDORANGEGREENBLUE 30% (506)20%(506)20%(506)10%(506)10%(506)1 0%(506) Then compute the Chi-Squared. H[pic]: f[pic], f[pic], f[pic], f[pic], f[pic], f[pic] hold previous year’s patterns or percentages H[pic]: At least one frequency differs from the previous year’s pattern or percentages E = 506/6 = 84. 33 [pic]=(177 –84. 33)[pic]/84. 33+(135 – 84. 33)[pic]/84. 33 + (79 – 84. 33)[pic]/84. 33+(41 – 84. 33)[pic]/84. 33)+(36 – 84. 33)[pic]/84. 33+(38 – 84. 33)[pic]/84. 33) ([pic]=101. 937 + 30. 49217 + 0. 333215 + 22. 24069 + 27. 67367 + 25. 4293 ([pic]=208. 106. This is the computed ([pic]-value. ( = 0. 05 d. f. = 6 – 1 = 5. Go to ([pic]-tables at ( = 0. 05, and d. f. = 5, you will get CRITICAL ([pic]-value = 11. 070. Since Computed ([pic]-value is greater than Critical ([pic]-value REJECT NULL H[pic]:P[pic] = P[pic] = P[pic] = P[pic] = P[pic] ALTERNATIVE H[pic]: At least one P is different is correct

Organizational Behavior in the Nfl - 2865 Words

Organizational Behavior in the National Football League Katie Johnston MT3250 Organizational Behavior Dr. Carl Proehl February 4, 2013 Abstract This paper will explore how people within the National Football League (NFL) interact with each other to reach their goals as a team, and an organization as a whole. Sports teams are defined as two or more individuals who possess a common identity, have common goals and objectives, share a common fate, exhibit structured patterns of interaction and modes of communication, hold common perceptions about group structure, are personally and instrumentally interdependent, reciprocate interpersonal attraction and consider themselves to be a group (Group Dynamics, 2004). There are many people†¦show more content†¦There are a series of periods that teams go through in making their decisions. The first is the preparation period, where the coaches and players anticipate the actions the opponents intend to perform and the probability of the actions. This early stage process is the one where video observation is used, studying the opponent’s strengths, weaknesses, and styles of play. The next decision regards how the team (A) should react, or respond, to the actions of the opposing team (B). Timing and quality must be a factor into team A’s next move. If the opposing team (B) changes their plan of action that was anticipated by team A, quick modifications must be made to ensure a successful retaliation. The success of decision making within a team depends on different mechanisms operating simultaneously and in mutual interaction (Decision Making in Sport, 2004). Let’s look more in depth at the visual aspect of decision making. Visual information is critical for any team. The visual (spatial) learning system is when a person (i.e. athlete) prefers learning through images, colors, pictures and maps to gather information. Cueing and priming are key features in the sport realm that are integral in visual attention (Decision Making in Sports, 2004). When an athlete is confident of their opponent’s next move, theirShow MoreRelatedOrganizational Culture Of The Nfl1037 Words   |  5 PagesThe organizational culture of the NFL was a breeding ground for dysfunction. From the lack of strong ethics to leadership accountability to inconsistencies, the NFL has many challenges to overcome. The first remedy for the NFL’s woes would be an organizational change in values. This would mean a paradigm shift to an ethical organizational culture. It will be imperative to consider the team owners and players â€Å"Until new behaviors are rooted in social norms and shared values, they are subject toRead MoreNfl: Global Entry1500 Words   |  6 Pages The National Football League (NFL) is considered the strongest, most lucrative, and financially resilient professional sport globally. 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