Differentiate Between Operation System And Application Software Computer Science Essay

Differentiate Between Operation System And Application Software Computer Science Essay The most important program that is run on a computer. Every general-purpose computer must have an operating system to run other programs. The implementation of the operating system recognizes input from the keyboard, such as the basic task of sending the output to the screen display, recorded in the files and directories on the disk track, and control such as disk drives and printer peripherals. Network operating system abbreviated as NOS, operating system, including connecting to a local area network equipment, computers and special features. Some operating system, such as UNIX and the Mac operating system, has been networking the term network operating system-inch built-in feature, however, is generally reserved for software, network capabilities by adding the basic operating system. Novells Netware, Artisofts LANtastic, Microsoft windows Server and Windows NT is an example of an network operating system. The program or programs designed for end-users group. Software can be divided into two categories: system software and application software. From low-level system software programs, interact with the computer a very basic level. This includes the operating system, compiler, used to manage computer resources and utilities. Computer system refers to the computer and its devices. Equipment such as speakers, printers, keyboards, scanners and other peripheral devices are called, sometimes referred to as peripherals. Central processing unit (CPU) is considered to be computer. If no external device input and output of the computer (home computer) (such as monitors, printers, speakers, etc.) will not be able to do anything you feel useful.Read phonetically Define Question 1 Operating system is a software program and computer interface as user behaviour. This is a software package that allows the computer is functions. Operating system also the most important programs into the computer. Basic operating system running on the computer and allows other programs to run well. Operating system to complete all need to do a computer, such as recognized from the mouse or keyboard input, the basic things. It retains all of the documents which track on the computer. Allocation of resources to running, it can prevent unauthorized access to computer programs. A network operating system (NOS) is a computer operating systems main purpose is to support workstations, personal computers, and in some cases, the old pier is a local area network (LAN) connection. In addition, some multi-purpose operating system such as Windows NT and Digitals OpenVMS, and out of capacity, so that they can describe as a network operating system. Network operating system provides printer sharing, common file system and database sharing, application sharing, and to manage the network name of the directory, security and other internal networks. An application software are designed to perform specific functions, directly to the user or in some cases, another application, any plans. Application uses the computers operating system and other services supporting the project. Services and with the programmers writing application is called application program interface (API) to use other means of communication formal request procedure. Answer Question 1 Operating System Operating system to create a link between users and applications forms the core of the computer system. It is not in favor of the programs and hardware to simplify resource management. Let us look at different types of operating systems. Multi-tasking and Single-tasking Operating Systems When a program is allowed to run once, the system is divided into single-task operating system, and the operating system allows the case to perform multiple tasks at the same time, it is listed as a multitasking operating system. Multi-task can be divided into two categories, namely pre-emptive or cooperation. In the pre-emptive multitasking operating system and CPU time slice of a slot dedicated to each project. Class Unix operating systems such as Solaris and Linux support for pre-emptive multitasking. Cooperative multitasking is relying on each process, to allow time to define the way in the other processes. Prior to Microsoft Windows to Windows95 to support the cooperative multitasking. Window 7 As the Windows operating system, it will be the next version of Windows Vistas successor, the work of the name. Windows 7 is expected to be released in 2010. Windows 7 is expected to use less power more effective, not as a resource pig because more than Vista, and includes better synchronization with mobile devices and PC integration elements. Windows 7 is expected to include 32-bit and 64-bit versions and server versions, Windows Server 7. Mac OS X Mac OS X pronounced Oh Apple ES of ten, was in the Apple Macintosh computer using the current version of the operating system. If you happen to be pronounced Mac OS X, computer fans, and dedicated to Mac users will quickly correct you. Although the name may be a bit confusing, Mac OS X is an advanced, user-friendly operating system. Application Software Applications the ability to use the computer directly to the specific task. Application software can handle text, numbers and graphics. It can be in a certain software, such as word processing, spreadsheets, or playback of audio and video files form the focus of a single task. Database Software Database is a collection of data structure. Rely on computer databases to organize data, allowing users of the database, database software, database operations to achieve. Database software allows users to store and retrieve data in the database. Spreadsheet Software In Excel, Lotus 1-2-3 and Apple figures are some examples of spreadsheet software. Spreadsheet software allows users to perform calculations. They simulate a display, so that more cells grid paper form. Multimedia Software They allow users to create and play audio and video media. They are able to play the media files. Audio converter, player, burner, video encoder and decoder is a form of multimedia software. Examples of this type of software, including Real Player and Media Player. Simulation Software Simulation software is the best example of the scientific simulation and flight simulators. The plan is mainly used for research and entertainment. Simulation is to create a human, vehicle and traffic accident environment, the computer model to calculate the forces in the discrete time interval for each agent process. By Newtonian physics, the vehicle position and velocity updates, and human and display graphics. Computer animation software can plug the vehicle location, based on user input the coordinates and speed. The animation provides a similar event is a simulated graphical representation of a visual description, it is not an analytical tool. Computer simulation is a complex event, because the analysis of human and vehicle movement in the simulation is a physical programmable valuable tool. Driver behaviour, vehicle characteristics, and road conditions, the parameters can be easily assessed. Define Question 2 The computer is one of mankinds most brilliant invention. Computer technology, we can achieve efficient storage and data processing. We can employ other information storage capacity of computer memory of our brain. Because the computer, we have the ability to work up to the daily rate for important transactions, to achieve precision and accuracy of the output. On the computer a few years ago is a large room size, and must consume large amounts of electricity. However, as technology advances, computers have shrunk to the size of a small watch. Depending on the size of the processing power and computer, they have different types of classification. Let us look at the computer category. Answer Question 2 Supercomputers Highly computationally intensive tasks can be carried out effectively by means of supercomputers. Quantum physics, mechanics, weather forecasting, molecular theory is the best studied by means of supercomputers. Their well-designed parallel processing and the ability of the memory hierarchy to give the super computer, large-scale transaction processing capabilities. Minicomputers In size and processing capability, the minicomputer is between mainframe and PC. Minicomputer, also known as mid-range system or workstation. The term began to be generally 60 years in the 20th century to refer to the third generation of relatively small computers. They picked up it would be a refrigerator or two core technologies used in transistors and memory space required. 12-bit Digital Equipment Corporation PDP-8 minicomputer was the first successful minicomputer. Laptops Similar operations, desktop computers, notebook computers and mobile use small design. Running on a single laptop battery or external adapter, charges the computer battery. They enabled with a built-in keyboard, touchpad as a mouse and LCD display. Its portability and ability to use the battery as a power advantage for mobile users. Desktops The desktop to a single location. Parts of a desktop computer is easy to provide a relatively low cost. Power not as the key to the laptop. Desktop machine is widely used in the workplace and the family welcome for daily use. Microcomputers It with a microprocessor and a computer central processing unit is called micro-computer. They do not occupy the space up to the mainframe. When using the keyboard and mouse, giving the micro-computer can be called personal computers. Monitor, keyboard and other similar input and output devices, in the form of computer memory and memory to power supplies packaged in a miniature computer. These computers can be installed in the desk or table, and as a single user tasks the best choice. Analogy Computers These are almost extinct today. These figures are from a different computer because the computer can run multiple analog mathematical operations simultaneously. It uses math continuous variables, and using mechanical or electrical energy. Wearable Computers A record in the computer evolution step is to create wearable computers. These computers can be worn on the body and often in the behavioral modeling and human health research to use. Military and health professionals in their daily wearable computers, as part of such a study. When the users hand, the activities of the other senses, wearable computers is very helpful to track peoples actions. Wearable computers in operation because they never been opened and closed, and continue to interact with the user. Conclusion Recommendation In 2011 years, we can see the world have many place and build also using computer. Computer gives us a lot convenience, it can get us searching any for internet (e.g. movie, music, New, literature and knowledge) and the reason for sub-types of the computer because they want to meet the market demands. Computer system are many types of computer, outsides the computer have hardware and insides the computer have software. And the software have type of operation System, application Software and other. But the software installer want to step by step, because you dont following the step well be broke the computer. So I think the computer is very interesting. Appendix

Solutions Hmwk

ISDS-361AExercises 1. Mean, Median, Mode, Range, Variance & SD Panayiotis Skordi 1. A basketball player has the following points for seven games: 20, 25, 32, 18, 19, 22, 30 Compute the following measures of central location: a. mean b. median c. mode Answers a. Mean[pic] b. Median[pic] c. Mode There is no mode. 2. Consider the following population of measurements: 162, 152, 177, 157, 184, 176, 165, 181, 170, 163 a. compute the mean b. compute the median Answers a. Mean[pic] b. Median [pic] [pic] 3. The following data represent the number of children in a sample of 10 families from a certain community: , 2, 1, 1, 5, 3, 0, 1, 0, 2 a. compute the range b. compute the variance c. compute the standard deviation Answers a. Range [pic] b. Variance[pic] Remember that [pic] [pic][pic][pic][pic] 14 2. 14. 41 22 0. 10. 01 31-0. 90. 81 41-0. 90. 81 55 3. 19. 61 63 1. 11. 21 70-1. 93. 61 81-0. 90. 81 90-1. 93. 61 102 0. 10. 01 Total1924. 9 [pic] Method 2[pic] [pic][pic][pic] 1416 224 311 411 5525 639 700 811 900 1024 Total1961 [pic] This is the same answer – as we would expect. c. The standard deviation is [pic] 4. Consider the following population of measurements: 162, 152, 177, 157, 184, 176, 165, 181, 170, 163 a. ompute the standard deviation Answer [pic] Remember that [pic] [pic][pic][pic][pic] |1 |162 | |-6. 70 | |44. 89 | |2 |152 | |-16. 70 | |278. 89 | |3 |177 | |8. 30 | |68. 89 | |4 |157 | |-11. 70 | |136. 89 | |5 |184 | |15. 30 | |234. 09 | |6 |176 | |7. 30 | |53. 29 | |7 |165 | |-3. 0 | |13. 69 | |8 |181 | |12. 30 | |151. 29 | |9 |170 | |1. 30 | |1. 69 | |10 |163 | |-5. 70 | |32. 49 | | | | | | | | | | | | | | | |Total |1687. 0 | | | |1016. 10 | [pic] The standard deviation is the square root of the variance [pic] Method 2[pic] pic][pic][pic] |1 |162 | |26244 | |2 |152 | |23104 | |3 |177 | |31329 | |4 |157 | |24649 | |5 |184 | |33856 | |6 |176 | |30976 | |7 |165 | |27225 | |8 |181 | |32761 | |9 |170 | |28900 | |10 |163 | |26569 | | | | | | | | | | | | |1687 | |285613 | [pic] As before, the standard deviation is the square root of the variance pic] 5. Monthly rent data in dollars for a sample of one-bedroom apartments in a small town in Iowa are as follows: 220, 216, 220, 205, 210, 240, 195, 235, 204 and 205. a. compute the sample monthly average rent. b. compute the sample median. c. what is the mode? Answers a. Average [pic] [pic][pic] |1 |220 | |2 |216 | |3 |220 | |4 |205 | |5 |210 | |6 |240 | |7 |195 | |8 |235 | |9 |204 | |10 |205 | | | | | |2,150 | | | [pic] b. MEDIAN 195 204 205 205 210 216 220 220 235 240 [pic] c. MODE205 and 220 (bimodal) 6. A sample of 25 families was asked how many pets they owned. Their responses were summarized in the following table: |Number of Pets |0 |1 |2 |3 |4 |5 | |Number of Families |3 |10 |5 |4 |2 |1 | Determine the mean, median and the mode of the number of pets owned per family. ANSWERS a. MEAN[pic] [pic][pic][pic][pic] 0 |3 |0 | |1 |10 |10 | |2 |5 |10 | |3 |4 |12 | |4 |2 |8 | |5 |1 |5 | | | | | | |25 |45 | [pic] b. MEDIAN1 median is 13th observation. c. MODE 1 most families have 1 pet. 7.The following data represent the ages in years of a sample of 25 employees from a government department: 31,43,56,23,49,42,33,61,44,28,48,38,44,35,40,64,52,42,47,39,53,27,36,35 and 20. Construct a relative frequency distribution for the data, using five class intervals and the value 20 as the lower limit of the first class. |20 | | | |23 | | | |27 | | | |28 | |4 | |31 | | | |33 | | | |35 | | | 35 | | | |36 | | | |38 | | | |39 | |7 | |40 | | | |42 | | | |42 | | | |43 | | | |44 | | | |44 | | | |47 | | | |48 | | | |49 | |9 | |52 | | | 53 | | | |56 | |3 | |61 | | | |64 | |2 | |Class Limits |Frequency |Relative Frequency | | | | | |20 upto 30 |4 |0. 16 | |30 upto 40 |7 |0. 28 | |40 upto 50 |9 |0. 36 | |50 upto 60 |3 |0. 12 | |60 upto 70 |2 |0. 8 | | | | | | |25 |1. 00 | 8. How many hours a day do college students spend studying? That question was asked to 100 college students, and the data are p resented in the table below. Hours per DayFrequency 0-225 2-448 4-615 6-89 8-103 a. compute the range b. compute the average hours per day spent studying. c. compute the variance of the number of hours per day spent studying d. find the median e. find the mode Answers a. The range is 10-0 = 10 b. Average[pic] [pic][pic][pic][pic][pic] 1 |0-2 |25 |1 |25 | |2 |2-4 |48 |3 |144 | |3 |4-6 |15 |5 |75 | |4 |6-8 |9 |7 |63 | |5 |8-10 |3 |9 |27 | | | | | | | | | |100 | |334 | [pic] c. compute the variance of the number of hours per day spent studying [pic] note that [pic] [pic][pic][pic][pic][pic][pic][pic] |1 |0-2 |25 |1 |-2. 34 |5. 4756 |136. 89 | |2 |2-4 |48 |3 |-0. 34 |0. 1156 |5. 488 | |3 |4-6 |15 |5 |1. 66 |2. 7556 |41. 334 | |4 |6-8 |9 |7 |3. 66 |13. 3956 |120. 5604 | |5 |8-10 |3 |9 |5. 66 |32. 0356 |96. 1068 | | | | | | | | | | | |100 | | |53. 7780 |400. 4400 | [pic] Method 2 [pic] [pic][pic][pic][pic][pic][pic] 1 |0-2 |25 |1 |25 |25 | |2 |2-4 |48 |3 |144 |432 | |3 |4-6 |15 |5 |75 |37 5 | |4 |6-8 |9 |7 |63 |441 | |5 |8-10 |3 |9 |27 |243 | | | | | | | | | | |100 | |334 |1516 | [pic] d. Find the MEDIAN3 e. Find the MODE3 9. The following data is for the daily room rate in $, for staying at various hotels in downtown LA Hotels Offering RateDaily room rate 130 50 1470 690 3110 4130 1150 1170a. Compute the range b. Compute the average daily room rate. c. Compute the variance of the room rate. d. Find the median. e. Find the mode. Answers a. Range 170-30 =140 b. Average[pic]where [pic] [pic][pic][pic][pic] | 1 |1 |30 |30 | |2 |7 |50 |350 | |3 |14 |70 |980 | |4 |6 |90 |540 | |5 |3 |110 |330 | |6 |4 |130 |520 | |7 |1 |150 |150 | 8 |1 |170 |170 | | | | | | | |37 | |3070 | [pic] c. Variance of the room rate [pic] [pic][pic][pic][pic][pic][pic] |1 |1 |30 |-52. 9730 |2806. 1359 |2806. 1359 | |2 |7 |50 |-32. 9730 |1087. 2169 |7610. 5186 | |3 |14 |70 |-12. 9730 |168. 2980 |2356. 1724 | |4 |6 |90 |7. 0270 |49. 3791 |296. 747 | |5 |3 |110 |27. 0270 |730. 4602 |2191. 3806 | |6 |4 |130 |47. 0270 |2211. 5413 |8846. 1651 | |7 |1 |150 |67. 0270 |4492. 6224 |4492. 6224 | |8 |1 |170 |87. 0270 |7573. 7034 |7573. 7034 | | | | | | | | | |37 | |136. 2162 | |36172. 9730 | [pic]Method 2 [pic] [pic][pic][pic][pic][pic] |1 |1 |30 |30 |900 | |2 |7 |50 |350 |17500 | |3 |14 |70 |980 |68600 | |4 |6 |90 |540 |48600 | |5 |3 |110 |330 |36300 | |6 |4 |130 |520 |67600 | |7 |1 |150 |150 |22500 | |8 |1 |170 |170 |28900 | | | | | | | | |37 | |3,070 |290,900 | [pic] d. Find the MEDIAN70 e. Find the mode70 Solutions Hmwk ISDS-361AExercises 1. Mean, Median, Mode, Range, Variance & SD Panayiotis Skordi 1. A basketball player has the following points for seven games: 20, 25, 32, 18, 19, 22, 30 Compute the following measures of central location: a. mean b. median c. mode Answers a. Mean[pic] b. Median[pic] c. Mode There is no mode. 2. Consider the following population of measurements: 162, 152, 177, 157, 184, 176, 165, 181, 170, 163 a. compute the mean b. compute the median Answers a. Mean[pic] b. Median [pic] [pic] 3. The following data represent the number of children in a sample of 10 families from a certain community: , 2, 1, 1, 5, 3, 0, 1, 0, 2 a. compute the range b. compute the variance c. compute the standard deviation Answers a. Range [pic] b. Variance[pic] Remember that [pic] [pic][pic][pic][pic] 14 2. 14. 41 22 0. 10. 01 31-0. 90. 81 41-0. 90. 81 55 3. 19. 61 63 1. 11. 21 70-1. 93. 61 81-0. 90. 81 90-1. 93. 61 102 0. 10. 01 Total1924. 9 [pic] Method 2[pic] [pic][pic][pic] 1416 224 311 411 5525 639 700 811 900 1024 Total1961 [pic] This is the same answer – as we would expect. c. The standard deviation is [pic] 4. Consider the following population of measurements: 162, 152, 177, 157, 184, 176, 165, 181, 170, 163 a. ompute the standard deviation Answer [pic] Remember that [pic] [pic][pic][pic][pic] |1 |162 | |-6. 70 | |44. 89 | |2 |152 | |-16. 70 | |278. 89 | |3 |177 | |8. 30 | |68. 89 | |4 |157 | |-11. 70 | |136. 89 | |5 |184 | |15. 30 | |234. 09 | |6 |176 | |7. 30 | |53. 29 | |7 |165 | |-3. 0 | |13. 69 | |8 |181 | |12. 30 | |151. 29 | |9 |170 | |1. 30 | |1. 69 | |10 |163 | |-5. 70 | |32. 49 | | | | | | | | | | | | | | | |Total |1687. 0 | | | |1016. 10 | [pic] The standard deviation is the square root of the variance [pic] Method 2[pic] pic][pic][pic] |1 |162 | |26244 | |2 |152 | |23104 | |3 |177 | |31329 | |4 |157 | |24649 | |5 |184 | |33856 | |6 |176 | |30976 | |7 |165 | |27225 | |8 |181 | |32761 | |9 |170 | |28900 | |10 |163 | |26569 | | | | | | | | | | | | |1687 | |285613 | [pic] As before, the standard deviation is the square root of the variance pic] 5. Monthly rent data in dollars for a sample of one-bedroom apartments in a small town in Iowa are as follows: 220, 216, 220, 205, 210, 240, 195, 235, 204 and 205. a. compute the sample monthly average rent. b. compute the sample median. c. what is the mode? Answers a. Average [pic] [pic][pic] |1 |220 | |2 |216 | |3 |220 | |4 |205 | |5 |210 | |6 |240 | |7 |195 | |8 |235 | |9 |204 | |10 |205 | | | | | |2,150 | | | [pic] b. MEDIAN 195 204 205 205 210 216 220 220 235 240 [pic] c. MODE205 and 220 (bimodal) 6. A sample of 25 families was asked how many pets they owned. Their responses were summarized in the following table: |Number of Pets |0 |1 |2 |3 |4 |5 | |Number of Families |3 |10 |5 |4 |2 |1 | Determine the mean, median and the mode of the number of pets owned per family. ANSWERS a. MEAN[pic] [pic][pic][pic][pic] 0 |3 |0 | |1 |10 |10 | |2 |5 |10 | |3 |4 |12 | |4 |2 |8 | |5 |1 |5 | | | | | | |25 |45 | [pic] b. MEDIAN1 median is 13th observation. c. MODE 1 most families have 1 pet. 7.The following data represent the ages in years of a sample of 25 employees from a government department: 31,43,56,23,49,42,33,61,44,28,48,38,44,35,40,64,52,42,47,39,53,27,36,35 and 20. Construct a relative frequency distribution for the data, using five class intervals and the value 20 as the lower limit of the first class. |20 | | | |23 | | | |27 | | | |28 | |4 | |31 | | | |33 | | | |35 | | | 35 | | | |36 | | | |38 | | | |39 | |7 | |40 | | | |42 | | | |42 | | | |43 | | | |44 | | | |44 | | | |47 | | | |48 | | | |49 | |9 | |52 | | | 53 | | | |56 | |3 | |61 | | | |64 | |2 | |Class Limits |Frequency |Relative Frequency | | | | | |20 upto 30 |4 |0. 16 | |30 upto 40 |7 |0. 28 | |40 upto 50 |9 |0. 36 | |50 upto 60 |3 |0. 12 | |60 upto 70 |2 |0. 8 | | | | | | |25 |1. 00 | 8. How many hours a day do college students spend studying? That question was asked to 100 college students, and the data are p resented in the table below. Hours per DayFrequency 0-225 2-448 4-615 6-89 8-103 a. compute the range b. compute the average hours per day spent studying. c. compute the variance of the number of hours per day spent studying d. find the median e. find the mode Answers a. The range is 10-0 = 10 b. Average[pic] [pic][pic][pic][pic][pic] 1 |0-2 |25 |1 |25 | |2 |2-4 |48 |3 |144 | |3 |4-6 |15 |5 |75 | |4 |6-8 |9 |7 |63 | |5 |8-10 |3 |9 |27 | | | | | | | | | |100 | |334 | [pic] c. compute the variance of the number of hours per day spent studying [pic] note that [pic] [pic][pic][pic][pic][pic][pic][pic] |1 |0-2 |25 |1 |-2. 34 |5. 4756 |136. 89 | |2 |2-4 |48 |3 |-0. 34 |0. 1156 |5. 488 | |3 |4-6 |15 |5 |1. 66 |2. 7556 |41. 334 | |4 |6-8 |9 |7 |3. 66 |13. 3956 |120. 5604 | |5 |8-10 |3 |9 |5. 66 |32. 0356 |96. 1068 | | | | | | | | | | | |100 | | |53. 7780 |400. 4400 | [pic] Method 2 [pic] [pic][pic][pic][pic][pic][pic] 1 |0-2 |25 |1 |25 |25 | |2 |2-4 |48 |3 |144 |432 | |3 |4-6 |15 |5 |75 |37 5 | |4 |6-8 |9 |7 |63 |441 | |5 |8-10 |3 |9 |27 |243 | | | | | | | | | | |100 | |334 |1516 | [pic] d. Find the MEDIAN3 e. Find the MODE3 9. The following data is for the daily room rate in $, for staying at various hotels in downtown LA Hotels Offering RateDaily room rate 130 50 1470 690 3110 4130 1150 1170a. Compute the range b. Compute the average daily room rate. c. Compute the variance of the room rate. d. Find the median. e. Find the mode. Answers a. Range 170-30 =140 b. Average[pic]where [pic] [pic][pic][pic][pic] | 1 |1 |30 |30 | |2 |7 |50 |350 | |3 |14 |70 |980 | |4 |6 |90 |540 | |5 |3 |110 |330 | |6 |4 |130 |520 | |7 |1 |150 |150 | 8 |1 |170 |170 | | | | | | | |37 | |3070 | [pic] c. Variance of the room rate [pic] [pic][pic][pic][pic][pic][pic] |1 |1 |30 |-52. 9730 |2806. 1359 |2806. 1359 | |2 |7 |50 |-32. 9730 |1087. 2169 |7610. 5186 | |3 |14 |70 |-12. 9730 |168. 2980 |2356. 1724 | |4 |6 |90 |7. 0270 |49. 3791 |296. 747 | |5 |3 |110 |27. 0270 |730. 4602 |2191. 3806 | |6 |4 |130 |47. 0270 |2211. 5413 |8846. 1651 | |7 |1 |150 |67. 0270 |4492. 6224 |4492. 6224 | |8 |1 |170 |87. 0270 |7573. 7034 |7573. 7034 | | | | | | | | | |37 | |136. 2162 | |36172. 9730 | [pic]Method 2 [pic] [pic][pic][pic][pic][pic] |1 |1 |30 |30 |900 | |2 |7 |50 |350 |17500 | |3 |14 |70 |980 |68600 | |4 |6 |90 |540 |48600 | |5 |3 |110 |330 |36300 | |6 |4 |130 |520 |67600 | |7 |1 |150 |150 |22500 | |8 |1 |170 |170 |28900 | | | | | | | | |37 | |3,070 |290,900 | [pic] d. Find the MEDIAN70 e. Find the mode70

Differentiating Between Market Structures Essay - 1105 Words

Differentiating Between Market Structures ECO/365 Principles of Microeconomics August 30, 2012 Differentiating Between Market Structures Retail sales are indicators of microeconomic conditions presented in a given area at a particular place in time. Since Sam Walton opened his first Wal-Mart store, Wal-Mart has been making ripples throughout the micro economies of America. Wal-Mart’s market structure is typical of most of our nation’s largest corporations in that they are an oligopoly (Brown, 2010). According to Colander (2010), â€Å"An oligopoly is a market structure in which there are only a few firms and these firms explicitly take other firms’ likely response into account when making decisions.† Furthermore, given that†¦show more content†¦The company’s balance sheet shows that their international expansion has been the key to producing profits during the tough economic conditions of the previous several years. Many countries have a lower cost of living than Wal-Mart is accustomed to operating in and the decreased salaries and operating expenses overseas would serve to boost sales while increasing revenues. Wal-Mart can further maximize its profits in the long run through data mining product sales in order to establish market share for each retail location. This data would then be used to set-up the display of products for sale in a location and manner that would increase the volume of items sold. This strategy would cost Wal-Mart some time and money in the short run; however it would generate more sales in the long run and increase customer satisfaction in the short run. Both lead to an increase in sales and therefore maximize profits. Wal-Mart has another strategy available that can assist in maximizing revenue. That strategy involves the equilibrium of the labor market in all of the locales in which they operate. 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Lastminute Ipo And Subsequent Performance Finance Essay - Free Essay Example

Sample details Pages: 7 Words: 1972 Downloads: 1 Date added: 2017/06/26 Category Finance Essay Type Argumentative essay Did you like this example? The short-run underpricing and long-run underperformance of initial public offerings (IPOs) are the best documented anomalies in finance. This paper investigates if these anomalies exist in the aftermarket performance of the IPO of an internet-based company, Lastminute.com plc. Further analyses are then carried out to explain the performance results. Don’t waste time! Our writers will create an original "Lastminute Ipo And Subsequent Performance Finance Essay" essay for you Create order Evidence are presented that the companys IPO exhibits positive abnormal returns on the first day of trading. There are several theories of underpricing do not apply in explaining the short-run performance of the company. The long-run underperformance of IPO, which found in previous research, is not supported by the evidence of this study. The main problem of the long-run performance investigation is the difficulty of justifying systematic long-run underperformance in a reliable manner, especially during the bubble period. Declaration This project is entirely my own and includes nothing that could be interpreted as plagiarism of any other published or unpublished research or of any other students unpublished work. 1. Introduction Numerous studies have documented two well-known anomalies in initial public offerings (IPOs). One is that the IPOs provide large positive abnormal returns in the initial days of trading (Ritter, 1987; Levis 1990). This anomaly has been observed in almost every finance markets of the world. The other puzzle is IPOs appear to be overpriced in the long run. For example, Ritter (1991) provides evidence that US IPOs significantly underperform in the 3 years following the offering. However, the international evidence on the long-run performance of IPOs are less extensive and unanimously conclusive than the one on underpricing. The purpose of this study is to investigate the short-run as well as the long-run performance of an internet-based company, Lastminute.com plc which floated before dot-com bubble burst by using the event study methodology on IPOs. Besides, this clinical study provides further analyses and possible explanations for the observed results of the analysed firm based on the theoretical models in academic literature. I use market adjusted abnormal returns (MAARs) to measure short-run performance and the intercept from Fama-French (1993) three-factor model, i.e. Jensens alpha ( to measure average monthly abnormal return for different periods in the long run. These returns are adjusted by different benchmarks. Moreover, buy-and-hold abnormal returns (BHARs) are computed as a complementary analysis for the results from the Fama-French three factor model. To summarize the empirical findings of this paper, first, the results provide evidence supporting the general robustness of the prior finding with regard to the short-run underpricing of the Lastminute.coms IPO. There is significant and abnormally high first day return for the studied firm regardless the selection of benchmark. The short-run performance appears to be best explained by the high speculation level over the issue. The Rock (1986) model, the signalling hypothesis and the underwriter p restigious hypothesis are not the appropriate elucidations for the abnormal initial return results. Second, unlike previous research, the interesting finding is an inverse relationship between the periods after the firm floated and its poor post-IPO performance. The results from Fama-French three-factor model are not consistent with the initial prediction based on the academic literature. I find that Lastminute.com outperforms the market indices in the long run in spite of the signs of underperformance in the first year of trading. Results also show that the company performs better than other technology companies when the period tested is longer than 1 year. These results, nevertheless, are all statistically insignificant and therefore it concludes that the company of interest does not exhibit abnormal performance in the long run. Furthermore, the earnings management analysis does not indicate that there are accounting manipulations in the firm prior to the flotation. The dot- com bubble period, 1999-2000 period is extraordinary for the simple fact that both valuations and underpricing of firms simultaneously skyrocketed. It is important to note that Ljungvist and Wilhelm Jr. (2002) provide some evidence for the unique firm characteristics and aberrant pricing behaviour during the period. This paper, however, does not intend to examine the effect of the bubble on asset pricing and investor behaviour. I leave this for other researchers. The rest of my paper is arranged as follows. Section 2 provides the background for the studied firm. Section 3 reviews the IPO academic literature on short-run underpricing and long-run underperformance. Section 4 describes the data, methodology and hypothesis used in the investigation. Section 5 set out the short-run results and analysis. Section 6 set out the long-run results and analysis. Section 7 discusses the limitations and possible future research for the paper. Section 8 concludes the paper. 2. Background of the clinical study The company under investigation, Lastminute.com plc is an online travel agency and e-tailer which specialises in selling inventory such as package holidays, flights and consumer products at cut-rate prices to website customers. It was founded by Martha Lane Fox and Brent Hoberman in 1998. The site became an instant hit with internet travelers, garnering enough business and rapid growth to allow the company to offer stock on the London Stock Exchange in March 2000. The purpose of the offering, according to its prospectus, was to raise approximately  £113.5 million. Half of the amount would be used to increase sales and marketing activities, and the remaining for product development and expansion such as broadening supplier base, potential acquisition in UK and internationally. In addition, the company acknowledged in the prospectus that it was not profitable and expected to incur future losses. The major risk factors were reliance on third parties, intense competition and e-com merce uncertainties. Lane Fox and Hoberman became the icon of UK internet business entrepreneurs during the British dot-com boom. The company timed its launch to perfection and floated at the peak of the internet bubble. The issues received high interest of public and the share price spiralled as high as 555p from the offer price 380p on the first day of trading. Following the bubble burst, subsequently, Lastminute.coms stock sank and lost nearly half of its value within three weeks. Lastminute.com, however, unlike hundreds of other first-wave internet companies, it survived the bubble burst and stock market clash in 2001. Moreover, it continues to thrive and grow through expansion and shows reducing loss in its financial accounts. Lastminute.com is still considered as one of the few successful internet-based businesses in the relatively unstable world of internet. 3. Literature review 3.1. Empirical evidence and theories of short-run IPO underpricing A number of studies indicate the mispricing of IPOs which tend to yield substantial returns in the days immediately following issue. Stoll and Curley (1970) are the avant-garde to show the systematic abnormal first-day returns of IPOs. Substantial international evidence show that IPO underpricing has become a worldwide phenomenon. For British IPOs, the studies of Dimson (1979), Buckland, Herbert and Yeomans (1981), the Bank of England (1990), Jenkinson and Mayer (1988) and Levis (1993) exhibit average first day returns ranging from 8.6% to 17%. Ritter (1987), Welch (1989), Ibbotson, Sindelar and Ritter (1994) and Rajan and Servaes (1997) provide evidence suggesting that the existence of average initial returns of up to 16% has been a regular feature of the US new issue market. Lee, Taylor and Walter (1994), Jacquillat (1986), Kaneko and Pettway (1994) and Ljungqvist (1997) among others provide evidence of abnorma l returns of up to 14% in the developed markets of the world such as Australia, France, Japan and Germany. The literature abounds with a variety of conjectures that purport to explain the observed underpricing in IPOs based on the economic realities in the marketplace. Rock (1986) model provide a fundamental and convincing explanation for IPO performance by applying winners curse hypothesis to the new issue market. The model classifies investors as either informed or uninformed. The former are those who spend to assess the potential performance of the new issue, whereas the latter do not spend resources on the evaluation of the stock. Informed investors tend to crowd out uninformed investors for the underpriced and possibly lucrative issues. Consequently, uninformed investors hold a disproportionately large amount of overpriced IPOs, as informed investors may not subscribe. Uninformed investors would leave the market as they would systematically make losses. In order to keep the uninformed investors in the IPO market and to compensate their expected losses, the investment bankers have to offer the securities at discounts from their expected after-market prices. The studies by Koh and Walter (1989), Keloharju (1993), and Levis (1990) produce results that are consistent with and thus add further weight to the Rock model. Some theories propose the underpricing as a signalling mechanism of the firm quality. Allen and Faulhaber (1989) conclude that IPO underpricing is a credible indication of a firms post issue prospects. It is assumed that the underpricing in the firms initial offering is an immediate loss to the initial owners and companies with favourable position and performance in the after-market will be able to recoup the loss. These good companies underprice their IPO, because by doing so they direct investors to a favourable subsequent dividend results. Nevertheless, the assumption that company directors are willing to accept the initial loss on the IPO and renounce larger potential funding is doubtful in practical realities of market. Ritter (1984) suggested that gross underpricing may be a result of the monopsony power of the investment bankers in underwriting common stocks of small speculative firms. These investment bankers intentionally underprice the securities and only are allocated to favoured large customers who regularly buy a variety of investment services from the investment bank and thus pay unusually high brokerage fees. Tinic (1988), however, found evidence that the monopsony power hypothesis is not adequate for explaining underpricing behaviour. Johnson and Miller (1988) advance another explanation for underpricing. They analyse the prestige of underwriters and the level of underpricing. The finding is that the greater the underwriter prestige, the lower the degree of underpricing and it also works in the opposite way. This suggests the more prestigious banks require less underpricing to attract investor i nterest because they deal with lower risk issues. Beatty and Welch (1996) challenge the underwriter prestige hypothesis and show the inverse relation recently reversed for small firms. Muscarella and Vetsuypens (1989) find that investment banks themselves that go public are underpriced as well. The speculative bubble hypothesis claims that large excess returns of the IPOs are attributed to the investors who could not get allocations of the oversubscribed new issues from the underwriters at the offering prices. The speculative appetites of these investors then speculate temporarily inflating the price of the new issues in the aftermarket. When speculative demand diminishes, this speculative bubble should burst and negative excess returns are expected on the post-IPO share. Tests on aftermarket returns by Ritter (1984) and Tinic (1988) could find no evidence supportive of this hypothesis. Tinic (1988) and Hughes and Thakor (1992) argue that IPO underpricing used as a form of ins urance to reduce legal liability by both issuers and underwriters. This theory implies that a greater degree of underpricing occur to prevent investors experiencing significant losses on IPOs, as a result they are willing to neglect small errors such as omission of data, inadequate nature of data supplied for the disclosure requirement and thus not led to legal actions. However, Drake and Vetsuypens (1993) criticize and reject this hypothesis by showing evidence that underpriced IPOs are just as likely to be sued as overpriced IPOs and that there is no significant difference in underpricing between sued and non-sued firms. 3.2 Empirical evidence and theories of long-run underperformance The long-run underperformance of IPOs is a well-known perplexity in IPO literature and has attracted much attention from either investors or academic researchers in recent years. From an investors viewpoint, the existence of price patterns may present opportunities for superior returns using ac tive trading strategies. A finding of non-zero market performance would also call into question the informational efficiency of the IPO market which proposes after-market stock price should appropriately reflect the shares intrinsic value. Several authors have examined the returns on IPOs during the three years after going public for a number of countries. The international evidence of long-run underperformance is summarized in Table 1. Table 1 International Evidence on Long-run IPO Overpricing Country