...2 Broad Study in Statistics Descriptive (mô tả) : provides simple summaries about the data collected & about the preliminary observations that have beed made. Such summaries maybe either quantitative (numerical measures) or visual (e.g. simple-to-understand graphs) e.g. Present a summary report of this year business result to management Inferential (suy luận) : are systems of procedures that can be used to draw conclusions from datasets arising from systems affected by random variation. The type of inferential statistical procedure used depends upon the type of data collected as well as the distribution of the data. The procedures are usually used to test hypotheses and establish probability. e.g. Estimate the IQ score of Kaplan students by observing a small group of students Population : e.g. A population is a collection of all individuals, objects, or measurement of interest Sample : e.g. A sample is a portion or part of the population of interst MCQ 1. The process of using sample statistics to draw conclusions about true population parameters is called Statistical inference. Keywords: inferential statistics 2. Those methods involving the collection, presentation, and characterization of a set of data in order to properly describe the various features of that set of data are called Descriptive statistics. 3. The collection characteristics of the employees of a particular firm is an example of Descriptive statistics. 4. The estimation of the population...
Words: 1655 - Pages: 7
...the stage where one can begin to use probabilistic ideas in statistical inference and modelling, and the study of stochastic processes. Probability axioms. Conditional probability and independence. Discrete random variables and their distributions. Continuous distributions. Joint distributions. Independence. Expectations. Mean, variance, covariance, correlation. Limiting distributions. The syllabus is as follows: 1. Basic notions of probability. Sample spaces, events, relative frequency, probability axioms. 2. Finite sample spaces. Methods of enumeration. Combinatorial probability. 3. Conditional probability. Theorem of total probability. Bayes theorem. 4. Independence of two events. Mutual independence of n events. Sampling with and without replacement. 5. Random variables. Univariate distributions - discrete, continuous, mixed. Standard distributions - hypergeometric, binomial, geometric, Poisson, uniform, normal, exponential. Probability mass function, density function, distribution function. Probabilities of events in terms of random variables. 6. Transformations of a single random variable. Mean, variance, median, quantiles. 7. Joint distribution of two random variables. Marginal and conditional distributions. Independence. iii iv 8. Covariance, correlation. Means and variances of linear functions of random variables. 9. Limiting distributions in the Binomial case. These course notes explain the naterial in the syllabus. They have been “fieldtested” on the class of 2000...
Words: 29770 - Pages: 120
...1 Hi I am Kim Johnson. I am presently a overnight stocker at Wall Mart. Up until July of 2013 I was the director of Nutrition Services at the local Medical Center. At this time the facility decided to outsource not only my position but the positions of managers in 2 other departments to a worldwide company. I have a Associates in Criminal Justice, I am a certified Correctional Officer, a Certified Dietary Manager and will have Bachelor’s Degree in Business in May----a person would think I could do better. But with the job market the way it is and me being an older person—it has been very hard to find a “good job”. I am the mother of 4 daughters, 4 grandchildren with another one on the way and a wife of 32 years. I love to garden, needlepoint, sew, read and I like to try new things. I enjoy going to sporting events so much that I have purchased tickets to the Women’s National Soccer game against China in Denver in April and have also got tickets for the NCAA women’s tournament in Lincoln. I have been in management for about 30 years. I am a democratic/participate leader. I really enjoy watching my employees achieve. I love to see them excited by something new that they did and excelled at. I also enjoy seeing events and projects come together and then evaluating them to see what can be improved on. I didn’t really learn anything from the personality or the Meyers Briggs tests. The results were what expected. I am planning on using these tests, if I ever get a job...
Words: 387 - Pages: 2
...to find the Significance of personality enhancement to the employability of hotel and restaurant graduates a four-year or a two-year concentration in Hotel and Restaurant Management is designed to prepare successful graduates for management positions in the field. Managers in the hotel and restaurant industry are generally responsible for keeping their establishment efficient and profitable while maximizing comfort of guests. This includes overseeing many aspects of the business including staffing and personnel, accounting, purchasing, and customer service. A hotel manager is responsible for coordinating registration, housekeeping, and maintenance activities, and may also coordinate special events, banquets, or conventions. This person will also decide on and arrange for outside services such as deliveries, laundry, trash collection, maintenance, and repairs. A restaurant manager must carefully observe food preparation, and may be responsible for ordering appropriate amounts of food and ensuring quality of inventory as well as coordinating and maintaining menus. Additionally, they are responsible for maintaining sanitation standards in the kitchen and dining areas. Restaurant managers will also decide on and arrange for outside services such as deliveries, laundry, trash collection, maintenance, and repairs. In the field personality enhancement is needed to be prioritized. Some students can’t catch up to that thing that’s why some that is in the field...
Words: 320 - Pages: 2
...Assignment 1: Starbuck’s Strategy MGT 500 Marcus Rowland October 18, 2014 Dr. Sandra Bryant Organizational culture is a term that has been used and defined in many different ways. Mainly organizational culture is the set of key values, beliefs, understanding and norms shared by members of an organization. (pg.75). A lot of companies use organizational culture to express to external factors what their organization truly believe and what is exactly important to them. A Company such as Starbucks expresses their key beliefs and values daily. Starbucks managers use this concept to understand the hidden aspects of organizational life. Starbucks, being an organization that deals with internal and external problems daily rely on these elements to cope with them. Starbucks visible values are well embedded with the company when you think of this organization. The Starbucks Logo is well known throughout and represents a green twin-tailed mermaid, known as Siren in Greek mythology. The Starbucks logo is so familiar the company has removed the company's name from around the logo and people can still easily recognize the logo as Starbucks brand. This reminds people who they are when customers see this mermaid. I However there are less obvious values that this company that are invisible and can only be perceived from what people believe and justify. For example one could interpret that Starbuck’s slogan is green because of their commitment to saving the environment and recycling. Starbucks...
Words: 769 - Pages: 4
...Unit 2 DB Subjective Probability “ A probability derived from an individual's personal judgment about whether a specific outcome is likely to occur. Subjective probabilities contain no formal calculations and only reflect the subject's opinions and past experience.” (investopedia.com, 2013) There are three elements of a probability which combine to equal a result. There is the experiment ,the sample space and the event (Editorial board, 2012). In this case the class is the experiment because the process of attempting it will result in a grade which could vary from an A to F. The different grades that can be achieved in the class are the sample space. The event or outcome is the grade that will be received at the end of the experiment. I would like to achieve an “A” in this class but due to my lack of experience in statistical analysis, my hesitation towards advanced mathematics, and the length of time it takes for me to complete my course work a C in this class may be my best result. I have a 1/9 chance or probability to receive an “A” in the data range presented to me which is (A,A-,B,B-,C,C-,D,D- AND F). By the grades that have been posted I would say that the other students have a much better chance of receiving a better grade than mine. I have personally use subjective probability in my security guard business in bidding on contracts based on the clients involved , the rates that I charge versus the rates other companies charge and the amount of work involved...
Words: 344 - Pages: 2
... Probability – the chance that an uncertain event will occur (always between 0 and 1) Impossible Event – an event that has no chance of occurring (probability = 0) Certain Event – an event that is sure to occur (probability = 1) Assessing Probability probability of occurrence= probability of occurrence based on a combination of an individual’s past experience, personal opinion, and analysis of a particular situation Events Simple event An event described by a single characteristic Joint event An event described by two or more characteristics Complement of an event A , All events that are not part of event A The Sample Space is the collection of all possible events Simple Probability refers to the probability of a simple event. Joint Probability refers to the probability of an occurrence of two or more events. ex. P(Jan. and Wed.) Mutually exclusive events is the Events that cannot occur simultaneously Example: Randomly choosing a day from 2010 A = day in January; B = day in February Events A and B are mutually exclusive Collectively exhaustive events One of the events must occur the set of events covers the entire sample space Computing Joint and Marginal Probabilities The probability of a joint event, A and B: Computing a marginal (or simple) probability: Probability is the numerical measure of the likelihood that an event will occur The probability of any event must be between 0 and 1, inclusively The sum of the...
Words: 553 - Pages: 3
...= {-20, -19, …, -1, 0, 1, …, 19, 20} Number of people arriving at a bank in a day: S = {0, 1, 2, …} Inspection of parts till one defective part is found: S = {d, gd, ggd, gggd, …} Temperature of a place with a knowledge that it ranges between 10 degrees and 50 degrees: S = {any value between 10 to 50} Speed of a train at a given time, with no other additional information: S = {any value between 0 to infinity} 4 Sample Space (cont…) Discrete sample space: One that contains either finite or countable infinite set of outcomes • Out of the previous examples, which ones are discrete sample spaces??? Continuous sample space: One that contains an interval of real numbers. The interval can be either finite or infinite 5 Events A collection of certain sample points A subset of the sample space Denoted by ‘E’ Examples: • Getting an odd number in dice throwing experiment S = {1, 2, 3, 4,...
Words: 685 - Pages: 3
...[pic] [pic] Markov Chain [pic] Bonus Malus Model [pic] [pic] This table justifies the matrix above: | | | |Next state | | | |State |Premium |0 Claims |1 Claim |2 Claims |[pic]Claims | |1 | |1 |2 |3 |4 | |2 | |1 |3 |4 |4 | |3 | |2 |4 |4 |4 | |4 | |3 |4 |4 |4 | | | | | | | | |P11 |P12 |P13 |P14 | | | |P21 |P22 |P23 |P24 | | | |P31 |P32 |P33 |P34 | | | |P41 |P42 |P43 |P44 | | | | ...
Words: 361 - Pages: 2
...Permutations The word ‘coincidence’ is defined as an event that might have been arranged though it was accidental in actuality. Most of us perceive life as a set of coincidences that lead us to pre-destined conclusions despite believing in a being who is free from the shackles of time and space. The question is that a being, for whom time and space would be nothing more than two more dimensions, wouldn’t it be rather disparaging to throw events out randomly and witness how the history unfolds (as a mere spectator)? Did He really arrange the events such that there is nothing accidental about their occurrence? Or are all the lives of all the living beings merely a result of a set of events that unfolded one after another without there being a chronological order? To arrive at satisfactory answers to above questions we must steer this discourse towards the concept of conditional probability. That is the chance of something to happen given that an event has already happened. Though, the prior event need not to be related to the succeeding one but must be essential for it occurrence. Our minds as I believe are evolved enough to analyze a story and identify the point in time where the story has originated or the set of events that must have happened to ensure the specific conclusion of the story. To simplify the conundrum let us assume a hypothetical scenario where a man just became a pioneer in the field of actuarial science. Imagine him telling us his story in reverse. “I became...
Words: 825 - Pages: 4
...organizational politics. Unlawful behavior from the employees’ side may be resisted with the help of organizational politics. Jacqui Blanc stayed with strict procedures and reported directly to the CEO. Hunt, the CEO, had to abide by these guidelines because she manager put a lot of trust and confidence in Jacqui; who then provided honest information to the manager. Jacqui was truthful and brought a lot help to the company from the two production managers and the producers who were frauds. She corrected the deceitful events that involved two of the company’s production managers. Doc also reported directly and the manager and the other staff really thought highly of him. He received answers quickly because he knew that the ESD will not in any way accept the unfinished ideas and therefore channeled through the manager. The manager would then order ESD to halt recent projects to begin work on Doc’s awesome idea. You could tell that this wasn’t expected because the manager, who put his trust and confidence in Doc and would not fire him because of the great impact he has on the company of being a mastermind in his job and producing ideas that were profitable to the company. Doc had a major influence over the company and the manager because he was smart. When it comes to political influence, employees may be convinced about the plans and goals of the organization Doc was a mastermind; he clearly could persuade any position was protected and could save his employees from being relieved from...
Words: 675 - Pages: 3
...Policy Process Part 2 Introduction Managers’ role and responsibility in implementing change in the department Modification management, in any organization, is the role of management and administrators. In modification management, managers and administrative must manage modification with in a manner that workers can handle with. The manager is liable for the assistance and enablement of modification. Managers must recognize the circumstances from an impartial perspective. They must also assistance individuals comprehend goals, details, and conducts of confidently replying to modification conferring to their circumstances and ability. The manger must understand, converse, and allow workers and not to teach or enforce modification on individuals. All modifications requirements sponsorship. A benefactor is somebody with ability to say what is significant. The manager can assistance in the development and performance of modification. Deprived of managers to proposal guidelines on modification implementation, modification appears possible with only with a rare workers eager to go on board though others endure on by-products. With modification manager or benefactor, modification implementation and management appears voluntary. In enormous administrations, the absence of decision-making sponsorship consequences to sluggish acceptance to modification. However, modification implementation that has someone as the manager from the organizational modification...
Words: 984 - Pages: 4
...presence with probability 0.99. If it is not present, the radar falsely registers an aircraft presence with probability 0.10. We assume that an aircraft is present with probability 0.05. What is the probability of false alarm (a false indication of aircraft presence), and the probability of missed detection (nothing registers, even though an aircraft is present)? A sequential representation of the sample space is appropriate here, as shown in Fig. 1. Figure 1: Sequential description of the sample space for the radar detection problem Solution: Let A and B be the events A={an aircraft is present}, B={the radar registers an aircraft presence}, and consider also their complements Ac={an aircraft is not present}, Bc={the radar does not register an aircraft presence}. The given probabilities are recorded along the corresponding branches of the tree describing the sample space, as shown in Fig. 1. Each event of interest corresponds to a leaf of the tree and its probability is equal to the product of the probabilities associated with the branches in a path from the root to the corresponding leaf. The desired probabilities of false alarm and missed detection are P(false alarm)=P(Ac∩B)=P(Ac)P(B|Ac)=0.95∙0.10=0.095, P(missed detection)=P(A∩Bc)=P(A)P(Bc|A)=0.05∙0.01=0.0005. Application of Bayes` rule in this problem. We are given that P(A)=0.05, P(B|A)=0.99, P(B|Ac)=0.1. Applying Bayes’ rule, with A1=A and A2=Ac, we obtain P(aircraft present | radar registers) =...
Words: 1422 - Pages: 6
...1.M/G/ Queue a. Show that Let A(t) : Number of arrivals between time (0, t] “ n should be equal to or great than k” since if n is less than k (n<k), Pk(t)=0 Let’s think some customer C, Let’s find P{C arrived at time x and in service at time t | x=(0,t)] } P{C arrives in (x, x+dx] | C arrives in (0, t] }P{C is in service | C arrives at x, and x = (0,t] } Since theorem of Poisson Process, The theorem is that Given that N(t) =n, the n arrival times S1, S2, …Sn have the same distribution as the order statistics corresponding to n independent random variables uniformly distributed on the interval (0, t) Thus, P{C is in service | C arrives between time (0, t] } Since let y=t-x, x=0 → y=t, x=t →y=o, dy=-dx Therefore, In conclusion, ------ (1) 1-a Solution Since b. let 1-b Solution ------------------------------------------------- 2. notation Page 147 in “Fundamentals of Queuing Theory –Third Edition- , Donald Gross Carl M. Harris a. b. ------------------------------------------------- ------------------------------------------------- ------------------------------------------------- 3. a. let X=service time (Random variable) and XT=total service time (Random variable) X2=X+X, X3=X+X+X, ….. f2(x2)...
Words: 277 - Pages: 2
...Probability & Mathematical Statistics | “The frequency concept of Probability” | [Type the author name] | What is probability & Mathematical Statistics? It is the mathematical machinery necessary to answer questions about uncertain events. Where scientists, engineers and so forth need to make results and findings to these uncertain events precise... Random experiment “A random experiment is an experiment, trial, or observation that can be repeated numerous times under the same conditions... It must in no way be affected by any previous outcome and cannot be predicted with certainty.” i.e. it is uncertain (we don’t know ahead of time what the answer will be) and repeatable (ideally).The sample space is the set containing all possible outcomes from a random experiment. Often called S. (In set theory this is usually called U, but it’s the same thing) Discrete probability Finite Probability This is where there are only finitely many possible outcomes. Moreover, many of these outcomes will mostly be where all the outcomes are equally likely, that is, uniform finite probability. An example of such a thing is where a fair cubical die is tossed. It will come up with one of the six outcomes 1, 2, 3, 4, 5, or 6, and each with the same probability. Another example is where a fair coin is flipped. It will come up with one of the two outcomes H or T. Terminology and notation. We’ll call the tossing of a die a trial or an experiment. Where we...
Words: 1183 - Pages: 5
