Guide :

how do you study?

I am trying to find different ways of studying please help I need and answer by tonight at 10:00pm please and thank you

Research, Knowledge and Information :

How to Develop Effective and Efficient Study Skills

How to Study. When you sit down to study, how do you transfer that massive amount of information from the books and notes in front of you to a reliable spot in your mind?
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How Do You Study - Study Habits Personality Quiz

How Do You Study for School? Created with Sketch. By Meredith Maines. Jun 23, 2010 Advertisement - Continue Reading Below. More from Seventeen: More From. Life Quizzes.
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How do top students study? - Quora

How do you get good grades at the top universities? Please give me directions, ... how many books you read, how you take the tests, how much do you study, ...
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What Subjects Should I Study in College? ~

The Right Way and the Wrong Way to Choose a College Major. Your first major decision, when setting off on your college career, will be what courses you intend to study.
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How Much Time Should You Devote to Studying? - Cornell College

How Much Time Should You Devote to Studying? Academic Support & Advising ... For the average Cornell block course you should estimate 6-8 hours of study time per day.
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How much do you study? Apparently 17 hours a week is the norm ...

Aug 17, 2014 · A recent study may be putting the “you should study three hours per credit hour” motto to rest. According to the National Survey of Student Engagement ...
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Discover proven ways to study not just harder but smarter. Learn how you can create a detailed study plan, maximize the time you spend studying, take meaningful notes ...
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What To Study | Be an Actuary

What To Study So, what do you need to know? If you are currently pursuing an undergraduate degree and are interested in an actuarial career, your equation for success ...
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''Where do you study?'' Vs ''where do you go to school ...

I wouldn't think twice about asking "where do you go to school" to any student from nursery right up through college, certainly, and even grad school.
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Suggested Questions And Answer :

How many students studied math only?

  To solve draw a large circle to represent 100 students. Inside the circle draw three smaller interlocking circles each representing a subject, represented by and labelled M, P, C. These circles produce 7 regions or areas caused by the overlaps and the region surrounding the three circles inside the larger circle is an 8th region. These are given letters a to h and represent the numbers of students in each region: a. M only b. P only c. C only d. M, P only e. M, C only f. All 3 g. P, C only h. None The combination of letters below represents addition of the quantities represented by the individual letters. abcdefgh=100; adef=40; bdfg=64; cefg=50; ef=20; df=24; c=8; f=10. (h=12, but this can be calculated as shown below.) abdefgh=92 and efg=42 (because c=8), so g=22 (because ef=20); ad=20; bg=40 (because df=24), so b=18 (because g=22); h=12 (because abdefgh=92, b=18, ad=20, efg=42); d=14 (because f=10), so a=6. There are a=6 students taking math only; b=18 students taking psychology only; g=22 taking psychology and chemistry only. (e=10 took math and chemistry only.)    
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in a school 37%study accounts 285 study business 15%study both what % study niether

We can't answer this because we don't know the size of the student population. This would have made more sense if it said a percent instead of a specific number (285 study business).
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what is the probability jose studied for a test given he got an A.

Truth table of probabilities:  Does study/gets A: 0.8*0.5=0.4, 40% Does study/fails A: 0.2*0.5=0.1, 10% Doesn't study/gets A: 0.1*0.5=0.05, 5% Doesn't study/fails A: 0.9*0.5=0.45, 45% There is a 40% probability that Jose studies and gets an A, where the probability is determined before the test. However, given that he gets an A, which is certain, the probability that he studied to get it remains at 50% if judging after the test when the results were known.
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anu studied 2 hours many minutes does she study in a week?

(2 ours/dae)* (7 daes) =14 ours
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(a)(1) The probability of a sale is 0.20 so the probability of no sale is 0.80. The probability of no sales with 8 firms is 0.80^8=16.78% approx. (2) We can use the binomial distribution with coefficients: 1 8 28 56 70 56 28 8 1. For no more than 2 sales we need the first 3 coefficients. (p+(p-1))^8=p^8+8p^7(1-p)+28p^6(1-p)^2+... where p=0.80. The first term is no sales at all, the second term just one sale, and the third term two sales. The total probability is 79.69%. (b)(1) Z score for X=10 is (10-7.5)/2.1=1.19 (approx) corresponding to 88.30%. So the percentage of students studying more than 10hrs per week is 11.70%. (2) If X=9, Z=0.7143, corresponding to 76.25%; and  if X=7, Z=-0.2380, corresponding to 1-0.5940=40.60%. So the proportion of students spending 7-9 hours is 76.25-40.60=35.65% approx. (3) If X=3 then Z=-2.143, corresponding to 1-0.9839=0.0161 or about 1.61% of students spend less than 3 hrs a week studying. (4) In the distribution table Z=1.645 corresponding to 95%. Therefore Z=-1.645 corresponds to 5% and -1.645=(X-7.5)/2.1, X=7.5-3.4545=4.04 or about 4 hours. So 5% of students spend less than 4 hours studying per week. (c) We don't know how many customers the clothing stores sees in one day. Should 2.7 be 2.7%?
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Discuss at least three applications of graph theory in the field of computer sciences?

Graphs are among the most ubiquitous models of both natural and human-made structures. They can be used to model many types of relations and process dynamics in physical, biological[1] and social systems. Many problems of practical interest can be represented by graphs. In computer science, graphs are used to represent networks of communication, data organization, computational devices, the flow of computation, etc. One practical example: The link structure of a website could be represented by a directed graph. The vertices are the web pages available at the website and a directed edge from page A to page B exists if and only if A contains a link to B. A similar approach can be taken to problems in travel, biology, computer chip design, and many other fields. The development of algorithms to handle graphs is therefore of major interest in computer science. There, the transformation of graphs is often formalized and represented by graph rewrite systems. They are either directly used or properties of the rewrite systems (e.g. confluence) are studied. Complementary to graph transformation systems focussing on rule-based in-memory manipulation of graphs are graph databases geared towards transaction-safe, persistent storing and querying of graph-structured data. Graph-theoretic methods, in various forms, have proven particularly useful in linguistics, since natural language often lends itself well to discrete structure. Traditionally, syntax and compositional semantics follow tree-based structures, whose expressive power lies in the Principle of Compositionality, modeled in a hierarchical graph. More contemporary approaches such as Head-driven phrase structure grammar (HPSG) model syntactic constructions via the unification of typed feature structures, which are directed acyclic graphs. Within lexical semantics, especially as applied to computers, modeling word meaning is easier when a given word is understood in terms of related words; semantic networks are therefore important in computational linguistics. Still other methods in phonology (e.g. Optimality Theory, which uses lattice graphs) and morphology (e.g. finite-state morphology, using finite-state transducers) are common in the analysis of language as a graph. Indeed, the usefulness of this area of mathematics to linguistics has borne organizations such as TextGraphs, as well as various 'Net' projects, such as WordNet, VerbNet, and others. Graph theory is also used to study molecules in chemistry and physics. In condensed matter physics, the three dimensional structure of complicated simulated atomic structures can be studied quantitatively by gathering statistics on graph-theoretic properties related to the topology of the atoms. For example, Franzblau's shortest-path (SP) rings. In chemistry a graph makes a natural model for a molecule, where vertices represent atoms and edges bonds. This approach is especially used in computer processing of molecular structures, ranging from chemical editors to database searching. In statistical physics, graphs can represent local connections between interacting parts of a system, as well as the dynamics of a physical process on such systems. Graph theory is also widely used in sociology as a way, for example, to measure actors' prestige or to explore diffusion mechanisms, notably through the use of social network analysis software. Under the umbrella of Social Network graphs there are many different types of graphs: Starting with the Acquaintanceship and Friendship Graphs, these graphs are useful for representing whether n people know each other. next there is the influence graph. This graph is used to model whether certain people can influence the behavior of others. Finally there's a collaboration graph which models whether two people work together in a particular way. The measure of an actors' prestige mentioned above is an example of this, other popular examples include the Erdős number and Six Degrees Of Separation Likewise, graph theory is useful in biology and conservation efforts where a vertex can represent regions where certain species exist (or habitats) and the edges represent migration paths, or movement between the regions. This information is important when looking at breeding patterns or tracking the spread of disease, parasites or how changes to the movement can affect other species. In mathematics, graphs are useful in geometry and certain parts of topology, e.g. Knot Theory. Algebraic graph theory has close links with group theory. A graph structure can be extended by assigning a weight to each edge of the graph. Graphs with weights, or weighted graphs, are used to represent structures in which pairwise connections have some numerical values. For example if a graph represents a road network, the weights could represent the length of each road. A digraph with weighted edges in the context of graph theory is called a network. Network analysis have many practical applications, for example, to model and analyze traffic networks. Applications of network analysis split broadly into three categories: First, analysis to determine structural properties of a network, such as the distribution of vertex degrees and the diameter of the graph. A vast number of graph measures exist, and the production of useful ones for various domains remains an active area of research. Second, analysis to find a measurable quantity within the network, for example, for a transportation network, the level of vehicular flow within any portion of it. Third, analysis of dynamical properties of networks.
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What is probability of 12 male and 13 female 25 volunteers vol pool of 30 15 male 15 female

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23 total studies 1=24 hr, 5=48 hr, and 17=72 hr what is the average # of days for a study

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its about phones like att-has a monthly fee of $39.99/mo and 450 anytime

?????????????? "methods we hav ben studying" ???????????
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(y=260.4+ 34.5) what is the score of someone who study 8 hours

yu left out the x y=260.4 +34.5x....evaluate at x=8 =260.4 +34.5*8 =260.4 + 276 =536.4
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