MGT 601: Statistical Inference Lecture 03 Dr. MUMTAZ AHMED Objectives of Current Lecture In the current lecture: Introduction to Probability Definition and Basic concepts of probability Some basic questions related to probability Laws of probability Conditional probability Independent and Dependent Events Related Examples 2 Probability Probability (or likelihood) is a measure or estimation of how likely it is that something will happen or that a statement is true. For example
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M227 Chapter 1 Nature of Probability and Statistics OBJECTIVES Demonstrate knowledge of statistical terms. Differentiate between the two branches of statistics. Identify types of data. Identify the measurement level for each variable. Identify the four basic sampling techniques. Explain the difference between an observational and an experimental study. Explain how statistics can be used and misused. Explain the importance of computers and calculators in statistics. Statistics is the science
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Probability distribution Definition with example: The total set of all the probabilities of a random variable to attain all the possible values. Let me give an example. We toss a coin 3 times and try to find what the probability of obtaining head is? Here the event of getting head is known as the random variable. Now what are the possible values of the random variable‚ i.e. what is the possible number of times that head might occur? It is 0 (head never occurs)‚ 1 (head occurs once out of 2 tosses)
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Probability From Wikipedia‚ the free encyclopedia Jump to: navigation‚ search Probability Outline Catalog of articles Probabilists Glossary Notation Journals Category v t e Certainty series Agnosticism Approximation Belief Certainty Doubt Determinism Epistemology Fallibilism Fatalism Hypothesis Justification Nihilism Probability Scientific theory Skepticism Solipsism Theory Truth Uncertainty v t e Probability (or likelihood[1])
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Probability Paper David E. Nelson QNT/561 February 14‚ 2013 Professor Minh Bui Probability Paper My friends suggested that we take a hiking trip through South America this year. The reason for such a trip was to celebrate 16 years of close friendship. The four of us had known each other since we were in middle school and have since become inseparable. Even though we all lead very different lives and have even started our own families‚ we always manage to find time to spend with each other
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1 Why probability and statistics? Is everything on this planet determined by randomness? This question is open to philosophical debate. What is certain is that every day thousands and thousands of engineers‚ scientists‚ business persons‚ manufacturers‚ and others are using tools from probability and statistics. The theory and practice of probability and statistics were developed during the last century and are still actively being refined and extended. In this book we will introduce the basic notions
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Appendix D Additional problems D.1 Probability theory (Chapter 2-3) (i) If X is a uniform‚ continuous random variable on the interval [a‚ b] and Y is a uniform‚ discrete random variable on the interval [k‚ l] where k and l are integers and k < l‚ then compute Pr [Z ≤ x] where Z = X + Y given that X and Y are independent. (ii) Suppose that the number N of pages in a fax transmission has a geometric probability distribution with mean 1/q = 4. The number K of bits per page also has a geometric
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14. If x has the probability distribution f(x) = 12x for x = 1‚2‚3‚…‚ show that E(2X) does not exist. This is famous Petersburg paradox‚ according to which a player’s expectation is infinite (does not exist) if he is to receive 2x dollars when‚ in a series of flips of a balanced coin‚ the first head appears on the xth flip. 17. The manager of a bakery knows that the number of chocolate cakes he can sell on any given day is a random variable having the probability distribution f(x) = 16 for x =
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2010 Words of Probability ISHIGURO‚ Makio(The Institute of Statistical Mathematics) Words of Probability ISHIGURO‚ Makio(The Institute of Statistical Mathematics) Key Words: subjective probability‚ confidence‚ belief‚ frequency‚ verbal expression Abstract There are everyday expressions such that ’probably’; ’might be’;’could be’ etc.‚ to describe the strengths of one’s confidence in the occurrence of events in the future. On the other hand there are probability theory expressions such
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Random Variable and Its Probability distribution “A random variable is a variable hat assumes numerical values associated with the random outcome of an experiment‚ where one (and only one) numerical value is assigned to each sample point”. “A random variable is a numerical measure of the outcome from a probability experiment‚ so its value is determined by chance. Random variables are denoted using letters such as X‚Y‚Z”. X = number of heads when the experiment is flipping a coin 20 times. There
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