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equilibrium price and quantity are achieved simultaneously, and as long as neither the supply curve nor the demand curve shifts, there is no tendency for either price or quantity to vary from their equilibrium values

ity. Alternatively, when the quantity that buyers are willing and able to purchase at a given price is just equal to the quantity that sellers are willing to offer at that same price, we say the market has discovered the equilibrium price. So <span>equilibrium price and quantity are achieved simultaneously, and as long as neither the supply curve nor the demand curve shifts, there is no tendency for either price or quantity to vary from their equilibrium values. <span><body><html>

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d><head>In general, economists believe that as the price of a good rises, buyers will choose to buy less of it, and as its price falls, they buy more. This is such a ubiquitous observation that it has come to be called the law of demand , although we shall see that it need not hold in all circumstances.<html>

head> We first analyze demand. The quantity consumers are willing to buy clearly depends on a number of different factors called variables. Perhaps the most important of those variables is the item’s own price. In general, economists believe that as the price of a good rises, buyers will choose to buy less of it, and as its price falls, they buy more. This is such a ubiquitous observation that it has come to be called the law of demand , although we shall see that it need not hold in all circumstances. Although a good’s own price is important in determining consumers’ willingness to purchase it, other variables also have influence on that decision, such as consumers’ inco

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analysts may appraise the quality of the company’s capital budgeting process on the basis of whether the company has an accounting focus or an economic focus.

of maximizing shareholder value. Because capital budgeting information is not ordinarily available outside the company, the analyst may attempt to estimate the process, within reason, at least for companies that are not too complex. Further, <span>analysts may be able to appraise the quality of the company’s capital budgeting process—for example, on the basis of whether the company has an accounting focus or an economic focus. This reading is organized as follows: Section 2 presents the steps in a typical capital budgeting process. After introducing the basic principles of capital budgeti

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Economic profit for a firm can originate from sources such as: competitive advantage; exceptional managerial efficiency or skill; difficult to copy technology or innovation (e.g., patents, trademarks, and copyrights); exclusive access to less-expensive inputs; fixed supply of an output, commodity, or resource; preferential treatment under governmental p

00 – $48,000,000 = $2,000,000. Note that total accounting costs in either case include interest expense—which represents the return required by suppliers of debt capital—because interest expense is an explicit cost. <span>2.1.2. Economic Profit and Normal Profit Economic profit (also known as abnormal profit or supernormal profit ) may be defined broadly as accounting profit less the implicit opportunity costs not included in total accounting costs. Equation (3a) Economic profit = Accounting profit – Total implicit opportunity costs We can define a term, economic cost , equal to the sum of total accounting costs and implicit opportunity costs. Economic profit is therefore equivalently defined as: Equation (3b) Economic profit = Total revenue – Total economic costs For publicly traded corporations, the focus of investment analysts’ work, the cost of equity capital is the largest and most readily identified implicit opportunity cost omitted in calculating total accounting cost. Consequently, economic profit can be defined for publicly traded corporations as accounting profit less the required return on equity capital. Examples will make these concepts clearer. Consider the start-up company for which we calculated an accounting profit of €300,000 and suppose that the entrepreneurial executive who launched the start-up took a salary reduction of €100,000 per year relative to the job he left. That €100,000 is an opportunity cost of involving him in running the start-up. Besides labor, financial capital is a resource. Suppose that the executive, as sole owner, makes an investment of €1,500,000 to launch the enterprise and that he might otherwise expect to earn €200,000 per year on that amount in a similar risk investment. Total implicit opportunity costs are €100,000 + €200,000 = €300,000 per year and economic profit is zero: €300,000 – €300,000 = €0. For the publicly traded corporation, we consider the cost of equity capital as the only implicit opportunity cost identifiable. Suppose that equity investment is $18,750,000 and shareholders’ required rate of return is 8 percent so that the dollar cost of equity capital is $1,500,000. Economic profit for the publicly traded corporation is therefore $2,000,000 (accounting profit) less $1,500,000 (cost of equity capital) or $500,000. For the start-up company, economic profit was zero. Total economic costs were just covered by revenues and the company was not earning a euro more nor less than the amount that meets the opportunity costs of the resources used in the business. Economists would say the company was earning a normal profit (economic profit of zero). In simple terms, normal profit is the level of accounting profit needed to just cover the implicit opportunity costs ignored in accounting costs. For the publicly traded corporation, normal profit was $1,500,000: normal profit can be taken to be the cost of equity capital (in money terms) for such a company or the dollar return required on an equal investment by equity holders in an equivalently risky alternative investment opportunity. The publicly traded corporation actually earned $500,000 in excess of normal profit, which should be reflected in the common shares’ market price. Thus, the following expression links accounting profit to economic profit and normal profit: Equation (4) Accounting profit = Economic profit + Normal profit When accounting profit equals normal profit, economic profit is zero. Further, when accounting profit is greater than normal profit, economic profit is positive; and when accounting profit is less than normal profit, economic profit is negative (the firm has an economic loss ). Economic profit for a firm can originate from sources such as: competitive advantage; exceptional managerial efficiency or skill; difficult to copy technology or innovation (e.g., patents, trademarks, and copyrights); exclusive access to less-expensive inputs; fixed supply of an output, commodity, or resource; preferential treatment under governmental policy; large increases in demand where supply is unable to respond fully over time; exertion of monopoly power (price control) in the market; and market barriers to entry that limit competition. Any of the above factors may lead the firm to have positive net present value investment (NPV) opportunities. Access to positive NPV opportunities and therefore profit in excess of normal profits in the short run may or may not exist in the long run, depending on the potential strength of competition. In highly competitive market situations, firms tend to earn the normal profit level over time because ease of market entry allows for other competing firms to compete away any economic profit over the long run. Economic profit that exists over the long run is usually found where competitive conditions persistently are less than perfect in the market. 2.1.3. Economic Rent The surplus value known as economic rent results when a particular resource or good is fixed in supply (with a vertical su

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Throughout this book the word empirical is used with reference to our knowledge of individuals as such.

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There are several methods available for estimating the cost of common equity, and we discuss two in this reading. The first method uses the capital asset pricing model, and the second method uses the dividend discount model, which is based on discounted cash flows. No matter the me

l on the borrowing. Equity entails no such obligation. Estimating the cost of conventional preferred equity is rather straightforward because the dividend is generally stated and fixed, but estimating the cost of common equity is challenging. <span>There are several methods available for estimating the cost of common equity, and we discuss two in this reading. The first method uses the capital asset pricing model, and the second method uses the dividend discount model, which is based on discounted cash flows. No matter the method, there is no need to make any adjustment in the cost of equity for taxes because the payments to owners, whether in the form of dividends or the return on capital, are not tax-deductible for the company. <span><body><html>

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Revenue recognition issues related to barter transactions became particularly important as e-commerce developed. As an example, if Company A exchanges advertising space for computer equipment from Company B but no cash changes hands, can Company A and B both report revenue? Such an exchange is referred to as a “barter transaction.” An even more challenging revenue recognition issue evolved from a specific type of barter transaction, a round-trip transaction. As an example, if Company A sells advertis

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following aspects of a company’s revenue recognition policy are relevant to financial analysis: Whether a policy results in recognition of revenue sooner rather than later, To what extent a policy requires the company to <span>make estimates.<span><body><html>

ods. Furthermore, a single company may use different revenue recognition policies for different businesses. Companies disclose their revenue recognition policies in the notes to their financial statement, often in the first note. <span>The following aspects of a company’s revenue recognition policy are particularly relevant to financial analysis: whether a policy results in recognition of revenue sooner rather than later (sooner is less conservative), and to what extent a policy requires the company to make estimates. In order to analyze a company’s financial statements, and particularly to compare one company’s financial statements with those of another company, it is helpful to understand any diffe

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Disposal of a portion of a business component does not qualify as discontinued operations. Instead, this is recorded as an unusual or infrequent item.

f analysis, an important issue is to assess whether non-recurring items are really "non-recurring," regardless of their accounting labels. There are four types of non-recurring items in an income statement. <span>1. Discontinued operations Discontinued operations are not a component of persistent or recurring net income from continuing operations. To qualify, the assets, results of operations, and investing and financing activities of a business segment must be separable from those of the company. The separation must be possible physically and operationally, and for financial reporting purposes. Any gains or disposal will not contribute to future income and cash flows, and therefore can be reported only after disposal, that is - when realized. Subsidiaries and investees also qualify as separate components. Disposal of a portion of a business component does not qualify as discontinued operations. Instead, this is recorded as an unusual or infrequent item. 2. Extraordinary items Extraordinary items are BOTH unusual in nature AND infrequent in occurrence, and material in amount. They must be reported separately (b

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; Free cash flow = CFO - capital expenditure Free Cash Flow to the Firm (FCFF): Cash available to shareholders and bondholders after taxes, capital investment, and WC investment. <span>FCFF = NI + NCC + Int (1 - Tax rate) - FCInv - WCInv NI: Net income available to common shareholders. It is the company's earnings after interest, taxes and preferred dividends. NCC: Net non-cash

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#13; FCFF = NI + NCC + Int (1 - Tax rate) - FCInv - WCInv = 250 + (-40) + 50 (1 - 0.3) - 20 - 100 = $125 million FCFF can also be computed from cash flow from operating activities (CFO). <span>FCFF = CFO + Int (1 - Tax rate) - FCInv The convenience of this approach to calculation of FCFF is that CFO is already adjusted for non-cash charges and changes in working capital accounts.

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Putting together a probabilistic Model that is, a model of a random phenomenon or a random experiment involves two steps. First step, we describe the possible outcomes of the phenomenon or experiment of interest. Second step, we describe our beliefs about the likelihood of the different possible outcomes by specifying a probability law. Here, we start by just talking about the first step, namely, the description of the possible outcomes of the experiment. So we carry out an experiment. For example

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ng a list of the possible outcomes-- or, a better word, instead of the word "list", is to use the word "set", which has a more formal mathematical meaning. So we create <span>a set that we usually denote by capital omega. That set is called the sample space and is the set of all possible outcomes of our experiment. The elements of that set should have certa

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;:"","st":"Khan Academy","th":126,"tu":"https://encrypted-tbn0.gstatic.com/images?q\u003dtbn:ANd9GcSn5LucwU2YqqP-QbKVKFxZQrH67dnFFkLdw7mMGEhss07jzQixQxdTCiUW","tw":224} <span>To create a box-and-whisker plot, we start by ordering our data (that is, putting the values) in numerical order, if they aren't ordered already. Then we find the median of our data. The median divides the data into two halves. To divide the data into quarters, we then find the medians of these two halves. Box-and-Whisker Plots - Purplemath www.purplemath.com/modules/boxwhisk.htm Feedback About this result People also ask What can you tell from a box and whisker plot?

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Suppose we make one forecast for the year-end level of the S&P 500 assuming economic expansion and another forecast for the year-end level of the S&P 500 assuming economic contraction. If we multiply the first forecast by the probability of expansion and the second forecast by the probability of contraction and then add these weighted forecasts, we are calculating the expected value of the S&P 500 at year-end. If we take a weighted average of possible future returns on the S&P 500, we are computing the S&P 500’s expected return.

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traction. If we multiply the first forecast by the probability of expansion and the second forecast by the probability of contraction and then add these weighted forecasts, we are calculating the expected value of the S&P 500 at year-end. <span>If we take a weighted average of possible future returns on the S&P 500, we are computing the S&P 500’s expected return. <span><body><html>

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Dollar-cost averaging (DCA) is an investment technique of buying a fixed dollar amount of a particular investment on a regular schedule, regardless of the share price. The investor purchases more shares when prices are low and fewer shares when prices are high. The premise is that DCA lowers the average share cost over time, increasing the opportunity

What is 'Dollar-Cost Averaging - DCA' <span>Dollar-cost averaging (DCA) is an investment technique of buying a fixed dollar amount of a particular investment on a regular schedule, regardless of the share price. The investor purchases more shares when prices are low and fewer shares when prices are high. The premise is that DCA lowers the average share cost over time, increasing the opportunity to profit. The DCA technique does not guarantee that an investor won't lose money on investments. Rather, it is meant to allow investment over time instead of investment as a lump sum. BREAKING DOWN 'Dollar-Cost Averaging - DCA' Fundamental to the strategy is a commitment to investing a fixed dollar amount each month. Depending

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According to Chebyshev’s inequality, for any distribution with finite variance , the proportion of the observations within k standard deviations of the arithmetic mean is at least 1 − 1/k 2 for all k > 1.

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Although CV was designed as a measure of relative dispersion, its inverse reveals something about return per unit of risk because the standard deviation of returns is commonly used as a measure of investment risk. For example, a portfolio with a mean monthly return of 1.19 percent and a standard deviation

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Although CV was designed as a measure of relative dispersion, its inverse reveals something about return per unit of risk. For example, a portfolio with a mean monthly return of 1.19 percent and a standard deviation of 4.42 percent has an inverse CV of 1.19%/4.42% = 0.27. This result indicates that each unit of standard deviation represents a 0.27 percent return.

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In calculations of variance since the deviations around the mean are squared, we do not know whether large deviations are likely to be positive or negative.

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The arithmetic mean is a special case of the weighted mean in which all the weights are equal to 1/n.

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Now suppose that the portfolio manager maintains constant weights of 60 percent in stocks and 40 percent in bonds for all five years. This method is called a constant-proportions strategy. Because value is price multiplied by quantity, price fluctuation causes portfolio weights to change. As a result, the constant-proportions strategy requires rebalancing to restore the w

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The stem of a stemplot can have as many digits as needed, but the leaves should contain only one digit.

Suppose you have the following set of numbers (they might represent the number of home runs hit by a major league baseball player during his career). 32, 33, 21, 45, 58, 20, 33, 44, 28, 15, 18, 25 <span>The stem of a stemplot can have as many digits as needed, but the leaves should contain only one digit. To create a stemplot to display the above data, you must first create the stem. Since all of the numbers have just two digits, start by arranging the tens digits from

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The stem of a stemplot can have as many digits as needed, but the leaves should contain only one digit.

Suppose you have the following set of numbers (they might represent the number of home runs hit by a major league baseball player during his career). 32, 33, 21, 45, 58, 20, 33, 44, 28, 15, 18, 25 <span>The stem of a stemplot can have as many digits as needed, but the leaves should contain only one digit. To create a stemplot to display the above data, you must first create the stem. Since all of the numbers have just two digits, start by arranging the tens digits from

#reading-9-probability-concepts

If we have two events, A and B, that we are interested in, we often want to know the probability that either A or B occurs. Note the use of the word "or," the key to this rule. The "or" is what we call an "inclusive or." In other words, either one event can occur or both events can occur. Such probabilities are calculated using the addition rule for probabilities. P(A or B) = P(A) + P(B) - P(AB) The logic behind this formula is that when P(A) and P(B) are added, the occasions on which A and B both occur are counted twice. To adjust for this, P(AB) is subtracted. If events A and B are mutually exclusive, the joint probability of A and B is 0. Consequently, the probability that either A or B occurs is simply the sum of the unconditional probabilities of A and B: P (A or B) = P(A) + P(B). What is the probability that a card selected from a deck will be either an ace or a spade? The relevant probabilities are: P(ace) = 4/52; P(spade) = 13/52 The only way in which an

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If we have two events, A and B, that we are interested in, we often want to know the probability that either A or B occurs. Note the use of the word "or," the key to this rule. The "or" is what we call an "inclusive or." In other words, either one event can occur or both events can occur. Such probabilities are calculated using the addition rule for probabilities. P(A or B) = P(A) + P(B) - P(AB) The logic behind this f

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use of the word "or," the key to this rule. The "or" is what we call an "inclusive or." In other words, either one event can occur or both events can occur. Such probabilities are calculated using the <span>addition rule for probabilities. P(A or B) = P(A) + P(B) - P(AB) The logic behind this formula is that when P(A) and P(B) are added, the occasions on which A and B both occur are counted twice. To adjust for this, P(AB) is subtracted. &#

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P(A or B) = P(A) + P(B) - P(AB) The logic behind this formula is that when P(A) and P(B) are added, the occasions on which A and B both occur are counted twice. To adjust for this, P(AB) is subtracted. <span>If events A and B are mutually exclusive, the joint probability of A and B is 0. Consequently, the probability that either A or B occurs is simply the sum of the unconditional probabilities of A and B: P (A or B) = P(A) + P(B). What is the probability t

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rySearch help Tools Any time Any time Past hour Past 24 hours Past week Past month Past year Custom range... Customised date range From To All results All results Verbatim About 649,000 results (0.47 seconds) Search Results Dictionary <span>con·vo·lut·ed ˈkänvəˌlo͞odəd/ adjective adjective: convoluted 1 . (especially of an argument, story, or sentence) extremely complex and difficult to follow. "its convoluted narrative encompasses all manner of digressions" synonyms: complicated, complex, involved, elaborate, serpentine, labyrinthine, tortuous, tangled, Byzantine; More Rube Goldberg; confused, confusing, bewildering, baffling "his convoluted answers did nothing to help his credibility" antonyms: straightforward 2 . technical intricately folded, twisted, or coiled. "walnuts come in hard and convoluted shells" Origin late 18th century: past participle of convolute, from Latin convolutus, past participle of convolvere ‘roll together, intertwine’ (see convolve). con·vo·lute ˈkänvəˌlo͞ot/ verb p

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e or." In other words, either one event can occur or both events can occur. Such probabilities are calculated using the addition rule for probabilities. P(A or B) = P(A) + P(B) - P(AB) <span>The logic behind this formula is that when P(A) and P(B) are added, the occasions on which A and B both occur are counted twice. To adjust for this, P(AB) is subtracted. If events A and B are mutually exclusive, the joint probability of A and B is 0. Consequently, the probability that either A or B occurs is simply the sum of the unconditio

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is 5/6. Therefore, the probability of getting a number from 1 to 5 on both rolls is: 5/6 x 5/6 = 25/36. This means that the probability of not getting a 1 to 5 on both rolls (getting a 6 on at least one roll) is: 1-25/36 = 11/36. <span>Despite the convoluted nature of this method, it has the advantage of being easy to generalize to three or more events. For example, the probability of rolling dice three times and getting a six on at least one of the three rolls is: 1 - 5/6 x 5/6 x 5/6 = 0.421 <span><body><html>

#reading-9-probability-concepts

Two events, A and B, are independent if and only if P(A|B) = P(A), or equivalently, P(B|A) = P(B). That is, the occurrence of one event has no influence on the probability of the occurrence of the other event. In more detail, whether or not B occurs will have no effect on the probability of A and vice versa. Thus, there will be no difference between P(A|B) and P(A), and similarly there will be no difference between P(B|A) and P(B). For example, suppose you flip a coin twice. The event of getting heads on the first flip does not affect the probability of getting heads on the second flip. Therefore, the event of getting heads on the second flip is independent of the event of getting heads on the first flip. When two events are not independent, they must be dependent: the occurrence of one is related to the probability of the occurrence of the other. If we are trying to forecast one event, information about a dependent event will be useful but information about an independent event will no

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Two events, A and B, are independent if and only if P(A|B) = P(A), or equivalently, P(B|A) = P(B). That is, the occurrence of one event has no influence on the probability of the occurrence of the other event. In more detail, whether or not B occurs will have no effect on

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Two events, A and B, are independent if and only if P(A|B) = P(A), or equivalently, P(B|A) = P(B). That is, the occurrence of one event has no influence on the probability of the occurrence of the other event. In more detail, whether or not B occurs will have no effect on the probability of A and vice versa. Thus, there will be no difference between P(A|B) and P(A), and similarly

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vent of getting heads on the first flip does not affect the probability of getting heads on the second flip. Therefore, the event of getting heads on the second flip is independent of the event of getting heads on the first flip. <span>When two events are not independent, they must be dependent: the occurrence of one is related to the probability of the occurrence of the other. If we are trying to forecast one event, information about a dependent event will be useful but information about an independent event will not be useful. Examp

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ffect the probability of getting heads on the second flip. Therefore, the event of getting heads on the second flip is independent of the event of getting heads on the first flip. When two events are not independent, they must be <span>dependent: the occurrence of one is related to the probability of the occurrence of the other. If we are trying to forecast one event, information about a dependent event will be useful but information about an independent event will not be useful. Examp

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nd flip is independent of the event of getting heads on the first flip. When two events are not independent, they must be dependent: the occurrence of one is related to the probability of the occurrence of the other. <span>If we are trying to forecast one event, information about a dependent event will be useful but information about an independent event will not be useful. Example 1 If C = {the price of insurance share C goes up} and D = {the price of insurance share D goes up}, then clearly C and D are dependent events, because

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hite car}, then events A and B are clearly independent, as the one almost certainly has no bearing upon the other. Remember that if A and B are independent, Ac and Bc will also be independent. A and B are two events. <span>If A and B are independent, the probability that events A and B both occur is: P(A and B) = P(A) x P(B) In other words, the probability of A and B both occurring is the product of the probability of A and the probability of B. This relationship is known as the multiplication

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nd B both occur is: P(A and B) = P(A) x P(B) In other words, the probability of A and B both occurring is the product of the probability of A and the probability of B. This relationship is known as the <span>multiplication rule for independent events. What is the probability that a fair coin will come up with heads twice in a row? Two events must occur: heads on the first toss and heads on the second toss. Since the prob

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in the deck, the probability of the first event is 1/52. Since 13/52 = 1/4 of the deck is composed of clubs, the probability of the second event is 1/4. Therefore, the probability of both events is: 1/52 x 1/4 = 1/208. Similarly, <span>for any number of independent events E 1 , E 2 .....E n , the probability that all of them occur is: P(E 1 and E 2 ..... and E n ) = P(E 1 ) x P(E 2 ) x ..... x P(E n ) Example In a bullish market, three shares, chosen from different sectors of the market, have probabilities of 0.6, 0.5 and 0.8 that their share prices will ris

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. If we wish to calculate the probability that all three shares will rise in price on the same day, we can use the results above to get: 0.6 x 0.5 x 0.8 = 0.24 (i.e., the individual probabilities multiplied together) <span>Warning: It is important to note that multiplying individual probabilities together can only be done if the events that make up those probabilities are independent. If the events are dependent, this process is not valid. To calculate the probability that, of the three shares above, none will have a price rise on a particular day, we can multiply the probabilities of the complementary events

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it helps to understand binomial experiments and some associated notation; so we cover those topics first. Binomial Experiment <span>A binomial experiment is a statistical experiment that has the following properties: The experiment consists of n repeated trials. Each trial can result in just two possible outcomes. We call one of these outcomes a success and the other, a failure. The probability of success, denoted by P, is the same on every trial. The trials are independent; that is, the outcome on one trial does not affect the outcome on other trials. Consider the following statistical experiment. You flip a coin 2 times and count the number of times the coin lands on heads. This is a bi