the example given in the lecture in your own words? Mean and variance are both about distribution‚ but mean refers to one measure of the central value for a probability distribution. It is the average of a set of measurements. On the other hand‚ variance is a measure of how far a set of numbers is spread out. In a statistical probability graph the difference in variance is made visible in the height of the graph. A low variance indicates that the data points are close to the mean. This can be recognized
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------------------------------------------------- Top of Form Bottom of Form Wallace State Community College Business Statistics I BUS 271‚ 3 Credit Hours Spring Semester 2013 Step One: Read the syllabus carefully. Step Two: E-mail your instructor‚ in Blackboard through the email/message area; this will be a tab on left side of your homepage in blackboard. Select create message. Browse for recipient‚ Terri McGriff-Waldrop‚ select and fill in the subject line with the topic title‚ Syllabus
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Heading: The Characteristics of Markov Analysis Key words: Markov analysis 9) The brand-switching problem analyzes the probability of customers’ changing brands of a product over time. Answer: TRUE Diff: 2 Main Heading: The Characteristics of Markov Analysis Key words: brand-switching problem‚ Markov analysis 10) Markov analysis provides information on the probability of customers switching from one brand to one or more other brands. Answer: TRUE Diff: 1 Main Heading: The Characteristics
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subcomponent (cm). Then if the machine is operating correctly‚ X ~ N (117‚ 2.12 ) . (i) find the probability that one randomly selected unit has a length greater than 120 cm; X −µ 120 − 117 ) = P( Z > 1.4286) ≈ P( Z > 1.43) σ 2.1 = 1 − P( Z < 1.43) = 1 − 0.9236 = 0.0764 X: P( X > 120) = P( > Alternative solution: P ( Z > 1.43) = P ( Z < −1.43) = 0.0764 (ii) Z: 117 120 0 1.43 find the probability that if three units are randomly selected‚ their mean length exceeds 120 cm; Let X = mean length
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|proficiency. | |Vocabulary: |Visuals‚ Materials & Texts: | |probability‚ event‚ outcome‚ sample space‚ tree diagram |graphing calculators‚ dice‚ coins‚ poster of tree diagram‚ index | | |cards for visual/verbal
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Answer: False Correct Answer: False Question 5 If events A and B are independent‚ then P(A|B) = P(B|A). Answer Selected Answer: False Correct Answer: False Question 6 A binomial probability distribution indicates the probability of r successes in n trials. Answer Selected Answer: True Correct Answer: True Question 7 The events in an experiment are mutually exclusive if only one can occur at a time. Answer
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points each) T F 1. The probability that X takes on a value that is between 3 and inclusive of 4 can be written as P(3 < X ( 4). T F 2. P(X > x ) + P(X < x) + P(X = x) = 1. T F 3. If P(X > x) = 0.34 and P(X = x) = 0.10‚ then P(X ( x) = 0.56. T F 4- Using the classical viewpoint‚ the probability of an event happening is defined as the number of favorable outcomes divided by the total number of possible outcomes. T F 5- The probability assigned to an event that
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UNIVERSITI TEKNOLOGI P E T RO NA S @t C OU R S E DATE TIME . GA B 2O13 B2133BUSINESS / SM STATISTTCS / QUANTITATIVE METHOD 27 MAY2008(TUESDAY) 2 .3 0PM- 5.30PM ( 3 hour s) INSTRUCTIONS CANDIDATES TO 1. 2. 3. 4. 5. Answer FIVE(5)outof SIX(6)questions theQuestion from Booklet. BeginEACHanswer a newpagein theAnswer on Booklet. lndicate clearly answers arecancelled‚any. that if Whereapplicable‚ showclearly stepstakenin arriving the solutions at and indicate ALL assumptions. Do notopenthisQuestion
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in an experiment are mutually exclusive if only one can occur at a time.Answer | | | | | Selected Answer: | True | Correct Answer: | True | | | | | Question 7 2 out of 2 points | | | A binomial probability distribution indicates the probability of r successes in n trials. Answer | | | | | Selected Answer: | True | Correct Answer: | True | | | | | Question 8 2 out of 2 points | | | If fixed costs increase‚ but variable cost and price
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Exemplar Theory Exemplar Theory refers to an approach of categorization in psychology using which individuals can make decisions by comparing new examples with the examples which is already present in their mind. Instead of relying on a single prototype‚ categories have many or known exemplars that fit into them. When you come across something new‚ you can compare it with all members of a category. The greater the number of exemplars the new item will match‚ the better will it adapt against all
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