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# MGTOP 215 Exam 1 Ch. 1-4 Study Guide MGTOP 215

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This 2 page Study Guide was uploaded by Megan Lester on Wednesday September 28, 2016. The Study Guide belongs to MGTOP 215 at Washington State University taught by Sung Ahn in Fall 2015. Since its upload, it has received 2 views.

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Date Created: 09/28/16

Chapter 1 Types of data: qualitative: nonnumeric and categorical quantitative: numeric o discrete: assumes only specific points on a scale o continuous: assumes all values within an interval Levels of measurements: The nominal scale applies to data that are divided into different categories, and these categories are used for identification purposes, e.g., female=0, male=1; ISP: Verizon=1, , AT&T=2, Sprint=3, T-Mobile=4, Other=5. The ordinal scale applies to data that are divided into different categories that can be ranked, e.g., bad=0, fair=1, good=2; bond ratings: AAA, AA, A, BBB, BB; Student grades: A, B, C, D, F, etc. The interval scale applies to data that can be ranked and for which the difference between two values can be calculated and interpreted and do not involve a true zero point, e.g., temperature, calendar time, SAT score. The ratio scale applies to data that can be ranked and for which the ratio between two values can be calculated and interpreted, e.g., income, weight. Chapter 2 Frequency table Finding the K class: range Class-interval/class width: width of intraval = number of classes Frequency: is the number of times a number in that rage appears in the variable set Relative Frequency: is the percentage (given in decimals) of the frequency out of the total number of variables on the set Cumulative Frequency: is an accumulation of the frequency of a class and all previous classes until it adds up to the total number of variables in the set Relative Cumulative Frequency (Percentage Less Than): is the percentage (given in decimals) of the Cumulative frequency out of the total number of variables on the set Example Histogram To get width: rage between class interval Relative Frequency To get Height: width = rage between class interval Bin: .01 less or more then each of the intervals Chapter 3 Mean: add all the variables up and divide by how many variables there are Median: middle number Mode: most frequent number Rage: largest number-smallest number (7−6)2+ 4−6)2+ 9−6)2+ 8−6)2+ 2−6)2 Variance: (ex: 7, 4, 9, 8, 2, Mean=6) 5−1 = 8.5 Standard deviation: is the √ of the variance ???? (???????????????????????????????? ????????????????????????????????????) Coefficient of variation: = ????(????????????????) ∗ (100%) ????−????̅ Z score: is the difference between a values and the mean,????, divided by the standard deviation, S, as shown ???? = 1 ???? Geometric mean (rate of return): ???? = [ 1 + ????( )∗ 1 + ???? ) ∗ …∗ 1 + ???? )???? − 1] ????=1 ???? 1 2 ???? The First Quartile: ???? =1 ranked value 4 The Thrid Quartile: ???? = 3(????=1) ranked value 1 4 Five number summary: smallest value, the first quartile, the median, the third quartile, and the largest value. Boxplot: use five number summary to make Chapter 4 Examples of: sample event: getting a head on the second coin Joint event: getting a tail on the second coin and a head on the third coin Complement of getting a tail on the forth coin: getting a head on the forth coin (opposite event) What dose sample space consist of: getting a head or a tail on any of the five coins A priori probability (or classical method): the probability of an outcome is based on the prior knowledge of the experiment (process) involved. Empirical probability (relative frequency or empirical method): the probability of an outcome is the relative frequency of the outcome, that is, the frequency of occurrences of the outcome divided by the number of trials repeated. Subjective probability: the probability of an event reflects a person’s degree of belief that the event will occur. The intersection of two events A and B, denoted by A and B, A∩B, or AB called the Joint event The union of two events A and B, denoted by A or B or by A∪B Additive rule: ????(???? ∪ ????) = ????(????) + ????(????) − ????(???? ∩ ????) P(A ∩ B) The conditional event of A given that B has occurred is denoted by A|B, and its probability is ???? (????⃒????) = ????(????) Two events A and B are independent if and only if one of the following holds: Ex B B’ Prob of event A’ A 90 80 40 + 80 = 120 A’ 50 10 120 20 + 40 + 40 = 100 Prob of event A ???? ????′ = 180 = .667 100 ???? ???? ???????? ???? = 180 = .556 20 + 40 + 40 + 80 = 180 Prob or event A and B 20 + 40 = 60 20 60 ???? ???? ???????????? ???? = 180 = .111 ???? ???? = = .33 Prob or event A’ and B’ 180 Ex B B’ 1⁄ ???? (????⃒????) = 9 = 0.33 (????′⃒????′) = A 15 30 1⁄ 60 4 A’ 30 60 3 ???? (????′⃒????′) = = (????⃒???? ) = 135 9 (????⃒????) = ????(????′ ???????????? ????′) ????(???? ???????????? ????) ′ 30 2 ???? (????⃒????′) = ???? (????⃒????) = ???? ???? ???????????? ???? )= = ????(????′) ????(????) 135 9 4⁄9 15 + 30 + 30 + 60 = 135 30 + 60 = 90 ???? (????⃒????) = = 0.67 15 1 ′ 90 2 2⁄3 ???? ???? ???????????? ???? = = ???? ???? ) = 135 = 3 135 9 2 15+30=45 ⁄9 45 1 ???? (????⃒????′) = 2 = .33 ???? ???? = = ⁄3 135 3 Example 6: At Cheers you have a 90 % chance of running into Cliff. When Cliff is present at the bar you have a 95% chance of running into Norm; when Cliff is not present you have only 10% chance of running into Norm. a) Find the probability that you will run into Norm at Cheers. b) One day you walk into the bar and spot Norm. Then find the probability that you run into Cliff. c) Are the event of running into Cliff and the event of running into Norm independent?

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