Assignment 1: Bottling Company Case Study xxxxxxx xxxxx Professor xxxxx Math 300 – Statistics June 9, 2014 Imagine you are a manager at a major bottling company. Customers have begun to complain that the bottles of the brand of soda produced in your company contain less than the advertised sixteen (16) ounces of product. Your boss wants to solve the problem at hand and has asked you to investigate. You have your employees pull thirty (30) bottles off the line at random from all the shifts
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frequency and 1000-1149 is the lowest. TABLE 2: Qualitative Frequency Distribution Table of Smoking/ Non- Smoking Respondents Smoking/ Non- Smoking | Frequency | RF (%) | S | 14 | 35 | N | 26 | 65 | TOTAL : 40 | Graph INTERPRETATION The non-smoking respondents were more than the smoking respondents with 65% and 35% respectively. TABLE 3: Qualitative Frequency Distribution Table (FDT) of the Time of Visit Time of Visit | Frequency | RF
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Running head: Practical Application Scenarios Capella University MBA –Data Analysis for Business Decisions May 31, 2014 Practical Application Scenario 1. Input Variables -- | | Sample Mean (x-bar) | 3.318956 | Sample standard deviation (s): | 0.281791 | Sample Size (n) | 70 | Confidence Level: | 0.95 | | | Intermediate Calculations -- | | Degrees of freedom: | 69 | Standard Error of the Estimate: | 0.03 | Prob. in the tails for this Conf Level: | 0.05 | t-Multiple:
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we already have created by using the data given. Questions For all three data sets the data is spread significantly. This is due to standard deviation being a huge percentage of the mean. In relation to skewness, all three have different distributions; for example the income data is uniformly distributed. However the household size data is skewed to the right, this means that the mean is greater than its median. The amount charged seems to be normally distributed. Amount charged has the greatest
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3. Ralph Winkler Problem 2 The 2002 New York City Housing and Vacancy Survey showed a total of 59,324 rent-controlled housing units and 236,263 rent-stabilized units built in 1947 or later. For these rental units, the probability distributions for the number of persons
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Case Study: Chest Sizes of Scottish Militiamen. a.) Construct a relative-frequency histogram for the chest circumference data, using classes based on a single value. b.) The population mean and population standard deviation of the chest circumferences are 39.85 and 2.07, respectively. Identify the normal curve that should be used for the chest circumferences. “The associated normal curve is the one whose parameters
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Chapter 6 Case Study: Chest size of Scottish Militiamen p. 295 a. Chest size (in) | Frequency | Relative Frequency | 33 | 3 | 0.000523 | 34 | 19 | 0.003315 | 35 | 81 | 0.014131 | 36 | 189 | 0.032973 | 37 | 409 | 0.071354 | 38 | 753 | 0.131368 | 39 | 1062 | 0.185276 | 40 | 1082 | 0.188765 | 41 | 935 | 0.163119 | 42 | 646 | 0.112701 | 43 | 313 | 0.054606 | 44 | 168 | 0.029309 | 45 | 50 | 0.008723 | 46 | 18 | 0.003140 | 47 | 3 | 0.000523 | 48 | 1 | 0.000174 |
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Event Study Analysis: CLM Chapter 4 Definition: An event study attempts to measure the valuation effects of a corporate event, such as a merger or earnings announcement, by examining the response of the stockprice around the announcement of the event. One underlying assumption is that the market processes information about the event in an efficient and unbiased manner (more on this later). Event Study Analysis The steps for an event study are as follows: – – – – – – – Event Definition Selection
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