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Words 1802

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Beef Consumption, Pork Consumption, and Beef Price

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2. The data in the Excel spreadsheet linked below give the seasonally adjusted value of total new car sales (in millions of dollars) in the United States, total national wage and salary disbursements (referred to here as "compensation") (in billions of dollars), and the employment level in the non-agricultural sector (in thousands) for 44 consecutive quarters. An auto industry executive wants to know how well she can predict new car sales two quarters in advance using the current quarter's compensation data. How many data points can she use in a regression analysis using the data provided?

1. 41.

2. 42. * 3. 43.

4. 44.

3. The Excel spreadsheet linked below contains the simple regressions of total new car sales (in millions of dollars) on each of two independent variables: "compensation" (in billions of dollars) and "employment level in the non-agricultural sector" (in thousands). Which of the following independent…...

.... . . . . . . . . . . . . . . . . . . . . . . . . . 9.5 Limitations and Common Misinterpretations of Hypothesis Testing . . . . . . . . . . 1 1 6 10 15 17 Stat 3011 Chapter 9 CHAPTER 9: HYPOTHESIS TESTS Motivating Example A diet pill company advertises that at least 75% of its customers lose 10 pounds or more within 2 weeks. You suspect the company of falsely advertising the beneﬁts of taking their pills. Suppose you take a sample of 100 product users and ﬁnd that only 5% have lost at least 10 pounds. Is this enough to prove your claim? What about if 72% had lost at least 10 pounds? Goal: 9.1 Elements of a Hypothesis Test 1. Assumptions 2. Hypotheses Each hypothesis test has two hypotheses about the population: Null Hypothesis (H0 ): Alternative Hypothesis (Ha ): 1 Stat 3011 Chapter 9 Diet Pill Example: Let p = true proportion of diet pill customers that lose at least 10 pounds. State the null and alternative hypotheses for the diet pill example. 3. Test Statistic Deﬁnition: Test Statistic A test statistic is a measure of how compatible the data is with the null hypothesis. The larger the test statistic, the less compatible the data is with the null hypothesis. Most test statistics we will see have the following form: What does a large value of |T | reﬂect? NOTE: 2 Stat 3011 Chapter 9 4. p-value The p-value helps us to interpret the test statistic. Deﬁnition: p-value Assume H0 is true. Then the p-value is the probability...

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...technologies respondents used, but additionally how satisfied they are with those technologies. This year, we continue both with a more comprehensive report document but also with the questions regarding satisfaction with results. As was the case last year, respondents did not seem to feel that their challenges were attributable to a lack of investment in their security programs or dissatisfaction with security tools, but rather that, despite all their efforts, they still could not be certain about what was really going on in their environments, nor whether all their efforts were truly effective. This lack of visibility into the severity of threats and the degree to which threats are effectively mitigated is a perennial problem in security and it presents problems for anyone trying to make sense of the state of information security. If respondents are unsure about what is happening on their networks, one could well argue, how can they possibly provide meaningful information on a survey questionnaire? We would argue that, for typical security incidents, enterprise security departments have relatively reliable and accurate powers of observation. They generally know when one strain or another of a virus is making its way through their end-user population’s computers. They know when money goes missing from key bank accounts. And even if their perceptions on some points aren’t necessarily altogether accurate, having a gauge of the perceptions of security practitioners can be......

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...STAT 302 – Statistical Methods Lecture 8 Dr. Avishek Chakraborty Visiting Assistant Professor Department of Statistics Texas A&M University Using sample data to draw a conclusion about a population • Statistical inference provides methods for drawing conclusions about a population from sample data. • Two key methods of statistical inference: o o Confidence intervals Hypothesis tests (a.k.a., tests of significance) Hypothesis Testing: Evaluating the effectiveness of new machinery at the Bloggs Chemical Plant • Before the installation of new machinery, long historical records revealed that the daily yield of fertilizer produced by the Bloggs Chemical Plant had a mean μ = 880 tons and a standard deviation σ = 21 tons. Some new machinery is being evaluated with the aim of increasing the daily mean yield without changing the population standard deviation σ. Hypothesis Testing: Evaluating the effectiveness of new machinery at the Bloggs Chemical Plant Null hypotheses • The claim tested by a statistical test is called the null hypothesis. The test is designed to assess the strength of the evidence against the null hypothesis. Usually the null hypothesis is a statement of “no effect” or “no difference”, that is, a statement of the status quo. Alternative hypotheses • The claim about the population that we are trying to find evidence for is the alternative hypothesis. The alternative hypothesis is one-sided if it states that a parameter is larger than or...

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...Distinguish between product and period costs. Explain the difference between a merchandising and a manufacturing income statement. Indicate how cost of goods manufactured is determined. Explain the difference between a merchandising and a manufacturing balance sheet. Identify trends in managerial accounting. Questions 1, 2, 3 Brief Exercises 1 Do It! 1 Exercises 1 A Problems B Problems *2. 4, 5, 6, 7, 8 11, 12 2, 3 1 *3. 4, 5, 7 2 2, 3, 4, 5, 6 3, 4, 5, 7, 13 8, 12, 13, 14, 15, 17 1A, 2A 1B, 2B *4. 13 6 2 1A, 2A 1B, 2B *5. 9, 14 3A, 4A, 5A 3B, 4B, 5B *6. 15, 16, 17, 18 8, 10, 11 3 8, 9, 10, 11, 12, 13, 14, 15, 16, 17 14, 15, 16, 17 3A, 4A, 5A 3B, 4B, 5B *7. 10, 19, 20, 21 9 3A, 4A 3B, 4B *8. 22, 23, 24 25, 26 4 18 *Note: All asterisked Questions, Exercises, and Problems relate to material contained in the appendix to the chapter. Copyright © 2012 John Wiley & Sons, Inc. Weygandt, Managerial Accounting, 6/e, Solutions Manual (For Instructor Use Only) 1-1 ASSIGNMENT CHARACTERISTICS TABLE Problem Number 1A 2A 3A Description Classify manufacturing costs into different categories and compute the unit cost. Classify manufacturing costs into different categories and compute the unit cost. Indicate the missing amount of different cost items, and prepare a condensed cost of goods manufactured schedule, an income statement, and a partial balance sheet. Prepare......

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...Forcing early retirements Forcing early retirement is a huge problem, there are rumours that there is a case of forcing early retirements at Loxley. Forcing early retirement is the involuntary ending of one's career because of a layoff, health problems or disability. Age discrimination means employers fail to hire or promote a worker or avoid training a staff member based on his age. Forcing an employee into early retirement based exclusively on age is also discriminatory. Employer discrimination also involves firing an employee or forcing the staff member to quit before earning company retirement benefits. One of the reasons why older workers would be forced into early retirements is due to the fact that younger workers earn less pay compared with senior workers and managers. Eliminating a division of senior staff saves money and also eliminates imminent company retirement benefits by letting the older workers go before the official retirement age. Using the bottom 10 employees as a sample of the entire 144 employees, we find that the correlation between the number of years an employee is at the company is lowly correlated with their performance score. The correlation coefficient is 0.2071 The top 10 employees’ correlation coefficient is 0.2964 This tells us that the number of years that an employee has been with the company does not affect the employees’ score by much. This leads to reason that the rumors about the company forcing early retirements have no substance...

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...What is “Statistics”? Data collection Chapter 1 of text “a way to get information from data” A framework for dealing with variability A way to make decisions under uncertainty Statistical inference: the problem of determining the behaviour of a large population by studying a small sample from that population Why is statistics important in business? Financial management (capital budgeting) Marketing management (pricing) Marketing research (consumer behaviour) Operations management (inventory) Accounting (forecasting sales) Human resources management (performance appraisal) Information systems Economics (summarising, predicting) See http://www.youtube.com/watch?v=D4FQsYTbLoI What is a population? What is a sample? Population: a collection of the whole of something – e.g. all female students of ANU; all people who live in Tuggeranong; all people who play the flute. Sample: a set of individuals drawn from a population e.g. the female students in STAT1008 are a sample of all female students at ANU. If we have a population…. We can get parameters – true values for things like the centre and spread of the population We know the answers – what proportion are this tall? We look at the population and get the answer. If we have a sample… We can get statistics – these are values that estimate the parameters e.g. sample centre and sample spread used to estimate population centre and population spread We have to use inference to do this estimation – what proportion are......

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...equal in length to the confidence interval. d) None of the above 4. Excluding an outlier point from your data in simple regression analysis, in general leads to: a) A significantly different slope as compared to the case where you do not exclude the point from your data b) Imprecise estimates of the intercept c) Significantly changes the value of index of fit d) Does not significantly change the regression equation e) None of the above 5. The Durbin-Watson test is used in Regression to test for a) Normality of Errors b) Constant standard deviation for Errors c) Correlation between Response and Errors d) Straight line type relationship between the Predictors and response e) None of the above Word Problems Question 1 (20 points) – Simple Regression 1. The following pairs of values give X, Narco Medical's advertising expense during a period (in hundreds of dollars), and Y, the amount of the company's sales (in thousands of dollars) for the period: Advertising , X ( in hundreds of $): 8 9 7 6 5 1 Sales, Y (in thousands of $): 15 11 10 11 8 5 | | | | | | | | |Advertising |Sales | | | | | |X |Y |X^2 |Y^2 |X*Y | | |8 |15 |64 ...

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...The Performance Test Can it produce good performance as measured by the ﬁrm’s proﬁtability, ﬁnancial and compe44ve strengths, and market standing? Strategy Analysis – How to gain a competitive advantage. What do you think the Mission and Vision for this business is? What is the problem or issue to be resolved? Finance, HR, Marketing, growth opportunity, merger or acquisition etc Objectives - (What do you think this firm would like to accomplish over the next 5 years?) Situation analysis (SWOT) What internal strengths and weaknesses does this company have? How well is the firm’s present strategy working? What are the firm’s competitively important resources and capabilities? Is the firm able to take advantage of market opportunities and overcome external threats to its external wellbeing? Are the firm’s prices and costs competitive with those of key rivals, and does it have an appealing customer value proposition? Is the firm competitively stronger or weaker than key rivals? What strategic issues and problems merit front-burner managerial attention? 9 What external environmental opportunities and threats (driving forces) should this company be aware of? PEST Analysis - Political, Economic, Social, Technology • global forces (trade policy) • general economic conditions • social forces (values attitudes) demographic, technology the natural environment......

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...applets at streaming plug-in. If you are still having any technical difficulty – please call ALEKS at 1-714-6197090, or me at 916-813-9027. They are open from 5 am to 6 p.m. PST. 7. Assessments Be prepared for the dreaded assessment – most students who have not already had statistics usually are unable to answer any of the questions – please, please do not let this intimidate you – I had many students who got a zero on the first assessment finish the course with an A! 8. Binder Print out the syllabus and Detailed Chapter Objectives for your binder. You will use this binder when taking the assessments, tests and the final. Keep the schedule of deadlines (last page of the syllabus) and all your printed ALEKS explanations and written problem solving work in the binder. 9. Deadlines Do absolutely everything in your power to stay on the schedule in the syllabus – I give you a lot of lead time in the beginning of the semester but by the second week you have to - have to – have to stay on schedule. These objectives need to be done on time so that you can be prepared for the online exams which expire at midnight on the given deadline dates! Employers are looking for employees who have soft skills of being on time and meeting deadlines. Establish the commitment and determine to be disciplined now. Missing the deadlines could very well cost you an A since the total deadline points is 100 points equal to the points for one exam. The complete schedule is given on the last......

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...NORTHEASTERN UNIVERSITY - GRADUATE SCHOOL OF BUSINESS ADMINISTRATION MGSC 6200: DATA ANALYSIS Spring, 2015 Instructor Information Name: Dr. Nizar Zaarour E-mail address: n.zaarour@neu.edu Office: 214 Hayden Hall Office hours: Monday and Wednesday: 12 – 2 PM and by appointment. Course Overview The objectives of this course are: (1) To provide you with an understanding of statistical methods and techniques and their usefulness in the decision-making process, (2) To expose you to the methods of descriptive and inferential statistics and how can be used to solve business problems, (3) To improve upon your data analysis and computer skills, (4) To help you develop the skills to recognize the appropriate statistical tool to analyze business problems, and (5) To provide you with the necessary tools for critical evaluation, correct interpretation, and presentation of the results of statistical analyses. Textbook and Software 1) Business Statistics: For Contemporary Decision Making, 7th Edition, by Ken Black, (Wiley). 2) Microsoft Excel. Course Organization The course web page is located in the Blackboard system at http://blackboard.neu.edu. Course materials and announcements will be posted on the course site. A Blackboard tutorial is available at http://www.discoveringblackboard.neu.edu. The textbook is quite easy to read and covers a lot of ground. However, some of the topics are not covered in depth. Class discussions, handouts, and my lecture notes will fill these......

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...use 0.75. Plotting the Binomial Probabilities 1. Create plots for the three binomial distributions above. Select Graph > Scatter Plot and Simple then for graph 1 set Y equal to ‘one fourth’ and X to ‘success’ by clicking on the variable name and using the “select” button below the list of variables. Do this two more times and for graph 2 set Y equal to ‘one half’ and X to ‘success’, and for graph 3 set Y equal to ‘three fourths’ and X to ‘success’. Paste those three scatter plots below. Calculating Descriptive Statistics Open the class survey results that were entered into the MINITAB worksheet. 2. Calculate descriptive statistics for the variable where students flipped a coin 10 times. Pull up Stat > Basic Statistics > Display Descriptive Statistics and set Variables: to the coin. The output will show up in your Session Window. Type the mean and the standard deviation here. Mean: 4.600 Standard deviation: 1.429 Short Answer Writing Assignment – Both the calculated binomial probabilities and the descriptive statistics from the class database will be used to answer the following questions. 3. List the probability value for each possibility in the binomial experiment that was calculated in MINITAB with the probability of a success being ½. (Complete sentence not......

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...and insufficient sample size, each of which can cause errors. Inattention to any of these potential flaws will invalidate survey results. DISADVANTAGES OF SAMPLING 1. Requires selection of relevant stratification variables which can be difficult. 2. Is not useful when there are no homogeneous subgroups. 3. Can be expensive to implement. Disadvantages of Sampling through different sampling methods: 1. Simple random sample: Disadvantages: * Difficult to obtain * Due to its very randomness, "freak" results can sometimes be obtained that are not representative of the population. In addition, these freak results may be difficult to spot. Increasing the sample size is the best way to eradicate this problem. 2. Systematic Sample: Disadvantages: * Can introduce bias where the pattern used for the samples coincides with a pattern in the population. 3. Stratified Sampling: Disadvantages: * Nothing major, hence it's used a lot 4. Quota Sampling: Disadvantages: * Not a genuine random sample * Likely to yield a biased result 5. Cluster Sampling: Disadvantages: * Not a genuine random sample * Likely to yield a biased result (especially if only a few clusters are sampled) HAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA Disadvantage of Sampling through few Sampling methods: 4. cluster sampling Higher sampling error, which can be expressed in the so-called "design effect", the ratio between......

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...chosen out of the male students and the sample proportion of smokers is found to be 0.2. Give an interval based on your data so that you are 95% confident that the true value of the unknown proportion lies inside it. How would you explain 95% confidence to a layman? Suppose a professor of IIMA thinks that true proportion is 0.3. Are you ready to accept the professor’s perception based on your data at 99% confidence level? Solution – 1 Sample Size n = 100 (male smokers) p = 0.2 Sd (P) = √(pq / n) = .04 95% confidence interval of p = 0.2 ± 2 x 0.04 = 0.08 to 0.32 Explanation to a layman – 95% confidence means that if the sampling experiment i.e. selection of random samples of 100 male smokers in the present problem, is repeated large no of times, 95% of the times the interval will include the true value of p (0.2) or the sample proportion of smokers in present example and 5% of the times the interval may not include the true value of p (0.2) or the sample proportion of smokers in present example. 99 % confidence interval of p = 0.2 ± 2.58 x .04 = .04 to 0.35 Based on our data, as the true proportion of 0.3 thought by the IIMA professor lies in the 99% confidence interval, we can accept IIMA Professor’s perception....

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...STAT 346/446 - A computer is needed on which the R software environment can be installed (recent Mac, Windows, or Linux computers are sufficient).We will use the R for illustrating concepts. And students will need to use R to complete some of their projects. It can be downloaded at http://cran.r-project.org. Please come and see me when questions arise. Attendance is mandatory. Topics covered in STAT 346/446, EPBI 482 Chapter 5 – Properties of a Random Sample Order Statistics Distributions of some sample statistics Definitions of chi-square, t and F distributions Large sample methods Convergence in probability Convergence in law Continuity Theorem for mgfs Major Theorems WLLN CLT Continuity Theorem Corollaries Delta Method Chapter 7 – Point Estimation Method of Moments Maximum Likelihood Estimation Transformation Property of MLE Comparing statistical procedures Risk function Inadmissibility and admissibility Mean squared error Properties of Estimators Unbiasedness Consistency Mean-squared error consistency Sufficiency (CH 6) Definition Factorization Theorem Minimal SS Finding a SS in exponential families Search for the MVUE Rao-Blackwell Theorem Completeness Lehmann-Scheffe Location and scale invariance Location and scale parameters Cramer-Rao lower bound Chapter 9 - Interval Estimation Pivotal Method for finding a confidence interval Method for finding the “best” confidence interval Large sample confidence......

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...have purchased vehicles at Whitners. Team D, after reviewing the provided data, knows that over the past couple years the car dealer’s average selling price for an automobile was $22,000. Team D’s null hypothesis states that the selling prices in the data set remain unchanged from the established $22,000 average. However, Team D has faith that its alternate hypothesis that the average has changed will prevail. The following will provide the purpose of the research, problem definition, research hypothesis, and a look ahead to the following weeks concerning the study. Using historic and current data, Team D intends to prove the $22,000 average price of a car has changed, and most likely increased due to many factors. If Team D’s alternate hypothesis proves true, then Whitners Autoplex has been charging far more less than surrounding, or even nationwide, auto dealers. Knowing the average cost of a vehicle is important to auto dealers because profit is what allows a business to prosper and grow. Problem Team D, believes the prices of vehicles has changes among the years. Team D, wants to gather information in order to find out why is it that the prices for a vehicle has varied among the years and among car dealers. Whitners Autoplex average price for a new vehicle is $22,000, while the national average for a vehicle in the United States is $30,748. As one can see, there is a great difference between the average at Whitners Autoplex and the national average.......

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