...Stat 141 R1 - Lecture #35 Announcements: 1) Assignment #11 Question 5: The answer is wrong … should be “fail to reject” but MyStatLab wants “reject”... so give the wrong answer for full marks in this question 2) Exam: STAT 141 R1 3 hrs 1400 Wed Apr 17 MAIN GYM, ~45 Multiple Choice Questions Chapters 7, 8, 18-28 …. some pre MT skills will be required. Simple Linear Regression …. continued Last time: Ex) Predicting final exam marks (%) from midterm exam marks (%) in a class of 88 students: Student | #1 | #2 | … | #88 | Midterm mark | 67% | 72% | … | 88% | Final mark | 62% | 50% | … | 91% | Stat 141 R1 - Lecture #35 page 2 Given x = midterm percentage, y = final percentage, n=88, x = 67.812, y = 52.643, sx = 17.922, sy = 25.430, r = 0.718 ∑(yi–ŷi)2 = 27278.82 We had calculated: The slope and intercept of the sample line of best fit: * sample line of best fit: y= -16.443 + 1.019 x An estimate for σ (standard deviation about the population line): se Given SSE = ∑(yi–ŷi)2 = 27278.82 : se2=SSEn-2=27278.8288-2=317.196 →σ≈se=317.196=17.810 Stat 141 R1 - Lecture #35 page 3 Inference for the population slope β1 When the 4 basic assumptions of the SLR model are satisfied: o The relationship between x and y is sufficiently linear. Presuming linearity, this means, at any x, με = 0. o The std. dev. of ε is the same for any particular x (constant). o The...
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...expected to be positive. The fact that one of them has the wrong sign (βS) may reflect negative omitted variable bias. Multicollinearity obviously is a problem and may be responsible for the wrong sign of βS too. Variable S looks irrelevant but it should be relevant in theory. Its small t-stat may be due to omitted variable or multicollinearity. Q2. Using the intuition from simple case of omitted variable: (a) y = apple consumption, x1 = price of banana, x2 = price of orange yt = 0 + 1 x1,t + 2 x2,t + ut If we leave out x2, bias on β1 depends on (1) whether x1 and x2 are correlated in the sample which mostly likely is positive (e.g. inflation), and whether price of orange has positive or negative effect on the annual consumption of apple in the population (sign of 2) which should be positive too (law of demand). Bias is (+) (+) = (+) (b) y = student grades on the midterm, x1 = hours studies for the midterm x2 = hours slept before the midterm If we leave out x2, bias on β1 depends on (1) whether x1 and x2 are correlated in the sample which mostly likely is negative, and (2) whether hours slept before the midterm has positive or negative effect on the midterm grade in...
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...recent study of 460 drivers age 70 and over by the National Highway Traffic Safety Administration reported that 75% of those drivers had uncorrected vision problems. Answer: The report of the ‘traffic safety administration’ reported that 75% (345 people) was the reported statistic from the 460 drivers of 70 or older drivers. I feel the assumed parameter would be the population of drivers that had uncorrected vision that were 70 years old or older. 4. What type of sampling procedure was used to collect the data in the MM207 Student Data Set? Answer: The sampling procedure used, believe was the ‘Conveyance’ sampling because this was a population which was readily available. STATISTICS, MM207, ‘Midterm Project’ Andre Bergman, 4-20-2014 Page, 2 of 3 5. From the MM207 Student Data Set identify one...
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...ca Lectures: Monday, Wednesday, Friday: 1.30pm to 2.20pm. Room: ARTS 143 Coordinator: Dr. Lawrence Chang, 236 McLean Hall. E-mail: chang@math.usask.ca Office hours: Please e-mail your instructor or the coordinator to make an appointment at a mutually convenient time. You should e-mail him a day or two in advance and not at the last minute. Lab Schedules: Every student is required to register in either one of the following 4 labs. 1. L01: Thursday, 2.30pm to 3.50pm. Room: ARTS 133 2. L03: Thursday, 4.00pm to 5.20pm. Room: ARTS 133 3. L05: Thursday, 2.30pm to 3.50pm. Room: THORV 271 4. L07: Thursday, 4.00pm to 5.20pm. Room: ARTS 134 First lab: Thursday 13 Sept 2012. Last lab: Thursday 29 November 2012. The lab periods will be devoted to midterm tests and to discussing homework problems. The lab is an essential part of this course. Previous terms have shown that students who skip labs tend not to do well and have a high chance of failing this course. Therefore, you are strongly advised to attend labs. Textbook: Mathematical Analysis for Business and Economics by Schelin and Bange. Customised copies are available in the U. of S. Bookstore. This course will cover Chapters 1 to 6 and part of Chapter 7. Website: To access the course website, go to https://bblearn.usask.ca and log in using your NSID and password. In the blackboard MATH 121...
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...STAT 2000 Midterm Exam # 1 Review Sheet Descriptive Statistics 1. Data, categorical variable, quantitative variable, identifier 2. Population, sample, census, parameter, statistic 3. Sampling designs: simple random, stratified and cluster samplings 4. Data presentation (a) Categorical variable: frequency tables, bar chart, pie chart (b) Quantitative variable: histogram, five-number summary, boxplots 5. Descriptive statistics: mean x, median, mode, range, interquartile range (IQR), variance s2 , ¯ standard deviation s. They are used to describe shape, center and spread of the distribution. 6. Percentiles: 25th = Q1 , 50th = median, 75th = Q3 etc. Correlation and Linear Regression 1. Scatterplot, y (dependent, response) variable, x (independent, explanatory) variable 2. Correlation (linear association between 2 variables) and correlation coefficient r = interpretations, properties, conditions, lurking variables, effect of outliers 3. Linear model: y = b0 + b1 x, where b1 = r(sy /sx ) and b0 = y − b1 x. ˆ ¯ ¯ 4. Interpretations of predicted value y , slope b1 and intercept b0 in problem context. ˆ 5. R2 = r2 : fraction of y’s variability accounted for by linear regression on x Probability 1. Trial, sample space, sample points, events 2. Three types of probability: theoretical, empirical and personal 3. Contingency table: joint probability and marginal probability 4. Notation: A, Ac , A ∩ B, A ∪ B, Venn diagram 5. Complement rule: P (Ac ) = 1 − P (A) 6. Addition rule: P (A ∪ B) = P (A)...
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...Question 1 # sold | P(x) | 0 | 0.1 | 1 | 0.11 | 2 | 0.2 | 3 | 0.23 | 4 | 0.3 | 5 | 0.06 | Question 2: The average rate of occurrence of accidents was 8.15 per week. A) during that time, what is the probability of getting less than 3 accidents a week? Use poisson for this question. Since it is less that 3 accidents, x = 0,1,2 (Px=o) = [(8.15^0) (e^8.15)] / 0! = 0.00288735. (Px=1) = [(8.15^1) (e^8.15)] / 1! = 0.002353193. (Px=2) = [(8.15^2) (e^8.15)] / 2! = 0.009589362. Add all these results together, and p(x<3) is 0.01223119. B) The probability if an accident on the road is 0.295. Out of 10 reportable accidents, what is the probability that 2 occurred on the road? Use Binomial for this. Since it is exactly 2, we need to find P(x=2). Use the binomial formula, n = 10, x = 2, p = 0.295, and q is 0.705. = 10!/2!(10-2)! * 0.205 ^2 * q^ 10-2. Answer is 0.23898436. Question 3: 15% of drivers have a probationary license and 85% have a regular license. In a given year, 10% of drivers with probationary licenses are involved in an accident. 2.5% of regular drivers are involved in an accident. For this question it is better to draw a tree diagram. Question 4: Mean values for income for men are 100K, for woman, 80K. SD deviations of 20K and 15K respectively. Variables are normally distributed and independent. Calculate the 95th percentile, for men income. 95th p = 0.95. In the zscore table, we find a value of 1.64. Us e the formula for z-score (population) : 1...
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... The calculation we made to compute the debt is as follows: = Total current liabilities + Total long-term debt and other non-current liabilities - Cash and cash equivalents - Trades payables = 2647961 + 6410751 - 1330441 - 1202398 D = 11.5915 billions The proportion of debt is then: D/D+E = 0.3328 B. Estimation of the cost of debt rD According to the financial statement, the average interest rate for Debt and Financing Arrangements, which corresponds actually to long-term notes, was 4.28% for the fiscal year 2012. After that we wanted to estimate the cost of bonds. To do so we found the Heinz’s credit rating, which is BBB . We then looked at the future bonds that Heinz is going to issue, and decided to take the bond with a midterm maturity as representative debt of the company. P=400 C=3.125% Price=101.4 Since the company is rated BBB, the default rate is d=0.4%. We have found a y = 3.38% using the formula seen in the course. To get the final rD we...
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...FRE 6023 Fall 2007 Midterm Exam Polytechnic University Professor Barry Blecherman Tuesday 23 October 2007 This is an open-book, open-note, open-computer exam – there is no reason that I can anticipate that you’ll need a computer, but you may use one if you wish to. Please do not speak unless asking me a question and please keep your eyes focused on your own work. Please keep your handwriting neat, and remember that I can only give full/partial credit if I understand what you’ve written. Do the problems in any order – just make sure that I can tell which problem your answer corresponds to. This is a 2.5-hour exam. When you are finished, please put the white exam questions inside your Blue Book before turning in your exam. Good luck! Part I – Short Essay Please use one or two paragraphs to answer each of these 10 questions (4 points each) 1. Name an organization not mentioned in your text that you believe has primary goals other than profit – what goals do you think they seek? 2. Suppose that many US universities rely on international graduate students as a primary revenue source. Suppose further that something happens which causes the number of student visas issued by the US government to fall dramatically. How does this change supply and demand for graduate education in the short-run? What long-run changes would occur if the number of visas granted remained low? Draw pictures of the short-run and long-run changes to supply and demand. 3...
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...EECE 350/450 Computer Networks Spring 2013 Course information Catalogue Description A course that outlines data communications; wide area networks; circuit and packet switching; routing; congestion control; local area networks; communications architecture and protocols; internetworking. Pre-requisites By topic: • Programming language (such as C++) • Basic understanding of probability theory and data structures • Basic understanding of the internal operations of computers By course: • STAT 230 Probability and Random Variables, and EECE 330 Data Structures and Algorithms. Instructor Ayman Kayssi Office: 404, Raymond Ghosn Building (RGB) Office Hours: Monday 2 – 3:30 pm and by appointment Extension: 3499 Email: ayman@aub.edu.lb Web: aub.edu/~ayman Messaging: +961 3 965 258 LinkedIn: lb.linkedin.com/in/aymankayssi Twitter: akayssi Facebook: akayssi Course objectives The objectives of this course are to give students: An understanding of the basic principles of computer networking An overview of the main technologies used in computer networks An overview of internetworking principles and how the Internet protocols, routing, and applications operate The basic background in computer networks that will allow them to practice in this field, and that will form the foundation for more advanced courses in networking The basic skills needed to write network applications. Topics covered in this course ...
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...ACC 312 Fundamentals of Managerial Accounting Midterm Exam 1, Spring 2014 Test Form A SOLUTION Name ______________________________________________________________________ UTEID ____________________________________ Instructor ____________________________________________ Class Days ___________________ Time ______________________ DO NOT OPEN until given instructions to do so. Instructions Pages are numbered sequentially, including this page. Confirm that you have 11 pages. 1. Answers to Multiple-Choice Questions (first two sections) should be recorded on the Scantron. A. On your Scantron answer sheet, write and bubble in your name, UTEID, and the “Test Form” letter noted above. B. Use a #2 pencil only to mark your responses on your Scantron answer sheet. Mark clearly and erase completely as needed. Only the multiple-choice answers marked on your Scantron answer sheet will be graded. C. The time allotted for an exam includes the time required to “bubble-in” your Scantron answer sheets. It is cheating to take extra time to bubble in the answer sheet after time is up for the exam. 2. Answers to Problems should be recorded on the exam where indicated. Show your work legibly in the space provided or attach scratch paper. 3. Cell phones, books, notes, PDAs and programmable calculators are NOT allowed at your desk during the exam. Calculators capable of storing text are NOT allowed. 4. In the interest of minimizing disruptions and making sure all...
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...COMM 291 Midterm Review Package Prepared by Angelica Cabrera 1. INTRODUCTION TO DATA AND VARIABLES Categorical vs. Quantitative Data Categorical Limited number – distinct categories No Quantitative Large number Yes Possible values for variable Measurement units? EXAMPLE. Which variables are quantitative and which are categorical? Employee # Age (years) Annual Income (in Performance 1,000s of dollars) Rating (1-5 scale) 5543 48 50 – 100 4.5 2431 34 20 – 49 3.9 7281 31 0 – 19 3.4 Job Type Management Clerical Maintenance 2. SURVEYS AND SAMPLING Population: _______ individuals with a common characteristic that you want to generalize about Parameter: fact or characteristic about _____________ Sample: ________ of population Statistic: fact or characteristic about ______________ EXAMPLE. Mattel claims that less than 5% of all its Hot Wheels toys are defective. When testing 100 Hot Wheels toys from a production run of 7000 toys, 7% were found to be defective. What is the: a) Population? c) Parameter? Poor (Biased) Sampling Convenience sampling: Choosing respondents that are __________ to obtain Voluntary response: Respondents volunteer, so those with __________ opinions are more likely to respond b) Statistic? d) Sample? Sampling Designs 1. Simple Random Sampling (SRS): Every individual has an equal chance of being selected 2. Stratified Random Sampling: Divide population into ______________ subgroups and randomly select from each stratum 3. Cluster Random...
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...computer skills • To overcome either too little or too much information • To develop technical literacy • To improve career mobility 2 Business Statistics π ∑θ Lecturer: Business Statistics Ammara 3 Business Statistics π ∑θ Lecture Overheads and Textbook Lecture overheads: posted on the Business Statistics Group Group name: business_statistics_bba Group home page: http://groups.yahoo.com/group/business_statistics_bba Group email: business_statistics_bba@yahoogroups.com before the week in which lectures are given. Textbook: Richard I. Lavin and David S. Rubin, “Statistics for Management”, Prentice Hall, New York,7th edition(2000) 4 Business Statistics π ∑θ • • • • Assessment Final Examination: Midterm Examination: Quizzes/Homework/Term Project: Total: 45% 35% 20% 100% 5 Business Statistics Regular work and study is the key to success π ∑θ • It can never be emphasised strongly enough how true this is for Business Statistics • This course rewards those students who put constant effort into it over the semester 6 Business Statistics π ∑θ How to do well in the class Statistics is a problem-solving subject. Practice in problem solving, and completing and understanding the assigned reading and homework are essential to success on the exams. Suggestions for success in the class: • Attend all lectures. I will not “read from the book” and you will not necessarily find the examples from lecture in the textbook. • Attend...
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...3100 Intermediate Financial Accounting I Course Outline – Fall 2014 Instructor: Carla Carnaghan, Ph.D., CISA, CMA Office & Hours: Calgary Campus office, 5:00 – 6:00pm Thursdays. Please email for appointment, and for alternative times. Office hours may be done in person, with Webex, or by phone, and for smaller issues with email. E-mail: Carla.Carnaghan@uleth.ca (emails received in the evening, particularly after 10 PM, may not be responded to until the next day) Telephone: 1- 403-329-2351 (Lethbridge office – Please use e-mail where possible) Class Times: Y Section: Th 1800-2050 (S6013A) Course Web Page: on Moodle Course Pre-requisites* Prerequisites: MGT 2400; ECON 1010 and 1012 and STAT 1770 or admission to the CA Bridging Program/Professional Diploma in Accounting; a minimum C- grade is required in all prerequisite courses; MGT 3040 (co-requisite) * It is the responsibility of students to check the prerequisites for courses before registration. If students are registered in a course for which they do not have the prerequisites, and they have not received prior permission from the appropriate program chair, they can be de-registered. If this occurs after the drop/add date, tuition will not be refunded. Course Objectives Building from MGT 2100, this course examines the accounting concepts, principles, judgments, and techniques used in recording business events and preparing and presenting financial...
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...|Topic |Reading Assignment | |Introduction to OM and SCM |Chapter 1 | |Competitiveness, Strategy, & Productivity |Chapter 2 | |Supply Chain Management |Chapter 15 | |Forecasting |Chapter 3 | |Product and Service Design |Chapter 4 | |Exam 1 – Online 6/11 from noon to midnight |Chapters 1-4, & 15 | |Capacity Planning |Chapter 5 | |Process Selection and Facility Layout |Chapter 6 | |Location Planning and Analysis |Chapter 8 | | Quality Management |Chapter 9 | |Exam 2– Online 6/19 from noon to midnight |Chapters 5, 6, 8, 9 | |Statistical Quality Control |Chapter...
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...Econometrics (Economics 360) Syllabus: Spring 2015 Instructor: Ben Van Kammen Office: Krannert 531 Office Hours: Friday, 10 a.m.-noon Email: bvankamm@purdue.edu Meeting Location: KRAN G010 Meeting Days/Times: TR 1:30-2:45 p.m. (001) TR 3-4:15 p.m. (002) TR 4:30-5:45 p.m. (003) Course Description This is an upper division economics course required for students pursuing a BS in economics. It is one of the few courses that explicitly covers empirical methods, i.e., the analysis of observed economic behavior in the form of data. Empirics stand in contrast to theory, e.g., micro and macro, about how agents behave. Despite this under-representation, empirical analysis comprises a large part of economists’ workload and is one of the most practical skills that an economics student can learn. Course Objectives In this class students will: 1. perform statistical and practical inference based on the results of empirical analysis, 2. identify useful characteristics of estimators, e.g., unbiasedness, consistency, efficiency, 3. state predictions of theoretical economic models in terms of testable hypotheses, 4. model economic relationships using classical methods, such as Ordinary Least Squares, derive the properties of estimators related to these methods, and 5. perform estimation using methods discussed in class using software, 6. perform diagnostic tests that infer whether a model’s assumptions are invalid, 7. evaluate empirical models based on whether their resulting estimators...
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