ECO220Y1Y; Fall 2011/Winter 2012
FINAL EXAM BULLETIN BOARD: This bulletin board contains information about the April 2012 final examination for ECO220Y1Y. It is relevant for ALL sections. Students in Sections L0101, L0201, L0301, L0401, L0501 will all take the SAME exact final exam. All students answer all questions.
EXAM TIME, DATE, AND LOCATION: The examination will be three hours long. The time, date, and locations are set by Arts & Science: check here.
FORMAT: Here are the actual instructions for the final exam that explain the format in detail
SCANTRON form: It is strongly recommended that you bring a pencil and an eraser. Here is a sample blank SCANTRON form and a sample SCANTRON form with top portion correctly filled in.
Formulas and statistical tables: Aid sheets including formulas and statistical tables will be attached to Part 1 of the final exam. During the final exam you may detach the aid sheets. You are NOT permitted to bring your own aid sheets.
WHAT TO BRING: Bring the following with you to the examination room:
Student ID card (i.e. T-card)
Pencils and an eraser
Non-programmable calculator
COVERAGE: The final examination is cumulative. With respect to the first Canadian Edition of Business Statistics by Sharpe, De Veaux, Velleman, and Wright (2011) and for the chapters listed below you are responsible for all sections except those specifically excluded (in parentheses).
Chapter 1: An Introduction to Statistics
Chapter 2: Data
Chapter 3: Surveys and Sampling
Chapter 4: Displaying and Describing Categorical Data
Chapter 5: Displaying and Describing Quantitative Data
Chapter 6: Randomness and Probability (Excluding Section 6.9)
Chapter 7: Scatterplots, Association, and Correlation (Excluding Section 7.4)
Chapter 8: Introduction to Linear Regression
Chapter 9: Random Variables and Probability Distributions (Excluding Sections 9.5, 9.7 and 9.11)
Chapter 10: Sampling Distributions
Chapter 11: Confidence Intervals for Proportions (Excluding Section 11.5 )
Chapter 12: Testing Hypotheses About Proportions
Chapter 13: Confidence Intervals and Hypothesis Tests for Means
Chapter 18: Inference for Regression
Chapter 19: Understanding Residuals
Chapter 20: Multiple Regression (Excluding Section 20.7)
Chapter 21: Building Multiple Regression Models
RELATIVE WEIGHTING OF MATERIAL: The material in the second term is weighted more heavily in the final examination: roughly three-fourth of the final examination will focus on material from Chapters 12, 13, 18-21 in the first Canadian Edition of Business Statististics by Sharpe, De Veaux, Velleman and Wright.
MANAGING YOUR TIME: Try to avoid two common mistakes: (1) rushing through the multiple choice questions and spending too much time on the long questions and (2) getting bogged down on a question and not leaving enough time for a good attempt at every question. You might want to formulate a plan of attack before you arrive at the exam.
ACADEMIC INTEGRITY: Let's have a positive exam environment where everyone behaves with integrity and treats each other with respect. When the end of the exam is announced immediately put down your writing instruments: no extra time is permitted (not even for writing your name, which you need to do during the regular allotted time). You may not have a cell phone or any other device (aside from a non-programmable calculator). Not immediately stopping when time is called or having a device in your possession (even if you do not use it) constitute academic offices and U of T deals harshly with these. Needless to say, communication during the exam or possession of unauthorized aids also constitute academic offences. Remember to cover your answers: you are committing serious academic misconduct if you do something that makes it easier for someone else to copy your work. Do not write your answers to the multiple-choice questions in large font next to each question: the Office of Academic Integrity investigates cases where this behavior is spotted. Despite our large numbers, students in our course have an excellent record regarding academic integrity and while violations and serious consequences have occurred they have been relatively rare. Let us continue to behave in a way that is clearly professional and marked by integrity.
PRACTICE FINAL EXAMINATIONS & ADVICE:
While practice final exams are helpful, they should not be the focus of your preparations. Advice to help you use them most effectively:Take each question in a quiet place where you can concentrate and time yourself. If a practice question is worth 12 points out of 100 and the exam is 3 hours then write that question in 21.6 minutes or less (=12/100*180). This gives you practice doing your best while under pressure. For effective practice, work within the time-budget, use the aid sheets you will be given, work without your notes/book, and write out your best answer.
If you do not know how to do a problem, do NOT look at the solutions. Instead write out your best attempt. If you feel your best attempt is poor, use this as an indicator that you need to study the related material. BEFORE peeking at the solutions study your notes, the book, and your homeworks and try the practice problem again.
When you feel you have your best answer, use the solutions grade yourself.
Given the breadth and depth of our course, all important skills and knowledge cannot be covered in a single three-hour final exam. Hence, while old exams give a good indication about format, expectations, and level of analysis expected, they are not comprehensive study guides. Your textbook, lecture notes, and problems sets highlight the important components of our course. [In brackets are questions you should skip because we did not cover these topics this year.]
Exam April/May 2011 (Soln) [Skip multiple choice question 7 and short answer question # 2]
Exam April/May 2009 (Soln) [Skip multiple-choice questions 9-11 and short answer questions 2, 3 and 5]
Exam April/May 2008 (Soln) [Skip multiple-choice questions 13-14 and short answer questions 2 and 4]
Exam April/May 2007 (Soln) [Skip multiple-choice question 18 and short answer question 1]
Exam April/May 2006 (Soln) [Skip multiple-choice questions 15, 18, 19]
Exam August 2007 (Soln) [Skip multiple-choice questions 20 and short answer question 1]
Exam August 2006 (Soln) [Skip multiple-choice questions 2, 11, 12 and short answer question 2]
key topics: Here is a list of key topics that you should know very well:
Describing data with graphs: histograms (frequency, relative frequency and density)
Describing data with statistics: sample mean, median, mode, variance, standard deviation, covariance, coefficient of correlation, percentiles, tabulations
Sampling error
Making informal inferences using graphs and statistics (for example, inference about the shape of the population by looking at a histogram of a sample)
Non-sampling errors and biases these errors cause
Probability (including probability used in finding sampling distributions and in statistical inference)
Working with expected values
Continuous and discrete distributions
Binomial distribution
Normal distribution (Bell curve)
Student t and F distributions
Sampling distributions
Fundamental concepts for all of statistical inference: sample vs. population, sample statistics vs. population parameters, sample size, sampling error & sampling distributions, non-sampling errors, observational versus experimental data (relevant for all topics below), when you can infer causality, significance levels (conventional choices by researchers are between 0.01 and 0.10; 0.05 is the most common)
How and when to use the two different methods of statistical inference: estimation and hypothesis testing
Concepts related to estimation: point and interval estimators, interpretation of confidence interval estimators, when you can infer causality, things that cause bias
Concepts related to hypothesis testing: rejection region, critical values, test statistics, p-value, Type I error, Type II error, significance level, test of statistical significance, one versus two tailed tests, power, burden of proof, when you can infer causality, failing to reject the null hypothesis does NOT support the inference that it is true, difference between statistical significance and significance in general (i.e. economic significance)
Link between estimation and hypothesis testing
Inference about a population mean
Inference about a population proportion
Inference using regression analysis: what a regression model is, required conditions for the error variable, how it is estimated, properties of estimators, how to calculate intercept and slope (simple regression), how to interpret parameter estimates, standard error of estimate, standard errors of parameter estimates, SSR, SSE, SST, measures of model fit (R-squared and adjusted R-squared), statistical tests of coefficients, confidence interval estimators of parameters, using estimates for prediction (simple regression), heteroscedasticity, outliers, statistical tests of overall model fit (F test)
Multiple regression and model building; dummy variables (indicator variables); interaction terms; quadratic terms; violations of the required assumptions
For everything above: being able to correctly interpret results, explain concepts and draw valid and meaningful conclusions