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
FINAL EXAM REVIEW SESSIONS:
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:
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