Midterm Exam Prep Sheet PDF

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BUAD 310 Midterm Exam Information The BUAD 310 Midterm Exam will be given on Blackboard. It will be open book subject to the following ground rules. By taking this exam you implicitly consent to all rules listed in this document. Any complaints regarding these rules will be automatically dismissed. You will be required to join the Zoom meeting for the day and time of the exam. You are required to be on Zoom with your camera on the entire time of the exam. You are NOT allowed to use a virtual background. You are allowed to use any of the resources we have been using for the course (textbook, homework problems, slides from class, discussion workbooks, ExcelNow!, Zoom videos, etc.). You are NOT allowed to communicate with any other person, regardless of whether that person is in your class, for any reason (life-threatening emergencies excluded), or to use any electronic devices (e.g., phone) other than the laptop used to take the exam. You should be aware that several methods of proctoring the exam will be used. Anyone found to have violated the Academic Integrity policy will fail the course and will be reported to the USC Student Judicial Affairs office for further disciplinary action. Please read that again. This doesn’t mean an F on the exam; it means an F in the course and additional penalties up to expulsion from the University. If you are caught facilitating cheating (e.g., helping someone else), you will fail the class and be disciplined regardless of whether you benefited from it. There will be different versions of the test. Blackboard will keep track of which version you are taking. Any complaints regarding the random assignment to a particular version (e.g., I think this version is harder than my friend’s) will be automatically dismissed. The exam will have around 20 questions, all of which carry equal weight. The questions might be multiple choice, fill in the blanks, or open questions. Fill in the blanks require answers with 2 decimal digits. Open questions require clear and concise answers. Unclear answers or answers that are correct but do not directly address the question will receive no credit. The exam will be 60 minutes. It is your responsibility to arrive to the Zoom meeting on time. The exam starts and ends at the same time for everyone, regardless of when you arrived. If you arrive late, you will have less time. Late submissions will be penalized by 5% if more than 1 minute late, and by 10% if more than 2 minutes late. You will automatically receive a score of 0 if you submit more than 5 minutes late. If you cannot complete the exam following these rules due to internet problems, you will be able to take instead an oral exam on Zoom, at a different time. The oral exam will be harder to discourage faking internet problems. There will be no other way to make up the exam. I reserve the right to audit you if I suspect cheating. Be prepared to explain and justify your answers in an oral exam in case you get audited. The audit may ask you to solve similar but slightly different problems to confirm your answers were yours. Some students may be audited at random, even in the absence of any suspicion. Refusal to comply with the audit request will be interpreted as evidence of cheating and automatically result in a failing grade, as well as into a report to the USC Student Judicial Affairs office.

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Regrade requests (for open questions) will be considered if they concern objective grading errors, but they will automatically result in the entire assignment to be re-graded. It is possible that your overall grade may decrease as a result of this process. In general, if your answer is at least partially incorrect, you cannot object to the amount of partial credit given. Students who have been granted an accommodation, such as extra time, by the DSP office, will have that accommodation for this exam. They must have filed their DSP letter with me and notify me at least 10 days before the exam that they would like the accommodation for this exam. Students in a time zone where the local time when the exam is administered (8:00 AM to 9:10 AM Los Angeles time on Wednesday, March 17) is outside the interval between 7:00 AM to 11:00 PM and who would like to take the exam at a different time on that day need to let me know no later than Wednesday, March 10. They need to provide their class schedule for Wednesday, March 17 with their request. Otherwise, they will be taking the exam with the rest of the class. I will hold regular office hours on Wednesday, March 10 from 2:00 PM to 4:30 PM. You are welcome to come with specific questions or just to hang out and listen to the questions of other students. I will record that office hour session on Zoom. To be prepared for the Midterm exam, you should know and understand all topics covered before March 10th, either in class, in the application sections, on in homework assignments. For your convenience, a list of some main topics that you are expected to know for the exam is provided below. Please note that this is provided for your convenience, with absolute no guarantee of completeness. You are ultimately responsible to know what was covered in this course. The exam may include topics that I forgot to list here, if they were covered.

1. Understand the meanings of and differences between categorical, ordinal and numerical variables. 2. Understand what a distribution of a variable is and how distributions are displayed. 3. Understand and know how to use the words that describe distributions: unimodal, bimodal, skewed to the left, skewed to the right, symmetric, mode, mean, median, minimum, maximum, range, variance, standard deviation, quartile, interquartile range, percentile, robust, the five-number summary, box plot, histogram. 4. Understand how correlation is used to show the linear relationship between two quantitative variables. 5. Know how to interpret a scatterplot (form, direction, strength, positive and negative association). 6. Understand the possible values for correlation, r, and what these values mean. 7. Understand the fundamental concepts of probability theory: random phenomena, sample space, events, probability of an event, equally likely events, the possible values for probability, empirical, classical and subjective approaches to assigning probabilities, law of large numbers, the rules of probability, the intersection of two events (A and B), the union of two events (A or B), the complement of an event, disjoint or mutually exclusive events, the general law of addition, the special law of addition, conditional probability, independent events, the general law of multiplication, and the special law of multiplication for independent events. 8. Know how to develop and interpret two-way tables (also called contingency tables) 9. Know how to use two-way tables to find joint, marginal and conditional probability distributions. 10. Understand random variables: the difference between discrete and continuous random variables, probability distribution functions and cumulative distribution functions for discrete and continuous random variables, and the expected value, variance and standard deviation of a random variable. 2

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Know how to calculate the expected value and standard deviation of a discrete random variable. Know the characteristics of the Uniform distribution. Understand Bernoulli experiments and how they lead to the binomial distribution. Recognize when it is appropriate to apply the binomial distribution and how to apply it. Know how to find the expected value and standard deviation of a linear function of a random variable (e.g., Y = aX + b). For a random variable with a continuous probability distribution, know what its probability density function (PDF) and cumulative distribution function (CDF) are and how the latter is used to find the probability the random variable is less than a given number, greater than a given number, or between two given numbers. Know how to use the CDF to find a given percentile. Be familiar with the uniform and normal density curves. Know how to convert a normal density curve with mean µ and standard deviation σ into a standard normal density with mean 0 and standard deviation 1. Know how to use the appropriate Excel functions for the above distributions. Know how to use the empirical rules for normal or near-normal distributions and for the standard normal distribution. Know the key definitions in statistical inference: population, sample, survey, bias, simple random sample, estimator, estimate, parameter, statistic, unbiased estimator, population distribution, sampling distribution. Know the mean and standard error of the sample mean, 𝑋 Understand the nature of the sampling distribution of 𝑋 if the population distribution is normal. Understand the impact of sample size on the distribution of 𝑋 regardless of the shape of the population distribution (the Central Limit Theorem). Know the definition of population proportion π and the sample proportion p used to estimate it. Understand the nature of the sampling distribution of p for n large and its mean and standard deviation. Know how to construct a confidence interval for the population mean assuming you know the population standard deviation. Understand the notions of confidence level and margin of error. Understand how the width of a confidence interval is related to the confidence level, the standard error of the sample mean and the sample size. Know how to construct a confidence interval for the population mean assuming you do not know the population standard deviation. Understand the t distribution and the role of degrees of freedom and how it is used to construct a confidence interval for the population mean assuming you do not know the population standard deviation. Know how to use the appropriate Excel functions for the t distribution. Know how to construct a confidence interval for the population proportion. Know the definitions of standard error of the sample mean, 𝑋, and the standard error of the sample proportion, p. Understand the general form of the confidence interval for a population mean and a population proportion, that is, what makes up the margin of error to be added and subtracted from the sample mean or sample proportion: a t multiplier times the standard error of the sample mean or a z multiplier times the standard error of the sample proportion. Know how to calculate the sample size required to estimate a population proportion with a maximum error of ± E.

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35. Know what a hypothesis test is and how to conduct one. Know the definitions of and how to frame the null hypothesis and the alternative hypothesis. Know when to use one-tailed and two-tailed alternatives. 36. Know what Type I and Type II errors are. Understand the trade-off between the two types of errors. 37. Understand the concept of a test statistic, how to calculate it given the sample data, and how to use it to decide whether or not to reject the null hypothesis. 38. Know the definition of the p-value and how to use it to decide whether or not to reject the null hypothesis. 39. Be able to do a t-test for a hypothesis test involving the sample mean. 40. Know what it means for the evidence against the null hypothesis provided by the data to be statistically significant at level α. Know what it means for the p-value to be greater than or less than α. 41. Understand the equivalence among the notions of rejecting the null hypothesis at level α, finding a p-value less than α, and determining a t-statistic less than or greater than the value of t with α or α/2 in the appropriate tail or tails. 42. For a two-sided hypothesis test, understand the relationship between rejecting the null hypothesis at level α and whether or not the mean in t he null hypothesis is in the (1 – α)100% confidence interval. 43. Know how to do a z-test for a null hypothesis involving the population proportion. 44. Know how to use the following Excel functions in connection with the above: AVERAGE, RAND(), STDEV.S, BINOM.DIST, NORM.DIST, NORM.S.DIST, NORM.INV, NORM.S.INV, T.DIST, T.INV, T.INV.2T, IF, AND, OR.

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