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ECON 2740 (5)
Final

# Final Exam Review

5 Pages
218 Views

School
University of Guelph
Department
Economics
Course
ECON 2740
Professor
David Prescott
Semester
Winter

Description
Key Equations and Concepts Random Discrete Variable- the random variable ▯ can taken any of a finite number of different values (for example, a six sided die) Random Continuous Variable- the random variable ▯ can take any of an infinite number of numerical values Variance- the average squared deviation of ▯ from its mean ▯ ▯ ▯ ▯▯▯▯▯▯▯ ▯ ▯ ▯ ▯▯ ▯▯▯ ▯ ·▯▯▯ ▯ ▯ ▯ Standard Deviation- the average deviation of ▯ from its mean (also the squared variance) ▯▯▯ ▯▯▯ ▯ ▯▯▯ σ▯ ▯ ▯▯ Coefficient Variation - a unit free measure that can be used to compare to things ▯▯ ▯▯ ▯ ▯▯▯▯ Sample Quartiles- quartiles divide data into for equal parts, or quartiles - ▯ ▯second quartile) is also the median - The position of the first quartil▯ is found using the first equation, and the vale by the ▯ second equation ▯ ▯ ▯▯ ▯ 1▯▯ ▯ 4 ▯ ▯ 0.75▯ ▯ 0.25▯ ▯ ▯ ▯ - The position of the third quartile is found usingthe first equation, and the vale by the ▯ second equation ▯ ▯ ▯▯▯1 ▯ ·3▯ ▯ 4 ▯ ▯ 0.25▯ ▯▯.75▯ ▯ Sample Median- the value that lies in the middle of the data set, and the position can be found using the first equation, and the value using the second equation ▯▯ ▯ 1▯▯ ▯▯▯ 2 ▯▯▯05.▯ ▯ ▯0.5▯ ▯ Interquartile Range- the interquartile range contains the middle 50% of ordered observations, or the values in between the first and third quartiles ▯▯ ▯ ▯ ▯▯ ▯ ▯ Moments- there are four moments is statistics, summarized in the following table Momen t Associated Statistics First Mean Second Variance Third Skew Fourth Kurtosis Set- a set is a collection of objects, and subsets are contained in the set Compliment- denoted ▯ or ▯ , it contains all the elements not in ▯ Union- denoted ▯ ∪▯ , is every element contained in both ▯ and ▯ - Note ▯ ∪▯ ▯ ▯ ∩▯ and are all the elements not in ▯ and ▯, so the unshaded area in the following diagram - ▯▯▯▯∪▯ ▯▯ ▯▯ ▯▯ ▯▯ ▯▯ ▯ ▯▯▯▯ ▯ ∩▯ ▯▯ Intersection- denoted ▯ ∩▯ , is the set of elements in both ▯ and ▯ Mutually Exclusive- two subsets are mutually exclusive if their intersection is empty, so ▯ ∩▯▯0 Collectively Exhaustive- every element in ▯ is in at least on of ▯,▯ or ▯, so ▯ ∪▯∪▯▯▯ Partition- every element of ▯ is in one of the subsets that defines the partition and no element is in more than on subset Conditional Probability- the probability of event ▯, given that event ▯ has occurred ▯ | ▯ ▯▯▯ ∩▯▯ ▯ ▯ ▯ ▯ ▯▯▯▯▯▯▯▯ Statistical Independence- if the occurrence or non-occurrence of ▯ does not change the probability of ▯, thand ▯ and ▯ are statistically independent ▯ ▯ ▯ ▯▯ ▯ ▯ ▯ ▯ ▯ ▯ ▯▯ ▯ ▯ ▯ ▯ ▯ ∩▯ ▯ ▯▯ ▯ ·▯ ▯▯ ▯ Symmetry- if the mean and median are equal, the distribution is symmetric, but if the mean and median are not equal we cannot say the distribution is not symmetric Co-Variance- the average of the product of deviations - Does not measure how close the data points are to the major axis ▯▯▯ ▯,▯ ▯ 1▯▯ ▯ ▯▯▯▯▯̅▯▯▯▯▯▯▯▯ Major Axis- the slope is the ration of the two standard deviations ▯ and ▯ Correlation Coefficient- measures how close the data points are to the major axis - It is also unit free
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