Econometrics Midterm 1

Front 1

stochastic error term

Back 1

A Stochastic error term is a term that is added to a regression equation to introduce all of the variation in Y that cannot be explained by the included Xs

Front 2

cross section

Back 2

Cross-sectional data refers to data collected by observing many subjects (such as individuals, firms or countries/regions) at the same point of time, or without regard to differences in time

Front 3

Residual

Back 3

the residual of an observed value is the difference between the observed value and the estimated function value.

Front 4

Dummy Variable

Back 4

is one that takes the value 0 or 1 to indicate the absence or presence of some categorical effect that may be expected to shift the outcome

Front 5

central limit theorem

Back 5

the central limit theorem (CLT) states that, given certain conditions, the mean of a sufficiently large number of independent random variables, each with a well-defined mean and well-defined variance, will be approximately normally distributed

Front 6

alternative hypothesis

Back 6

In statistical hypothesis testing, the alternative hypothesis (or maintained hypothesis or research hypothesis) and the null hypothesis are the two rival hypotheses which are compared by a statistical hypothesis test.

Front 7

type II error

Back 7

term used within the context of hypothesis testing that describes the error that occurs when one accepts a null hypothesis that is actually false.

Front 8

rejection region

Back 8

If T falls in the rejection region, the null hypothesis is rejected.

Front 9

p value

Back 9

the p-value is the probability of obtaining a test statistic at least as extreme as the one that was actually observed

Front 10

OLS

Back 10

linear least squares is a method for estimating the unknown parameters in a linear regression model.

Front 11

multiple regression

Back 11

multiple linear regression tests the relationship between several independent variables and a dependent variable

Front 12

time series

Back 12

A time series is a sequence of data points, measured typically at successive points in time spaced at uniform time intervals

Front 13

true regression line

Back 13

a smooth curve fitted to the set of paired data in regression analysis; for linear regression the curve is a straight line

Front 14

estimator

Back 14

In statistics, an estimator is a rule for calculating an estimate of a given quantity based on observed data: thus the rule and its result (the estimate) are distinguished

Front 15

total sum of squares

Back 15

The sum, over all observations, of the squared differences of each observation from the overall mean

Front 16

Gauss Markov theorem

Back 16

states that in a linear regression model in which the errors have expectation zero and are uncorrelated and have equal variances, the best linear unbiased estimator of the coefficients is given by the ordinary least squares estimator.

Front 17

null hypothesis

Back 17

test that the things you were testing are not related and your results are the product of random chance events.

Front 18

type I error

Back 18

is the incorrect rejection of a true null hypothesis

Front 19

acceptance region

Back 19

If the value of T comes out to be in the acceptance region, the null hypothesis being tested is not rejected

Front 20

level of significance

Back 20

The probability of a false rejection of the null hypothesis in a statistical test