Lecture 12, April 16 starts here
Time series
Data occur in time-ordered sequences is referred to as time series.
Our objective is to use past history of the series, say zt , where t is the time
index,
Lecture 7, March 5 starts here
Example. Suppose all the relevant assumptions are satisfied and we find the
least squares estimator 0 and 1 for the model y = 0 + 1 x + . Then the
correlation between0 a
Key Action 1ilerbs
Your rsum must be action oriented in order to catch the reader's eye. Listed below are a few ideas to help you start each
sentence or phrase on your resume with an action verb.
(lis
Lecture 2, Jan 29 starts here
Probability distributions.
The Normal distribution is a continuous bell-shaped probability distribution. It can be fully described by its mean and its variance. If X is n
Lecture 3, Feb 5 starts here
2
2.1
Review of calculus
Limits and derivatives
As x becomes larger, the value of 1/x become smaller. It can not reach 0,
but we can make 1/x as close to 0 as possible by
Lecture 8, March 19 starts here
5
Multiple linear regression
Instead of studying the relationship between response y and one independent
variable x, we may also use linear model to study the relations
Lecture 4, Feb 12 starts here
3.2
Matrices
A matrix is a collection of numbers ordered by rows and columns. It is
customary to enclose the elements of a matrix in parentheses, brackets, or
braces. For
Lecture 9, March 26 starts here
7
Special issues in linear regression
Indicator variables
So far the X variables in the regression model y = 0 + 1 x1 + + p xp +
are numeric. In many cases, we have ca