A sequence of -tuples that fills * n* -space
more uniformly than uncorrelated random points, sometimes also called a low-discrepancy
sequence. Although the ordinary uniform random numbers and quasirandom sequences
both produce uniformly distributed sequences, there is a big difference between the
two. A uniform random generator on will produce
outputs so that each trial has the same probability of generating a point on equal
subintervals, for example and . Therefore, it is possible for trials to coincidentally
all lie in the first half of the interval, while the st point still
falls within the other of the two halves with probability 1/2. This is not the case
with the quasirandom sequences, in which the outputs are constrained by a low-discrepancy
requirement that has a net effect of points being generated in a highly correlated
manner (., the next point "knows" where the previous points are).

Research design provides the glue that holds the research project together. A design is used to structure the research, to show how all of the major parts of the research project -- the samples or groups, measures, treatments or programs, and methods of assignment -- work together to try to address the central research questions. Here, after a brief introduction to research design , I'll show you how we classify the major types of designs . You'll see that a major distinction is between the experimental designs that use random assignment to groups or programs and the quasi-experimental designs that don't use random assignment. [People often confuse what is meant by random selection with the idea of random assignment. You should make sure that you understand the distinction between random selection and random assignment .] Understanding the relationships among designs is important in making design choices and thinking about the strengths and weaknesses of different designs. Then, I'll talk about the heart of the art form of designing designs for research and give you some ideas about how you can think about the design task. Finally, I'll consider some of the more recent advances in quasi-experimental thinking -- an area of special importance in applied social research and program evaluation.