1. Google vs. PsycINFO:

a. Google yields more results and a greater variety in its types of sources along with a higher rate of relevancy but less currency.

b. PsycINFO tends to be more specific than Google which may return many irrelevant results. For example, searching PsycINFO for tension will find only publications related to psychological and biological tension, but searching Google for tension will obtain results for mechanical and physical tension as well, which may not be relevant for your research.

c. With PsycINFO, there are many more metadata fields than Google Scholar. In the case of Google Scholar, much of this metadata is not as easily available as in PsycINFO (e.g. the latest revisions and exact descriptors). The related articles feature of Google does not have enough depth to satisfy a scholar or professional.

d. Google is very user friendly, but it is less in-depth than PsycINFO.

e. Google is good at finding information quickly. PsycINFO requires more effort as it has more data and metadata.

2. Induction:

Induction is employed, for example, in the following argument:

· Every star we know of is spherical.

· All stars must be spherical in order to exist.

Inductive reasoning permits the possibility that the conclusion is false, even where all of the premises are true  For example:

· All of the people we have seen are less than 8 feet tall.

· All people are less than 8 feet tall.

Deduction is employed, for example, in the following argument:

· All stars are spherical

· We have found an object in outer space that is not spherical

· Therefore, what we have found is not a star.

3. Between-subjects design:

a. A “between-subjects” experiment is where you use two (or more) different groups - e.g. attitudes between those who have seen a TV program and those who haven't. The dependent variable is the attitude of the people, and the independent variable is whether they’ve seen the program or not.

b. Within subjects design is where you use the same subjects twice. e.g. measure people's attitude to nuclear power before they see a documentary on the Chernobyl disaster and then after. It's "within subjects" because you are measuring the change in the variable among the same subjects. The dependent variable is the attitude of the people, and the independent variable is whether they’ve seen the documentary or not.

4. 2x2 Factorial Design: Suppose you want to analyze the total power used by each of two different engines, A and B, running at each of two different speeds, 4000 or 6000 RPM. The 2x2 factorial experiment would consist of four experimental units: engine A at 4000 RPM, engine B at 4000 RPM, engine A at 6000 RPM, and engine B at 6000 RPM. Each combination of a single level selected from every factor is present once.

5. Stratified vs. proportionate stratified sampling: Stratified sampling is the process of separating members of a population into homogeneous subgroups prior to sampling. The strata should be mutually exclusive, i.e. each member of the population must be assigned to one and only one stratum. The strata should also be collectively exhaustive: no member should be left out. Proportionate allocation uses a sampling fraction in each of the strata that is proportional to that of the total population. For instance, if the population consists of 60% in the plant stratum and 40% in the animal stratum, then the relative size of the two samples (three plants, two animals) should reflect this proportion.