RESEARCH STRATEGIES

A. Scientific Method:

1. Begin with theory

2. Develop hypothesis – the testable prediction

3. Description – gather information about variables of interest

Operationalize variables -

•To define, establish parameters of variables

•Primary methods of Freud & Piaget

•Lengthy, time-consuming

•Usually ex post facto

a. Case Study – study one or more individuals in depth

METHODS:

b. Naturalistic Observation

•Going out into the “field”, observing subject in their natural environment

•No interaction between researcher and subjects•Researcher must carefully record results

•Could result in misinterpretation by researcher

Sample – group of items (subjects) selected from population

Population – all cases from which a sample may be drawn

•Study behaviors & attitudes of sample group, generalize to larger population

c. Survey

•Sample MUST BE RANDOM – every person in group has chance of being selected

•Sample must be representative of population

•The bigger the sample, the better!

•Sample could be stratified – only a particular group within pop. is sampled

•Avoid bias in wording

•Have a significant response before going forward

d. Interview•One – on – one directed conversation between 2 peoplee. Correlation Study

•Measuring the relationship between variables

•Positive correlation – variables change together – as one increases the other also increases, OR as one decreases, the other decreases                           

The correlation coefficient is the numerical value of the relationship (represented by r)

The closer r is to a whole 1.0, the stronger the correlation

Negative correlation – variables move in opposite directions

The graph is called a scatter plot, a line of best fit is extended through the data points

CORRELATION DOES NOT PROVE ANYTHING!!

The evidence of a relationship may lead to further research to prove causation

•Beware of illusory correlations (spurious correlation)– an apparent relationship where there is none

Super Bowl winner & stock market rise correlated from 1972 to 1985

•Also beware of confounding variables – another variable not taken into consideration (also called intervening or lurking variable)

=

? Does smoking correlate with low grades?

Confounding variable – smokers more likely to be partiers

•Also, recognize and avoid potential confounding variables- variables you didn’t consider, which had an effect

Controlled variables -

•Variables that should be equalized in both subject selection & assignment to group

Gender Race/ethnicity

Age

Socioeconomic level

• Identify population, take random sample

*Most powerful research tool – allows conclusions about cause and effect

f. Experiment (experimental design)

Experiment ALWAYS has:

1. Independent variable

•Experimental factor manipulated & controlled by experimenter

2. Dependent variable

3. Experimental Condition (group)

4. Control Condition (group)

•Behavior observed & measured, affected by the indep. variable

•The condition exposed to the indep variable

•The condition that LACKS the indep variable•It serves as comparison to the experimental group

•Control condition may receive a placebo (then called placebo condition)

Experiment may be single blind or double blind

Researchers must avoid biasing the results with:

1. Experimenter bias

2. Sample bias (among the worst mistakes)

3. Demand Characteristics

4. Hawthorne Effect

* Same group of people could be both experimental & control condition

-Be aware of Barnum effect

4. Analyze data

A variety of statistical methods may be used

5. Draw conclusion

6. Replicate (!!)STATISTICS:

“There are three kinds of lies:

lies, damned lies, and statistics.” Benjamin Disraeli

(often attributed to Mark Twain)

Measures of central tendency -

Mode – the most frequently occurring score

*could be unimodal, bimodal or multimodal

Mean – the average

Median – the middle score in a distribution

Variation among scores:

Range – the gap between the highest and lowest scores in a distribution

A perfect distribution has the same mean, median and mode (and forms a bell{normal} curve)

A normal curve

Standard deviation: measure of how much scores vary from the mean

The equation:

The steps:

1. Order scores from low to high

2. Find the mean of the scores

3. Find the difference between each score and the mean (this is the deviation of each score)

4. Square each deviation

5. Find the average of the squared deviations (this is the variance)

6. Find the square root of # 5

These percentages of scores within a standard deviation are always the same:

Score of 130 = z score of 2

S.D. also provides z scores – number of S.D. from the mean