Fact = an objective statement, usually based on direct observation, that reasonable observers agree is true.
Theory = an idea, or conceptual model, that is designed to explain existing facts and make prediction about new facts that might be discovered.
Hypothesis = Any prediction about new facts that is made from a theory
Important lessons scientific research
1. The value of skepticism. The ideal scientist always tries to disprove theories, even those that are his or her own.
- Parsimony/ Occam's razor: when there are two or more explanations that are equally able to account for a phenomenon, the simplest explanation is usually preferred.
2. The value of careful observations under controlled conditions. To test hypotheses scientists control the conditions in which they make observations so as to rule out alternative explanations.
3. The problem of observer-expectancy effects. Science is carried out by people who come to their research with certain expectations. In psychology, the subjects may perceive the observer's expectations and behave accordingly.
Research strategies
1. Research designs: experiments, correlational studies, descriptive studies
2. Setting: field, lab
3. Data-collection: self-report, observation
Research designs
Experiments
An experiment is the most direct and conclusive approach to testing a hypothesis about a cause-effect relationship between two variables. The variable that is hypothesized to cause some effect on another variable is called the independent variable, and the variable that is hypothesized to be affected is called the dependent variable. An experiment can be defined as a procedure in which a researcher systematically manipulates one or more independent variables and looks for changes in one or more dependent variables while keeping all other variables constant.
- Within-subject experiments each subjects is tested in each of the different conditions of the independent variabele.
- Between-groups experiments, there is a separate group of subjects for each different condition of the independent variabele. Random assignment is regularly used in between-group experiments to ensure that the subjects are not assigned in a way that could bias the result.
Correlational studies
A correlational study can be defined as a study in which the researcher does not manipulate any variable, but observes or measures two or more already existing variables to find relationships between them. Correlational studies can identify relationships between variables, which allow us to make predictions about one variable based on knowledge of another; but such studies DO NOT tell us in any direct way whether change in one variable is the cause of change in another.
Descriptive studies
The aim of research is to describe the behavior of an individual or set of individuals without assessing relationships between different variables.
Setting
A laboratory study is any research study in which the subjects are brought to a specially designated area that has been set up to facilitate the researchers collection of data or control over environmental conditions. Field study is any research study conducted in a setting in which the researcher does not have control over the experiences that a subject has.
The lab allows the researchers to collect data under more uniform, controlled conditions than are possible in the field. However, the strangeness or artificiality of the lab may induce behaviors that obscure those the researcher wants to study.
Data-collection methods
Self report methods are procedures in which people are asked to rate or describe their own behavior or mental state in some way. One form of self-report is introspection, the personal observation of one's thoughts, perception and feeling.
Observational methods include all procedures by which researchers observe and record the behavior of interest rather than relying on subjects self-reports. In one subcategory, tests, the researchers deliberately presents problems, tasks or situations to which the subject responds.
- Naturalistic observation, the researcher avoids interfering with the subjects' behavior.
- Hawthorne effect: the alteration of behavior by the subjects of a study due to their awareness of being observed. One technique for minimizing the Hawthorne effect takes advantage of the phenomenon of habituation, a decline in response when a stimulus is repeatedly or continuously present.
Descriptive statistics
Descriptive statistics include all numerical methods for summarizing a set of data.
- Mean is simply the arithmetic average, determined by adding the scores and dividing the sum by the number of scores.
- The median is the center score.
- Variability refers to the degree to which the numbers in the set differ from one another and from their mean
- Standard deviation is a common measure of variability
When variables are measured numerically, the strength an direction of the relationship can be assessed by a statistic called the correlation coefficient. Correlation coefficient produces a result ranging from -1.00 to +1.00. The sign (+ or -) indicates the direction of correlation. In a positive correlation, an increase in one variable coincides with a tendency for the other variable to increase; in a negative correlation, an increase in one variable coincides with a tendency for the other variable to decrease. A correlation close to zero means that the two variables are statistically unrelated.
Inferential statistics
Any set of data collected in a research study contain some degree of variability that van be attributed to chance. Inferential statistic help researchers decide how confident hey can be in judging that the results observed are not due to chance.
P or the level of significance: when two means are being compared, p is the probability that a difference as great as or greater than that observed would occur by chance (in larger population) if there were no difference between the two means. In other word, in the case of comparing two means in an experiment, p is the probability that a difference observed would occur if the independent variable had no real effect on the scores. By convention results are labeled as statistically significant if the value of p is less than 0.05 (5%).
Components of statistical significance:
1. The size of observed effect. Other things being equal, a large effect is more likely yo be significant than a small one.
2. The number of individual subjects or observations in the study. Other things being equal, results are more likely to be significant the more subjects or observations included in research study.
3. The variability of the data within each group.
! Don't confuse statistical significance with practical significance.
Bias
Bias = nonrandom effect caused by extraneous factors, must be avoided.
Three types of bias: sampling bias, measurement bias, expectancy bias.
In terms of biased samples, one problem that psychological scientists run into is that human subjects who are easily available to be studies maybe not be representatieve of the greater population.
Reliability and validity of measurements
Reliability has to do with measurement error, not bias. A measure is reliable to the degree that it yields similar results each time it is used with a particular subject under a particular set of conditions, sometimes referred to as replicability.
A second type of a reliability os interobserver reliability: the same behavior seen by one observer is also seen by a second observer. This requires that the behavior in question be carefully defined ahead of time. This is done by generating an operational definition, specifying exactly what constitutes an example of your dependent measure.
Validity is a critical issue than reliability because of lack of validity can be a source of bias. A measurement procedure is valid if it measures or predicts what it is intended to measure or predict.
Face validity: the test measures what it's supposed to measure.
Criterion validity: measures how well one measure predicts an outcome for another measure.