Introduction to Psychology/Research Methods in Psychology

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RESEARCH METHOD IN PSYCHOLOGY.

Research psychology encompasses the study of behavior for use in academic settings, and contains numerous areas. It contains the areas of abnormal psychology, biological psychology, cognitive psychology, comparative psychology, developmental psychology, personality psychology, social psychology and others. All branches of psychology can have a research component to them. Research psychology is contrasted with applied psychology.

Research in psychology is conducted in broad accord with the standards of the scientific method, encompassing both qualitative ethological and quantitative statistical modalities to generate and evaluate explanatory hypotheses with regard to psychological phenomena. Where research ethics and the state of development in a given research domain permits, investigation may be pursued by experimental protocols. Psychology tends to be eclectic, drawing on scientific knowledge from other fields to help explain and understand psychological phenomena. Qualitative psychological research utilizes a broad spectrum of observational methods, including action research, ethography, exploratory statistics, structured interviews, and participant observation, to enable the gathering of rich information unattainable by classical experimentation. Research in humanistic psychology is more typically pursued by ethnographic, historical, and historiographic methods.

The testing of different aspects of psychological function is a significant area of contemporary psychology. Psychometric and statistical methods predominate, including various well-known standardized tests as well as those created ad hoc as the situation or experiment requires.

Academic psychologists may focus purely on research and psychological theory, aiming to further psychological understanding in a particular area, while other psychologists may work in applied psychology to deploy such knowledge for immediate and practical benefit. However, these approaches are not mutually exclusive and most psychologists will be involved in both researching and applying psychology at some point during their career. Clinical psychology, among many of the various disciplines of psychology, aims at developing in practicing psychologists knowledge of and experience with research and experimental methods which they will continue to build up as well as employ as they treat individuals with psychological issues or use psychology to help others.

When an area of interest requires specific training and specialist knowledge, especially in applied areas, psychological associations normally establish a governing body to manage training requirements. Similarly, requirements may be laid down for university degrees in psychology, so that students acquire an adequate knowledge in a number of areas. Additionally, areas of practical psychology, where psychologists offer treatment to others, may require that psychologists be licensed by government regulatory bodies as well.

Quantitative psychology involves the application of statistical analysis to psychological research, and the development of novel statistical approaches for measuring and explaining human behavior. It is a young field (only recently have Ph.D. programs in quantitative psychology been formed), and it is loosely comprised of the subfields psychometrics and mathematical psychology.

Psychometrics is the field of psychology concerned with the theory and technique of psychological measurement, which includes the measurement of knowledge, abilities, attitudes, interests, achievement in particular degree or course, and personality traits (Carl Dellomos, 2009). Measurement of these unobservable phenomena is difficult, and much of the research and accumulated knowledge in this discipline has been developed in an attempt to properly define and quantify such phenomena. Psychometric research typically involves two major research tasks, namely: (i) the construction of instruments and procedures for measurement; and (ii) the development and refinement of theoretical approaches to measurement.

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Psychology is a science, to be approached as such. Experiments should be designed using the scientific method.

There are several research methods that psychologists employ:

Approaches in Psychology Research[edit | edit source]

Nomothetic (Quantitative Approach)[edit | edit source]

This approach is basically used in inferential and descriptive statistics as both mediums of scientific method of investigation in analyzing, presenting, and interpretation of data gathered by the researcher through standardized or objective instruments (e.g. psychological Tests). The term “nomothetic” comes from the Greek word “nomos” meaning “law”. Psychologists who adopt this approach are mainly concerned with studying what we share with others. That is to say in establishing laws or generalisations. (Carl Dellomos, 2009)

Idiographic (Qualitative Approach)[edit | edit source]

This approach tends not to use inferential or descriptive statistics, but rather uses qualitative methods of data gathering such as interviews, diaries, and other written materials, obtained from or provided by the expected or anticipated respondents of a particular research. The term “idiographic” comes from the Greek word “idios” meaning “own” or “private”. Psychologists interested in this aspect of experience seek to discover what makes each of us unique. Despite the importance of our genetic individuality, proceeding from biology, the distinction between the nomothetic and the idiographic is often equated with two types of science — the natural sciences concerned with discovering laws of nature, and the social sciences concerned with individual meanings. We can examine these differences further by seeing how they relate to personality theory.(Carl Dellomos, 2009)

Both approaches were introduced by Gordon Allport. (Carl Dellomos, 2009)

Research Designs[edit | edit source]

Although there are many different kinds of research designs in psychology, studies may be categorized into descriptive or qualitative, correlational, and experimental. The method of data collection also varies, with self-report on one end of the spectrum, and naturalistic observation on the other.

Descriptive Studies[edit | edit source]

The Studies that do not test specific relationships between variables are called descriptive studies. In this research method, general or specific behaviors or attributes are observed and measured, without respect to each other. These studies are generally the design of choice for breaking into new areas, as the vast but often inconclusive amount of information collected can be drawn upon for future hypotheses.

An example of such a study would be a researcher inquiring into the quality of mental health institutions. This would be done by observation or measurements of various criteria, as opposed to relationships between variables. Alternatively, the study could be conducted without any specific criteria in mind.

Factorial Design[edit | edit source]

Every level of one independent variable is joined with every level of the others in a factorial design to create every possible combination. Because this particular design contains two variables, each of which has two levels, it is known as a 2 × 2 (or "two-by-two") factorial design. There would be six different conditions in a 3 × 2 factorial design if one of the independent variables had a third level. Observe that the product of the levels' numbers is the total number of possible circumstances. There are four conditions in a 2 × 2 factorial design, six in a 3 × 2 factorial design, twenty in a 4 × 5 factorial design, and so on. It's also important to note that every number in the notation indicates a single independent variable or component. Because this particular design contains two variables, each of which has two levels, it is known as a 2 × 2 (or "two-by-two") factorial design. There would be six different conditions in a 3 × 2 factorial design if one of the independent variables had a third level. Observe that the product of the levels' numbers is the total number of possible circumstances. There are four conditions in a 2 × 2 factorial design, six in a 3 × 2 factorial design, twenty in a 4 × 5 factorial design, and so on. It's also important to note that every number in the notation indicates a single independent variable or component.

Correlational Study[edit | edit source]

This method of statistical analysis shows the relationship between two variables. For example, research has shown that alcohol dependence correlates with depression. That is to say, the more alcohol people consume, the more depressed they become. On the other hand, it could be the other way around as well: the more depressed people become, the more likely they are to consume alcohol.

The attributes of correlations include strength and direction. The direction may be positive (both variables both increase or decrease together), negative (one variable increases while the other decreases) or unrelated (a random relationship between variables). The strength of a correlation ranges from -1 to +1 with a 0 reflecting no relationship between variables. A correlational study serves only to describe/predict behavior and not to explain it. This is so because a third variable could be shown to cause the occurrence of one of the variables. Furthermore, only experiments can prove causation.

Experiments[edit | edit source]

Experiments are generally the studies that are the most precise and have the most weight to them due to their conclusive power. They are particularly effective in proving hypotheses about cause and effect relationships between variables. A hypothesis is a prediction of how one variable relates to another. There are two types of hypotheses, null and directional. The null is a prediction that there will not be any change in the dependent variable when the researcher changes the independent variable. The directional hypothesis states that the change in the independent variable will induce a change in the dependent variable. In a true experiment, all variables are held constant except for the independent variable, which is manipulated. Thus, any changes in the experimental groups can be solely attributed to the action of the independent variable. This is called being objective.

For instance, in an experiment to test whether music improves people's memories, we would have a sheet of paper with ten unrelated words on it for people to memorize. The control group would have no music playing in the background while the experimental group would have some music in the background. Because as researchers we have adhered to the scientific method and held all variables as constant as possible, if the experimental group does report better recollection of words, then we could assume that the music had an effect on memory. However, we must be certain to do our best to ensure that any controllable differences between the two groups are eliminated in order to ensure that no confounding variable interferes with the experiment.

There are two main ways to pick, or sample the subjects in an experiment, random and stratified. In a random sampling each person has an equal chance at being picked. This means that if 80% of the population being sampled from are Christian, then 80% of the sample will be Christian. If the researcher wanted all religions represented equally, he would employ stratified sampling. For instance, the experiment could be performed only on women, or on mixed groups with equal numbers of each sex in them, to eliminate the possibility of biased results from one gender having better average memory than the other.

Steps must be taken to make sure that there is no experimenter bias. Two common forms of bias are demand characteristics and expectancy effects. If a researcher expects certain results from an experiment and influences the subjects response this is called demand characteristics. If the experimenter inadvertently interprets the information to be as expected in their hypothesis it is called expectancy effect. To counteract experimenter bias the subjects can be kept uninformed on the intentions of the experiment, which is called single blind. If the people collecting the information and the subjects giving it are kept uninformed then it is called a double blind experiment.

The experiment should also be reported so that other researchers can repeat it. If an experiment isn't repeatable it will not hold much weight in the scientific community. To help an experiment be repeatable the researcher should have the variables be measureable, this is called being empirical.

Whether researching humans or animals the experiment should be ethical. When humans are the subjects they should be informed of what the study is, consent to being in it, be debriefed afterwards, and their information should also be kept confidential.

Naturalistic Observation[edit | edit source]

Researchers study organisms in their natural environments or habitats without trying to manipulate or control anything. In this method, the researcher observes the behavior under study in its natural setting while attempting to avoid influencing or controlling it. The observations are done in a naturalistic setting without any preparation or participation of the researcher. Therefore, the behavior is observed in public places, streets, homes, and schools. Observing people from other cultures response in the same setting is a way to provide information for cross-cultural research.

Self Report[edit | edit source]

This method includes tests, questionnaires, and interviews. All of which do the same thing, give the subject a stimuli, i.e. the question, and get a response. The advantage of using these is the ability to inexpensively and rapidly collect vast amounts of data. This allows a psychologist to compare one person, or a group of peoples results to thousands of others. The disadvantage is that they are not always telling what the subject's response is but what the subject says is the response.

Information Display[edit | edit source]

Statistics[edit | edit source]

Once the information is gathered it has to be put into some kind of form, usually numerical. Statistics deals with the collection, analysis, interpretation, and presentation of numerical data. The goal of statistics is to summarize the data and let descriptions or inferences be made. Inferences are used when making predictions of the relationships of variables. Descriptions are concise displays, using statistical symbols,of the information in frequency distributions, measures of central tendency, or measures of variability.

Statistical Symbols[edit | edit source]

There are agreed upon standard symbols used in statistical displays. These symbols can be used by themselves or in equations.

N = number of scores

X = score (or scores)

M = mean

d = difference of a score from the mean

Σ = sum of

D = difference in rank

r or ρ = correlation

SD = standard deviation

Frequency Distribution[edit | edit source]

A frequency distribution is obtained by taking the score and splitting them into subgroups. The subgroups are then put on either a histogram (bar graph) or a frequency polygram (line graph). When a frequency distribution has most of the scores on one side of the graph it is considered skewed. If it has most of the scores in the middle with equal amounts on both sides it is considered symmetrical.

Measures of Central Tendency[edit | edit source]

In measures of central tendency there is one number that is used to represent a group of numbers. This number is either the mean, median, or the mode.

Measures of Variability[edit | edit source]

Variability is concerned with the dispersal of the scores, called variability i.e. are the scores clustered together or spread out. Range and standard deviation are the measures most commonly used. To find the range just subtract the number of the lowest score from the number of the highest score. This can be deceiving if most of the scores are bunched together and one of the scores is very far away from it. In this case standard deviation must be used. A formula commonly used for standard deviation is SD = the square root of Σd²/N.

Case Studies[edit | edit source]

In the course of treating a patient a psychologist will take records of problems, insights, and techniques that were important in the patients treatment. A clinical case history may be drawn upon by researchers to expose a factor that is important for understanding a behavior. Case studies repeat and are used as guides for psychologists.

Basic Concepts[edit | edit source]

  • a. independent variable = variable that one manipulates in order to see if it has any effect on the dependent variable (eg. in the example above, the independent variable would be music and its effect on memory)
  • b. dependent variable = variable that depends on the effect of the independent variable (e.g. in the example above, the dependent variable would be memory and better recollection of words)
  • c. double-blind procedure = procedure in which neither the researcher nor the subjects know which group (experimental or control) the subjects are in in order to minimize experimenter cues.
  • d. single-blind procedure = procedure in which only the researcher knows which group which kind of subject is in.
  • e. experimenter cues - subtle and often unintentional cues that the experimenter makes which implies which group which kind of subject is in. for example, if an experimenter believes that music does indeed improve memory, some cues would be the experimenter's smiling/winking at the experimental group. This smile/wink would imply to the subjects in the experimental group that the researcher is secretly implying that they're in the experimental group.
  • f. placebo effect - a treatment works because of the patient's belief that it works and not because it actually does.
  • g. experimenter - the person who is researching through the participant.
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