APA Project - Survey Research Plan (Assignment #1 )

TIPS ON READING RESEARCH REPORTS

You have probably already recognized that reading a professional article in psychology is somewhat different from other reading that you do. Here is some advice for those who are new at reading research reports in psychology.

Format of Journal Articles

There is no single “right” way to read a journal article, however, the following strategy may work well for you. A typical article has five main sections: abstract, introduction, method, results, and discussion. Below are a few pointers to consider about each section.

Abstract. The abstract provides a quick overview of the research problem, the methods used, the main findings, and the conclusions to be drawn from the study. The abstract is probably the single most important paragraph in the article, and deserves special attention. If you read the abstract carefully (and perhaps more than once), it will be easier to follow the rest of the article.

· Abstract read at least once.

Introduction. The introduction sets the stage for the study by describing the central issue of interest, and briefly reviewing previous research on the topic. The introduction also presents the rationale for the research, that is, the reasons for undertaking this particular study. The introduction specifies the goals of the research, and the research strategy to be used. In some articles, the research problem will be stated in the form of specific hypotheses. After reading the introduction, you should be able to answer the following questions about the study:

· Why is this study important? 


· What questions will this study answer (hint: look for the hypotheses)? 


· How does this study build on previous research?




Method. The method section describes in detail how the study was conducted. This section usually begins with a description of the participants who took part in the research. Next, the materials used in the study such as questionnaires or standardized laboratory tasks are described. The method section also includes a step-by- step description of the specific procedures used in the research. 


· In reading the method section, try to imagine what it was like to be a participant in the study. 


· After reading the method section you should be able to describe from start to finish what the 
researcher did and how he or she did it. 


Results. The results section describes the data that were collected and the ways in which the data were analyzed. Statistical analyses are presented here. Because space in professional journals is limited, authors must juggle the need to be clear and detailed against the need to be concise. Tables and figures are often used to summarize information efficiently, and you should be sure to look at them carefully. After reading the results section, you should be able to answer these questions:

· What were the main findings?

· Did the results support the original hypotheses?

· Were there any important but unexpected results?

Discussion. The discussion section evaluates and interprets the results. This is where the research can consider the implications of the study, and compare its findings to results from previous research. Authors sometimes also comment on limitations or special features of their research that may have affected the results, or propose directions for future studies. After reading the discussion section, you should be able to answer these questions: 


· What have I learned from this research? 


· How have these findings helped me to understand the original research problem identified in the 
introduction? 


By the way, A Few Words about Statistics:

For many people, the most intimidating aspect of reading professional articles in psychology is confronting the statistical analyses of data in the results section. Such terms as “log-linear analysis” or “analysis of covariance” may seem mysterious and perplexing. Whereas you cannot be expected to understand the specifics of sophisticated data analyses that go beyond you level of training, even articles with the fanciest of statistics should also state the key findings in plain English--which you should understand. Try to read the results section carefully, and understand what each particular analysis is designed to accomplish and how specific results are interpreted. Some of the basic abbreviations and statistical terms you will encounter are explained below.

Analysis of Variance: A statistical procedure that uses an F-test to assess the degree of difference between the mean scores of two or more groups.

ANOVA: Abbreviation for analysis of variance.

Chi Square: A measure of the degree of association between two categorical variables, abbreviated as X2. [A categorical variable has named categories, not numerical values; religious is a categorical variable with such categories as Catholic, Jewish, Protestant, etc.]

Correlation: A measure of the degree of relationship between two variables (e.g., intelligence and income), sometimes abbreviated as r. A correlation can range between -1 (perfect negative relationship) and +2 (perfect positive relationship); r = 0 means there is no relationship between the variables.

Factor analysis: A statistical procedure for uncovering common dimensions or factors that link variables together; a researcher might use this statistical procedure to see if a 20-item questionnaire has distinct subscales.

F or F-test: The F statistic is obtained from an F- test used to assess the degree of difference between the mean scores of two or more groups.

Log-linear analysis: A statistical procedure for determining the degree of association between categorical (named) variables.

M: Abbreviation for the mean or average score.

N or n: Abbreviation for the number of participants in a study or subgroup.
 ns: Abbreviation for not statistically significant.
 p: Abbreviation for probability or significance level. This refers to the likelihood that a pattern of results could have occurred by chance; p =01 means that there is only a 1% probability that the observed result occurred by chance.

r: Abbreviation for correlation (see above). Regression analysis A statistical procedure that allows the researcher to predict the value of one variable given the value of one or more other variables.

Reliability: Refers to the degree to which test scores are reproducible and consistent over time.
 SD: Standard deviation. This term refers to how much scores vary around the mean score; a large SD means that there is much variation in scores.

Statistical significance: A result, such as a difference in scores between two groups, is said to be statistically significant if it is unlikely to have occurred by chance. For example, if a group difference is significant at the “.05 level,” the probability is only 5% that a difference of this size occurred by chance.

t or t-test: The t statistic is obtained in a t-test used to assess the degree of difference in mean scores between two groups.


Validity: Refers to the degree to which a test or instrument measures what it is intended to measure.

Adapted from: Peplau, L. A. (1988). Introduction: Reading research reports in social psychology. In L. A. Peplau, D. O. Sears, S. E. Taylor, & J. L. Freedman (Eds.), Readings in social psychology: Classic and contemporary contributions (2nd ed., pp. 1-5). Englewood Cliffs, NJ: Prentice Hall.

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