We understand the world by asking questions and searching for answers. Our construction of reality depends on the nature of our inquiry.  Until the sixteenth century, human inquiry was primarily based on introspection. The way to know things was to turn inward and use logic to seek the truth. This paradigm had endured for a millennium and was a well-established conceptual framework for understanding the world. The seeker of knowledge was an integral part of the inquiry process.  A profound change occurred during the sixteenth and seventeenth centuries. Copernicus, Kepler, Galileo, Descartes, Bacon, Newton, and Locke presented new ways of examining nature. Our method of understanding the world came to rely on measurement and quantification. Mathematics replaced introspection as the key to supreme truths. The Scientific Revolution was born.  Objectivity became a critical component of the new scientific method. The investigator was an observer, rather than a participant in the inquiry process. A mechanistic view of the universe evolved. We believed that we could understand the whole by performing an examination of the individual parts. Experimentation and deduction became the tools of the scholar. For two hundred years, the new paradigm slowly evolved to become part of the reality framework of society. The Age of Enlightenment had arrived.  Scientific research methodology was very successful at explaining natural phenomena. It provided a systematic way of knowing. Western philosophers embraced this new structure of inquiry. Eastern philosophy continued to stress the importance of the one seeking knowledge. By the beginning of the twentieth century, a complete schism had occurred. Western and Eastern philosophies were mutually exclusive and incompatible.

Then something remarkable happened. Einstein's proposed that the observer was not separate from the phenomena being studied. Indeed, his theory of relativity actually stressed the role of the observer. Quantum mechanics carried this step further and stated that the act of observation could change the thing being observed. The researcher was not simply an observer, but in fact, was an integral part of the process. In physics, Western and Eastern philosophies have met. This idea has not been incorporated into the standard social science research model, and today's social science community see themselves as objective observers of the phenomena being studied. However, "it is an established principle of measurement that instruments react with the things they measure." (Specter, 1981, p. 25) The concept of instrument reactivity states that an instrument itself can disturb the thing being measured.  Problem Recognition & Definition.  All research begins with a question. Intellectual curiosity is often the foundation for scholarly inquiry. Some questions are not testable. The classic philosophical example is to ask, "How many angels can dance on the head of a pin?" While the question might elicit profound and thoughtful revelations, it clearly cannot be tested with an empirical experiment. Prior to Descartes, this is precisely the kind of question that would engage the minds of learned men. Their answers came from within. The modern scientific method precludes asking questions that cannot be empirically tested. If the angels cannot be observed or detected, the question is considered inappropriate for scholarly research.

A paradigm is maintained as much by the process of formulating questions as it is by the answers to those questions. By excluding certain types of questions, we limit the scope of our thinking. It is interesting to note, however, that modern physicists have begun to ask the same kinds of questions posed by the Eastern philosophers. "Does a tree falling in the forest make a sound if nobody is there to hear it?" This seemingly trivial question is at the heart of the observer/observed dichotomy. In fact, quantum mechanics predicts that this kind of question cannot be answered with complete certainty. It is the beginning of a new paradigm.  Defining the goals and objectives of a research project is one of the most important steps in the research process. Clearly stated goals keep a research project focused. The process of goal definition usually begins by writing down the broad and general goals of the study. As the process continues, the goals become more clearly defined and the research issues are narrowed.  Exploratory research (e.g., literature reviews, talking to people, and focus groups) goes hand-in-hand with the goal clarification process. The literature review is especially important because it obviates the need to reinvent the wheel for every new research question. More importantly, it gives researchers the opportunity to build on each other’s work.  The research question itself can be stated as a hypothesis. A hypothesis is simply the investigator's belief about a problem. Typically, a researcher formulates an opinion during the literature review process. The process of reviewing other scholar's work often clarifies the theoretical issues associated with the research question. It also can help to elucidate the significance of the issues to the research community.  The hypothesis is converted into a null hypothesis in order to make it testable. "The only way to test a hypothesis is to eliminate alternatives of the hypothesis. Statistical techniques will enable us to reject a null hypothesis, but they do not provide us with a way to accept a hypothesis. Therefore, all hypothesis testing is indirect.  Creating the Research Design Defining a research problem provides a format for further investigation. A well-defined problem points to a method of investigation. There is no one best method of research for all situations. Rather, there are a wide variety of techniques for the researcher to choose from. Often, the selection of a technique involves a series of trade-offs. For example, there is often a trade-off between cost and the quality of information obtained. Time constraints sometimes force a trade-off with the overall research design. Budget and time constraints must always be considered as part of the design process  Many authors have categorized research design as either descriptive or causal. Descriptive studies are meant to answer the questions of who, what, where, when and how. Causal studies are undertaken to determine how one variable affects another. P2M INFOTECH state that the two characteristics that define causality are temporal sequence and concomitant variation.  The word causal may be a misnomer. The mere existence of a temporal relationship between two variables does not prove or even imply that A causes B. It is never possible to prove causality. At best, we can theorize about causality based on the relationship between two or more variables, however, this is prone to misinterpretation. Personal bias can lead to totally erroneous statements. For example, Blacks often score lower on I.Q. scores than their White counterparts. It would be irresponsible to conclude that ethnicity causes high or low I.Q. scores. In social science research, making false assumptions about causality can delude the researcher into ignoring other (more important) variables.

There are three basic methods of research: 1) survey, 2) observation, and 3) experiment. Each method has its advantages and disadvantages.

 The survey is the most common method of gathering information in the social sciences. It can be a face-to-face interview, telephone, or mail survey. A personal interview is one of the best methods obtaining personal, detailed, or in-depth information. It usually involves a lengthy questionnaire that the interviewer fills out while asking questions. It allows for extensive probing by the interviewer and gives respondents the ability to elaborate their answers. Telephone interviews are similar to face-to-face interviews. They are more efficient in terms of time and cost, however, they are limited in the amount of in-depth probing that can be accomplished, and the amount of time that can be allocated to the interview. A mail survey is generally the most cost effective interview method. The researcher can obtain opinions, but trying to meaningfully probe opinions is very difficult.  Observation research monitors respondents' actions without directly interacting with them. It has been used for many years by A.C. Nielsen to monitor television viewing habits. Psychologists often use one-way mirrors to study behavior. Social scientists often study societal and group behaviors by simply observing them. The fastest growing form of observation research has been made possible by the bar code scanners at cash registers, where purchasing habits of consumers can now be automatically monitored and summarized.  In an experiment, the investigator changes one or more variables over the course of the research. When all other variables are held constant (except the one being manipulated), changes in the dependent variable can be explained by the change in the independent variable. It is usually very difficult to control all the variables in the environment. Therefore, experiments are generally restricted to laboratory models where the investigator has more control over all the variables.

Sampling

 It is incumbent on the researcher to clearly define the target population. There are no strict rules to follow, and the researcher must rely on logic and judgment. The population is defined in keeping with the objectives of the study.  Sometimes, the entire population will be sufficiently small, and the researcher can include the entire population in the study. This type of research is called a census study because data is gathered on every member of the population.  Usually, the population is too large for the researcher to attempt to survey all of its members. A small, but carefully chosen sample can be used to represent the population. The sample reflects the characteristics of the population from which it is drawn.  Sampling methods are classified as either probability or no probability. In probability samples, each member of the population has a known probability of being selected. Probability methods include random sampling, systematic sampling, and stratified sampling. In no probability sampling, members are selected from the population in some nonrandom manner. These include convenience sampling, judgment sampling, quota sampling, and snowball sampling. The other common form of no probability sampling occurs by accident when the researcher inadvertently introduces no randomness into the sample selection process. The advantage of probability sampling is that sampling error can be calculated. Sampling error is the degree to which a sample might differ from the population. When inferring to the population, results are reported plus or minus the sampling error. In no probability sampling, the degree to which the sample differs from the population remains unknown.

Random sampling is the purest form of probability sampling. Each member of the population has an equal chance of being selected. When there are very large populations, it is often difficult or impossible to identify every member of the population, so the pool of available subjects becomes biased. Random sampling is frequently used to select a specified number of records from a computer file.  Systematic sampling is often used instead of random sampling. It is also called an nth name selection technique. After the required sample size has been calculated, every nth record is selected from a list of population members. As long as the list does not contain any hidden order, this sampling method is as good as the random sampling method. Its only advantage over the random sampling technique is simplicity.  Stratified sampling is commonly used probability method that is superior to random sampling because it reduces sampling error. A stratum is a subset of the population that shares at least one common characteristic. The researcher first identifies the relevant stratums and their actual representation in the population. Random sampling is then used to select subjects for each stratum until the number of subjects in that stratum is proportional to its frequency in the population.  Convenience sampling is used in exploratory research where the researcher is interested in getting an inexpensive approximation of the truth. As the name implies, the sample is selected because they are convenient. This no probability method is often used during preliminary research efforts to get a gross estimate of the results, without incurring the cost or time required to select a random sample.  Judgment sampling is a common no probability method. The researcher selects the sample based on judgment. This is usually an extension of convenience sampling. For example, a researcher may decide to draw the entire sample from one "representative" city, even though the population includes all cities. When using this method, the researcher must be confident that the chosen sample is truly representative of the entire population.  Quota sampling is the no probability equivalent of stratified sampling. Like stratified sampling, the researcher first identifies the stratums and their proportions as they are represented in the population. Then convenience or judgment sampling is used to select the required number of subjects from each stratum. This differs from stratified sampling, where the stratums are filled by random sampling.

 Snowball sampling is a special no probability method used when the desired sample characteristic is rare. It may be extremely difficult or cost prohibitive to locate respondents in these situations. Snowball sampling relies on referrals from initial subjects to generate additional subjects. While this technique can dramatically lower search costs, it comes at the expense of introducing bias because the technique itself reduces the likelihood that the sample will represent a good cross section from the population.  Data Collection There is very few hard and fast rules to define the task of data collection. Each research project uses a data collection technique appropriate to the particular research methodology. The two primary goals for both quantitative and qualitative studies are to maximize response and maximize accuracy.  When using an outside data collection service, researchers often validate the data collection process by contacting a percentage of the respondents to verify that they were actually interviewed. Data editing and cleaning involves the process of checking for inadvertent errors in the data. This usually entails using a computer to check for out-of-bounds data.  Quantitative studies employ deductive logic, where the researcher starts with a hypothesis, and then collects data to confirm or refute the hypothesis. Qualitative studies use inductive logic, where the researcher first designs a study and then develops a hypothesis or theory to explain the results of the analysis.

Quantitative analysis is generally fast and inexpensive. A wide assortment of statistical techniques is available to the researcher. Computer software is readily available to provide both basic and advanced multivariate analysis. The researcher simply follows the preplanned analysis process, without making subjective decisions about the data. For this reason, quantitative studies are usually easier to execute than qualitative studies.  Qualitative studies nearly always involve in-person interviews, and are therefore very labor intensive and costly. They rely heavily on a researcher's ability to exclude personal biases. The interpretation of qualitative data is often highly subjective, and different researchers can reach different conclusions from the same data. However, the goal of qualitative research is to develop a hypothesis--not to test one. Qualitative studies have merit in that they provide broad, general theories that can be examined in future research.  Data Analysis Modern computer software has made the analysis of quantitative data a very easy task. It is no longer incumbent on the researcher to know the formulas needed to calculate the desired statistics. However, this does not obviate the need for the researcher to understand the theoretical and conceptual foundations of the statistical techniques. Each statistical technique has its own assumptions and limitations. Considering the ease in which computers can calculate complex statistical problems, the danger is that the researcher might be unaware of the assumptions and limitations in the use and interpretation of a statistic.  Reporting the Results  The most important consideration in preparing any research report is the nature of the audience. The purpose is to communicate information, and therefore, the report should be prepared specifically for the readers of the report. Sometimes the format for the report will be defined for the researcher (e.g., a dissertation), while other times, the researcher will have complete latitude regarding the structure of the report. At a minimum, the report should contain an abstract, problem statement, methods section, results section, discussion of the results, and a list of references (Anderson, 1966).

 Validity and Reliability

 Validity refers to the accuracy or truthfulness of a measurement. Are we measuring what we think we are? "Validity itself is a simple concept, but the determination of the validity of a measure is elusive"   Face validity is based solely on the judgment of the researcher. Each question is scrutinized and modified until the researcher is satisfied that it is an accurate measure of the desired construct. The determination of face validity is based on the subjective opinion of the researcher.  Content validity is similar to face validity in that it relies on the judgment of the researcher. However, where face validity only evaluates the individual items on an instrument, content validity goes further in that it attempts to determine if an instrument provides adequate coverage of a topic. Expert opinions, literature searches, and pretest open-ended questions help to establish content validity.  Criterion-related validity can be either predictive or concurrent. When a dependent/independent relationship has been established between two or more variables, criterion-related validity can be assessed. A mathematical model is developed to be able to predict the dependent variable from the independent variable(s). Predictive validity refers to the ability of an independent variable (or group of variables) to predict a future value of the dependent variable. Concurrent validity is concerned with the relationship between two or more variables at the same point in time.  Construct validity refers to the theoretical foundations underlying a particular scale or measurement. It looks at the underlying theories or constructs that explain    nominal. This is also quite subjective and depends heavily on the understanding, opinions, and biases  f the researcher.

 Reliability is synonymous with repeatability. A measurement that yields consistent results over time is said to be reliable. When a measurement is prone to random error, it lacks reliability. The reliability of an instrument places an upper limit on its validity (Sector, 1981). A measurement that lacks reliability will necessarily be invalid. There are three basic methods to test reliability: test-retest, equivalent form, and internal consistency.  A test-retest measure of reliability can be obtained by administering the same instrument to the same group of people at two different points in time. The degree to which both administrations are in agreement is a measure of the reliability of the instrument. This technique for assessing reliability suffers two possible drawbacks. First, a person may have changed between the first and second measurement. Second, the initial administration of an instrument might in itself induce a person to answer differently on the second administration.

 The second method of determining reliability is called the equivalent-form technique. The researcher creates two different instruments designed to measure identical constructs. The degree of correlation between the instruments is a measure of equivalent-form reliability. The difficulty in using this method is that it may be very difficult (and/or prohibitively expensive) to create a totally equivalent instrument.

 The most popular methods of estimating reliability use measures of internal consistency. When an instrument includes a series of questions designed to examine the same construct, the questions can be arbitrarily split into two groups. The correlation between the two subsets of questions is called the split-half reliability. The problem is that this measure of reliability changes depending on how the questions are split. A better statistic, known asP2M INFORTECH is based on the mean (absolute value) interterm correlation for all possible variable pairs. It provides a conservative estimate of reliability, and generally represents "the lower bound to the reliability of an unweighted scale of items. For dichotomous nominal data, the KR-20 is used instead of Chronbach's alpha.

 Variability and Error

 Most research is an attempt to understand and explain variability. When a measurement lacks variability, no statistical tests can be (or need be) performed. Variability refers to the dispersion of scores.  Ideally, when a researcher finds differences between respondents, they are due to true difference on the variable being measured. However, the combination of systematic and random errors can dilute the accuracy of a measurement. Systematic error is introduced through a constant bias in a measurement. It can usually be traced to a fault in the sampling procedure or in the design of a questionnaire. Random error does not occur in any consistent pattern, and it is not controllable by the researcher.

Summary

Scientific research involves the formulation and testing of one or more hypotheses. A hypothesis cannot be proved directly, so a null hypothesis is established to give the researcher an indirect method of testing a theory. Sampling is necessary when the population is too large, or when the researcher is unable to investigate all members of the target group. Random and systematic sampling is the best methods because they guarantee that each member of the population will have a known non-zero chance of being selected. The mathematical reliability (repeatability) of a measurement, or group of measurements, can be calculated, however, validity can only be implied by the data, and it is not directly verifiable. Social science research is generally an attempt to explain or understand the variability in a group of people.

 The Seven Steps of the Research Process, The following seven steps outline a simple and effective strategy for finding information for a research paper and documenting the sources you find. Depending on your topic and your familiarity with the library, you may need to rearrange or recycle these steps. Adapt this outline to your needs. We are ready to help you at every step in your research.

 STEP 1: IDENTIFY AND DEVELOP YOUR TOPIC

 SUMMARY: State your topic as a question. For example, if you are interested in finding out about use of alcoholic beverages by college students, you might pose the question, "What effect does use of alcoholic beverages have on the health of college students?" Identify the main concepts or keywords in your question.  More details on how to identify and develop your topic.

 STEP 2: FIND BACKGROUND INFORMATION

 SUMMARY: Look up your keywords in the indexes to subject encyclopedias. Read articles in these encyclopedias to set the context for your research. Note any relevant items in the bibliographies at the end of the encyclopedia articles. Additional background information may be found in your lecture notes, textbooks, and reserve readings.  More suggestions on how to find background information.  Return to the top

 STEP 3: USE CATALOGS TO FIND BOOKS AND MEDIA

 SUMMARY: Use guided keyword searching to find materials by topic or subject. Print or write down the citation (author, title, etc.) and the location information (call number and library). Note the circulation status. When you pull the book from the shelf, scan the bibliography for additional sources. Watch for book-length bibliographies and annual reviews on your subject; they list citations to hundreds of books and articles in one subject area. Check the standard subject subheading "--BIBLIOGRAPHIES," or titles beginning with Annual Review of... in the Cornell Library Catalog.  More detailed instructions for using catalogs to find books.

STEP 4: USE INDEXES TO FIND PERIODICAL ARTICLES

SUMMARY: Use periodical indexes and abstracts to find citations to articles. The indexes and abstracts may be in print or computer-based formats or both. Choose the indexes and format best suited to your particular topic; ask at the reference desk if you need help figuring out which index and format will be best. You can find periodical articles by the article author, title, or keyword by using the periodical indexes in the Library Gateway. If the full text is not linked in the index you are using, write down the citation from the index and search for the title of the periodical in the Cornell Library Catalog. The catalog lists the print, microform, and electronic versions of periodicals at Cornell.

 How to find and use periodical indexes at Cornell.

 Download video (mp4): reading citations,     Subscribe to the videos,  Return to the top

 STEP 5: FIND INTERNET RESOURCES

 SUMMARY: Use search engines. Check to see if your class has a bibliography or research guide created by librarians.  Finding Information on the Internet: A thorough tutorial from UC Berkeley.

 STEP 6: EVALUATE WHAT YOU FIND

 SUMMARY: See How to Critically Analyze Information Sources and Distinguishing Scholarly from Non-Scholarly Periodicals: A Checklist of Criteria for suggestions on evaluating the authority and quality of the books and articles you located. Download videos (mp4): identifying scholarly journals    identifying news sources    Subscribe to the videos If you have found too many or too few sources, you may need  o  arrow or broaden your topic. Check with a reference librarian or your instructor.  When you're ready to write, here is an annotated list of books to help you organize, format, and write your paper.

 STEP 7: CITE WHAT YOU FIND USING A STANDARD FORMAT

 Give credit where credit is due; cite your sources.  Citing or documenting the sources used in your research serves two purposes, it gives proper credit to the authors of the materials used, and it allows those who are reading your work to duplicate your research and locate the sources that you have listed as references.  Knowingly representing the work of others as your own is plagiarism. (See Cornell's Code of Academic Integrity). Use one of the styles listed below or another style approved by your instructor. Handouts summarizing the APA and MLA styles are available at Uris and Olin Reference.

 Available online:

 Reworks are a web-based program that allows you to easily collect, manage, and organize bibliographic references by interfacing with databases. Reworks’ also interfaces directly with Word, making it easy to import references and incorporate them into your writing, properly formatted according to the style of your choice.

    *    See our Gateway guide to citation tools and styles.

    *     Format the citations in your bibliography using examples from the following Library Gateway Help pages: Modern Language Association (MLA) examples and American Psychological Association (APA) examples.

      Style guides in print (book) format:

                     MLA Handbook for Writers of Research Papers. 6th ewe York: MLA, 2003. (Olin Ref Z 253 .M68 2003; also Uris Ref, others)

            This handbook is based on the MLA Style Manual (Olin and Uris Ref PN 147 .G444x 1998) and is intended as an aid for college students writing research papers. Included here is information on selecting a topic, researching the topic, note taking, the writing of footnotes and bibliographies, as well as sample pages of a research paper. Useful for the beginning researcher.

                    Publication Manual of the American Psychological Association. 5th ed. Washington: APA, 2001. (Olin Ref BF 76.7 .P83x 2001; also Uris Ref, Mann Ref, others) .The authoritative style manual for anyone writing in the field of psychology. Useful for the social sciences generally. Chapters discuss the content and organization of a manuscript, writing style, the American Psychological Association citation style, and typing, mailing and proofreading.  If you are writing an annotated bibliography, see How to Prepare an Annotated Bibliography.