Action Research Midterm

Palomo, Joyvelyn C.BSED III

Dr. ISIDRO M. BIOL Jr.

MIDTERM COVERAGE

Quantitative and Qualitative Research

QUALITATIVE research – involves analysis of data such words (e.g., from interviews), pictures, (e.g., video), or objects (e.g., an artifact)

QUANTITATIVE research – involves analysis of numerical data

Quantitative Research• All research has a qualitative

grounding – Donald Campbell

• The aim is a complete, detailed description

• The design emerges as the study unfolds

• Researcher may only know roughly in advance what he/ she is looking for.

• Recommended during earlier phases of research projects.

• Researcher is the data gathering instrument.

• Data is the form of words, pictures or objects.

• Subjective – individuals’ interpretation of events is important, e.g., uses participant observation, in – depth interviews, etc.

• Rich, time consuming, and less able to be generalized

• Subjectively immersed in the subject matter

QUALITATIVE research

• “There’s no such thing as qualitative data. Everything is either 1 or 0” - Fred Kerlinger

• Recommended during latter phases of research projects

• Data is in the form of numbers and statistics.

• The aim is to classify features, count them, and construct statistical models in an attempt to explain what is observed.

• Researcher knows clearly in advance what he/ she is looking for.

• All aspects of the study are carefully designed before data is collected.

• Researcher uses tools, such as questionnaires or equipment to collect numerical data.

• Objective – seeks precise measurements and analysis of target concepts, e.g., uses surveys, questionnaires, etc.

• Researcher tends to remain objectively separated from the subject matter.

IDENTIFYING THE RESEARCH PROBLEM

DEFINITION

• Research problems are educational issues or concerns studied by researchers

• In education, a problem is a concern to educators that exists in educational settings

Ask yourself…

• To help locate your research problem for your thesis, ask yourself such questions as: What was the

issue/problem you want to study?

What is the concern being addressed “behind” this study?

Why do you want to undertake this study?

Why is this study important to the scholarly community?

DEFINING TERMS

• Research Problem: Educational issue/problem in a study

• Research Topic: Broad subject matter being addressed in a study

• Purpose: Major intent or object of study

• Research Questions: Questions to answer or address in a study

General

Specific

Topic

Research Problem

Research Statement

Research Questions

OVERVIEW

PROBLEM RESEARCHABILITY

1. Will your research contribute to knowledge and practice? It fills a void or extends existing

research It replicates a study with new

participants or a new site Problem has not be studied or

understudied

It gives “voice” to people not heard, silenced, or rejected in society

It informs practice2. Accessed to people & sites3. Time, Resources and skills4. Therapy5. To prove what your already

know

DESIGNING & WRITING THE STATEMENT OF THE PROBLEM

The research problem within this study

Justification for the problem (based on past research and practice)

Shortcoming of past research or practice

The importance / significance of the problem

GETTING STARTED

• Write down the purpose statement of your study

• Look for studies similar to your problem statement in Australia.

• Look for studies similar to your problem statement in other countries.

• Embedded in this purpose statement are key terms that will help you to start your literature review

• This part of the literature review searches for core literature and it should focus almost exclusively on empirical studies

LITERATURE PRIORITY

CORE

RELATIONAL

PARENT

WHERE TO START

1. Encyclopedia of educational research (Alkin, 1992) The appendix ‘Doing library research in education’ is brilliant

2. Theses

Overseas – Dissertation abstracts, US computer disks

British Dissertation abstracts

Australia – Cunningham library, ACER, www.acer.edu.au

3. Handbooks: International Handbooks of Educational Administration, Educational Leadership, Lifelong Learning etc. quickly introduce you to the major players and research issues in your study

4. DatabasesERIC (Educational Resources Information Centre) www.accesseric.org. (world’s largest source of information – one million abstracts)Australian Education Index (AUSINET)

5. Current index to journals in education and resources in education: locate through ERIC

6. Social Science Citation Index: CDROM

7. Online Journals (anbar) 8. Google (search engine)

INITIAL ORGANISING THE LITERATURE

• Read, categorize, file• Construct a literature map

(different from but a pre-requisite to a conceptual framework)

• Print out your research problem and research purpose statement in font size 20pt & bold & adhere to a place near your computer where your regularly see. Do not be a dilettante . You need to get a reasonably solid grasp of your proposed topic relatively quickly in order to focus or flick.

From Creswell (2002).

Research Design• Common sense and clear

thinking necessary for the management of the entire research endeavor.

• Research design is the strategy, the plan, and the structure of conducting a research project.

A Research design • is concerned with turning a

research question into a testing project. The best design depends on the research questions. Every design has its positive and negative sides.

• The research design has been considered a "blueprint" for research, dealing with at least four problems: what questions to study, what data are relevant, what data to collect, and how to analyze the results

• It can be divided into fixed and flexible research designs (Robson, 1993). Others have referred to this distinction with ‘quantitative research designs’ and ‘qualitative research designs’. However, fixed designs need not be quantitative, and flexible design need not be qualitative.

• In fixed designs the design of the study is fixed before the main stage of data collection takes place. Fixed designs are normally theory-driven; otherwise it’s impossible to know in advance which variables need to be controlled and measured. Often these variables are quantitative.

• Flexible designs allow for more freedom during the data collection. One reason for using a flexible research design can be that the variable of interest is not quantitatively measurable, such as culture. In other cases, theory might not be available before one starts the research.

Examples of fixed (quantitative) designs

Experimental designIn an experimental design,

the researcher actively tries to change the situation,

circumstances or experience of participants (manipulation), which may lead to a change in behaviour of the participants of the study. The participants are (randomly) assigned to different conditions, and variables of interest are measured.

• The researcher tries to keep the other variables as similar as possible. Experiments are normally highly fixed before the data collection starts. In a good research design, a few things are of great importance. First of all, it is necessary to think of a proper way to operationalize the variables that you want to measure.

• Do you want to measure your variable with a questionnaire? Do you measure it physically? Secondly, the statistical analysis has to be taken into account. What are your expectations? How do you want to analyze this? Thirdly, in a design you have to think of the practical limitations.

Can you find enough participants for your study? Are the participants that you want to include in your study representative for the population? The most important thing is that when you want to execute a good research, you think of all these questions beforehand. (Adèr, Mellenbergh & Hand, 2008).

• Non-experimental research designs can be split up in three designs. First, relational designs, in which a range of variables is measured. These designs are also called correlation studies, since the correlation is most often used analysis.

Non-experimental research designs

Non-experimental research is almost the same as experimental research, the only difference is that non-experimental research does not involve a manipulation of the situation, circumstances or experience of the participants.

The second type is comparative designs. These designs compare two natural groups. The third type of non-experimental research is a longitudinal design.

Quasi experiment

• Quasi research designs are research design that follow the experimental procedure, but do not randomly assign people to (treatment and comparison) groups.

Examples of flexible (qualitative) research designs

Case study• In a case study, one single unit

is extensively studied. that can be a case of a person, organization, group or situation

Famous case studies are for example the descriptions about the patients of Freud, who were thoroughly analyzed and described. Read more on case study. Bell (1999) states “a case study approach is particularly appropriate for individual researchers because it gives an opportunity for one aspect of a problem to be studied in some depth within a limited time scale”.

Ethnographic study• This type of research is

involved with a group, organization, culture, or community. Normally the researcher shares a lot of time with the group. Read more on Ethnography.

Observation, Interview, Journals

Interview• Interview is a process of

communication or interaction in which the subject or interviewee gives the needed information verbally in a face-to-face situation.

In a sense, it is an oral questionnaire. In a research situation it may be seen as an effective, informal, conversation, initiated for a specific purpose as it focuses on certain areas.

The main objective may be the exchange of ideas and experiences and eliciting of information.

Types of interview

• Interviews may be classified according to the purpose for which they are used and according to their design and structure.

1) Clinical Interview

• major purposes of interviews are diagnosis and treatment is used by social workers and psychiatrists.

2. Interviews may vary in design and structure.

• Individual Interview - interviewer may interview one individual at a time

• Group Interview - a group of individuals is interviewed at one and the same time.

3. Interviews are also classified as 'structured' and 'unstructured'.

'structured' - the whole situation is carefully structured and the major areas of inquiry are mapped out.

It is designated as directive interview

'Unstructured interview' also termed as 'uncontrolled', 'unguided', or 'non-directive' interview is one where the interviewer does not follow a list of predetermined questions.

The interviewees are encouraged to relate their

concrete experiences with no or little direction from the

interviewer, to dwell on whatever events seem

significant to them,

to provide their own definition of their social situations and reveal their opinions and views as they

like. Although the series of questions to be asked and the procedure to be followed are

decided before hand,

the interviewer is largely free to arrange the form and timing of the questions. He/she can rephrase the

questions, modify them and add new questions to his/her

list.

Techniques of interviewing

• Although the interview as a research tool can be modified according to the needs of the research situation, there are certain techniques that need to be understood.

I . Preparation for the Interview

• It is necessary to plan carefully for an interview.

• The interviewer must decide exactly what kind of data the interview should yield, whether the structured or unstructured type of interview will be more useful and how the results of interview should be recorded.

• It is advisable to try out the interview on some persons before using it for actual investigation. This is helpful in revealing the deficiencies or shortcomings that need to be corrected before the interview is carried out.

• Since it is administered personally, it provides the researcher an opportunity to establish a rapport with the respondents.

• This helps the researcher to explain the nature and purpose of investigation and to make the meaning of the questions clear to the respondents in case they misinterpret a question or give incomplete or indefinite responses.

The interviewer must have a clear idea of the sort of information he/she needs, and may accordingly prepare a list of questions in the form of a "schedule". Interview schedule is a device consisting of a set of questions,

which are asked and filled in by an interviewer in a face-to-face situation with the interviewee.

• The schedule also economizes time and expenses of investigation. The procedure of constructing a schedule is same as that of a questionnaire.

2. Conduct of Interview

• In the conduct of an interview, a harmonious relationship between the interviewer and interviewee is most essential. A good rapport helps the interviewee to feel at ease and express himself /herself willingly.

In order to establish a good rapport, the interviewer should greet the interviewee in a friendly manner so as to get settled in a relaxed manner. As an interviewer you should observe the following rules in order to elicit effective responses:

• Ask only one question at a time.• Repeat a question if necessary.• Try to make sure that the

interviewee understands the questions.

• Listen carefully to the interviewee's answer.

• Observe the interviewee's facial expressions, gestures, and tone or voice so as to derive meanings from his/her body language.

• Allow the interviewee sufficient time to answer the question, but don't let the interview drag on and on.

• Avoid suggesting answers to questions.

• Do not show signs of surprise, shock, anger, or other emotions if unexpected answers are given.

• Maintain a neutral attitude with respect to controversial issues during the interview.

• Take note of answers that seem to be vague, ambiguous, or evasive.

• Use tact and skill in getting the subject back to an area of inquiry

• He/she has strayed too far from the original question.

• In the unstructured interview, ask additional questions to follow up clues or to obtain additional information.

• The interviewer should try to redirect the interview to more fruitful topics when he/she feels that the required information is not sufficient. He/she should wind up the interview before the interviewee becomes tired.

3. Recording of the Interview

• The recording of the interview is obviously an essential step in interviewing. The interviewer may use a schedule, a structured format, rating scale or a tape recorder to record the responses of the interviewee.

• The use of a tape recorder during the conduct of the interview not only eliminates the omissions, distortions, elaborations and other modifications of data usually found in written interview responses,

but it also provides an objective basis for evaluating the adequacy of the interview data in relation to the performance of the interviewee.

The use of a tape-recorder also permits the interviewer to devote full attention to the interviewee and save much of the time which he/she would otherwise use in writing down the responses during or after the interview.

However, if a tape-recorder is not available, the interviewer has to take notes to record the responses.

Uses of the interview

1.) An interview provides an opportunity to the interviewer to ask questions on various areas of inquiry. It permits greater depth in responses which is not possible through any other means.

2) An interview is not an entirely independent tool of research for gathering information pertaining to feelings, attitudes or emotions. It is supplementary to other tools and techniques.

• A combination of interviewing, observations, and statistical techniques often yield the best results, but the balance of emphasis shifts with the frame of reference and objectives of the study. Since an interview is a highly flexible tool in the hands of skillful interviewers,

• it allows a more liberal atmosphere than in the use of other techniques of investigation. Questions not readily grasped by interviewees can be rephrased or repeated with proper emphasis and explanations when necessary.

Limitations of the interview

In spite of many uses of the interview method, it is not without limitations that jeopardize its value, even when it is used as a supplementary research technique.

1) Interview is a time-consuming technique.

2) The effectiveness of the interview depends greatly upon the skill of the interviewer which everyone do not ordinarily possess. It takes time to master this skill.

3) There is a constant danger of subjectivity on the part of the interviewer.

4) An interview is very difficult to employ successfully because even in the presence of a skilled interviewer some interviewees do not respond freely, frankly and accurately.

• Since memory and retention are highly selective processes, interviewees generally provide accurate and vivid accounts of the most recent or intense experiences,

or of situations that they encounter most frequently. Painful or embarrassing experiences are forgotten or consciously avoided by the interviewees. In such cases the responses lack accuracy.

ObservationObservation may be defined as a

process in which one or more persons observe some real-life situation and record pertinent occurrences. It is used to evaluate the overt behavior of the individuals in controlled and uncontrolled situations.

Types of observation

Observations may be classified into two types:

a) Participant observation

b) Non-participant observation

Participant observation

In the process of 'participant observation' the observer becomes more or less one of the group members and may actually participate in some activity or the other of the group.

The observer may play any one of the several roles in observation, will varying degrees of participation, as a visitor, an attentive listener, an eager learner, or as a participant observer

• Non-participant observation: In the process of 'non-participant observation', the observer takes a position where his/her presence is not felt by the group. He/she may follow closely the behavior of an individual or characteristics of one or more groups.

• In this type of observation, a one-way 'vision screen‘ permits the observer to see the subject but prevents the subject from seeing the observer.

Observations may also be classified into the following two categories:

i) Structured observation

ii) Unstructured observation

Structured observation:

• Structured observation is formal in character and is designed to provide systematic description to test casual hypotheses. It is executed in controlled situations like classrooms or. laboratory settings.

Unstructured observation:

• Unstructured observation is associated with participant observation and is often an exploratory exercise. In unstructured observation,

it may not be possible to categorize behaviour before the observation. The observer considers aspects of behaviour in terms of their contexts or situations of which they are a part.

Stages in the process of observation

As a good research technique, observation needs proper planning, expert execution, and adequate recording and interpretation.

1.) Planning for observation

Planning for observation includes definition of specific activities or

units of behaviour to be observed; the nature of the groups of subjects

to be observed; the scope of observation--individual or group;

determination of the length of each observation period; and deciding

about the tools to be used in making the observation and recording.

2.) Execution of observation

The expert execution of observation includes:

a) proper arrangement of specific conditions for the subject or subjects to be observed,

• b) assuming proper role or physical positions for observing

• c) focusing attention on the specific activities or units of behaviour under observation,

d) proper handling of recording instruments to be used, and

e) utilizing one's training and experience fairly effectively in terms of making the observation and recording the facts.

3.) Recording and interpreting the observation

Recording of the observation data should take place either simultaneously or soon after the observation.

• In the former case, the observer goes on recording his/her observation data simultaneously with the occurrence of the phenomenon observed. In the latter case, the observer undertakes to record his/her observations not simultaneously with the actual event,

but immediately after he/she has observed for a certain period of time while the details are still fresh in his/her mind. In viewing, classifying and recording behaviour, the observer must take utmost care to minimize the influence of his/her biases,

attitudes and values on the observation report.

• observer should know what he/she is looking for in a given situation and should carefully and objectively record the relevant data. Subjectivity on the part of an observer may partly

be due to his/her emotional involvement, his/her selective perceptions and memory.

Uses and limitations of observation

1. Observation provides a direct method for studying various aspects of human behaviour. Indeed, 'it may be the only effective way to gather data in a particular situation e.g., behaviours of a counselors in actual counseling sessions.

11. Observation enables the researcher to record behaviour at the time of occurrence.

JOURNALS

• The function of a research journal is to set down on paper your thoughts about the primary and secondary source material you are reading.

• It is a record of your questions about the material and your tentative answers to those questions. It is a record of your questions about the material and your tentative answers to those questions.

Data Analysis

• Analysis of data is a process of inspecting, cleaning, transforming, and modeling data with the goal of highlighting useful information,

suggesting conclusions, and supporting decision making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, in different business, science, and social science domains

Choice of method and selecting statistic

Research methodology • is a collective term for the

structured process of conducting research.  Different methodologies used in various types of research and the term is usually considered to include research design, data gathering and data analysis.

• Research methodologies can be quantitative (for example, measuring the number of times someone does something under certain conditions) or qualitative (for example, asking people how they feel about a certain situation).

Ideally, comprehensive research should try to incorporate both qualitative and quantitative methodologies but this is not always possible, usually due to time and financial constraints.

Research methodologies are generally used in academic research to test hypotheses or theories. 

A good design should ensure the research is valid, i.e. It clearly tests the hypothesis and not extraneous variables, and that the research is reliable, i.e. It yields consistent results every time.

Part of the research methodology is concerned with the how the research is conducted.  This is called the study design and typically involves research conducted using questionnaires, interviews, observation and/or experiments.

The term research methodology, also referred to as research methods, usually encompasses the procedures followed to analyze and interpret the data gathered.  These often use a range of sophisticated statistical analyses of the data to identify correlations or statistical significance in the results.

Objective, representative research can be difficult to conduct because tests can normally only be conducted on a small sample (e.g. You cannot test a drug on every person in the world so a sample needs to be used in research). 

This means that researchers need to have a very detailed understanding of the types and limitations of research methodologies which they are using.

Statistics is the study of the collection, organization, analysis, and interpretation of data.[1][2] It deals with all aspects of this, including the planning of data collection in terms of the design of surveys and experiments.[1]

• A statistician is someone who is particularly well versed in the ways of thinking necessary for the successful application of statistical analysis. Such people have often gained this experience through working in any of a wide number of fields.

• There is also a discipline called mathematical statistics that studies statistics mathematically.

• The word statistics, when referring to the scientific discipline, is singular, as in "Statistics is an art."[3]

• This should not be confused with the word statistic, referring to a quantity (such as mean or median) calculated from a set of data,[4] whose plural is statistics ("this statistic seems wrong" or "these statistics are misleading").

In applying statistics to a scientific, industrial, or societal problem, it is necessary to begin with a population or process to be studied. Populations can be diverse topics such as "all persons living in a country" or "every atom composing a crystal".

A population can also be composed of observations of a process at various times, with the data from each observation serving as a different member of the overall group. Data collected about this kind of "population" constitutes what is called a time series.

For practical reasons, a chosen subset of the population called a sample is studied — as opposed to compiling data about the entire group (an operation called census). Once a sample that is representative of the population is determined,

data are collected for the sample members in an observational or experimental setting. This data can then be subjected to statistical analysis, serving two related purposes: description and inference.

Descriptive statistics summarize the population data by describing what was observed in the sample numerically or graphically. Numerical descriptors include mean and standard deviation for continuous data types (like heights or weights),

while frequency and percentage are more useful in terms of describing categorical data (like race).

Inferential statistics uses patterns in the sample data to draw inferences about the population represented,

accounting for randomness. These inferences may take the form of: answering yes/no questions about the data (hypothesis testing), estimating numerical characteristics of the data (estimation), describing associations within the data (correlation)

and modeling relationships within the data (for example, using regression analysis). Inference can extend to forecasting, prediction and estimation of unobserved values either in or associated with the population being studied;

it can include extrapolation and interpolation of time series or spatial data, and can also include data mining.[13]

* The concept of correlation is particularly noteworthy for the potential confusion it can cause.

Statistical analysis of a data set often reveals that two variables (properties) of the population under consideration tend to vary together, as if they were connected.

For example, a study of annual income that also looks at age of death might find that poor

people tend to have shorter lives than affluent people. The two variables are said to be correlated; however, they may or may not be the cause of one another. The correlation phenomena could be caused by a third,

previously unconsidered phenomenon, called a lurking variable or confounding variable. For this reason, there is no way to immediately infer the existence of a causal relationship between the two variables.

For a sample to be used as a guide to an entire population, it is important that it is truly a representative of that overall population. Representative sampling assures that the inferences and conclusions can be safely extended from the sample to the population as a whole.

A major problem lies in determining the extent to which the sample chosen is actually representative. Statistics offers methods to estimate and correct for any random trending within the sample and data collection procedures.

There are also methods of experimental design for experiments that can lessen these issues at the outset of a study, strengthening its capability to discern truths about the population.

Randomness is studied using the mathematical discipline of probability theory. Probability is used in "mathematical statistics" (alternatively, "statistical theory") to study the sampling distributions of sample statistics and,

more generally, the properties of statistical procedures. The use of any statistical method is valid when the system or population under consideration satisfies the assumptions of the method.

Misuse of statistics can produce subtle, but serious errors in description and interpretation — subtle in the sense that even experienced professionals make such errors, and serious in the sense that they can lead to devastating decision errors.

For instance, social policy, medical practice, and the reliability of structures like bridges all rely on the proper use of statistics.

Statistical methods• Experimental and

observational studiesA common goal for a statistical

research project is to investigate causality, and in particular to draw a conclusion on the effect of changes in the values of predictors or

independent variables on dependent variables or response. There are two major types of causal statistical studies: experimental studies and observational studies. In both types of studies, the effect of differences of an independent variable (or

variables) on the behavior of the dependent variable are observed. The difference between the two types lies in how the study is actually conducted. Each can be very effective. An experimental study involves taking measurements of the system

under study, manipulating the system, and then taking additional measurements using the same procedure to determine if the manipulation has modified the values of the measurements. In contrast, an observational study does not involve experimental

manipulation. Instead, data are gathered and correlations between predictors and response are investigated.

• ExperimentsThe basic steps of a statistical

experiment are:

1) Planning the research, including finding the number of replicates of the study, using the following information: preliminary estimates regarding the size of treatment effects, alternative hypotheses, and the estimated experimental variability.

Consideration of the selection of experimental subjects and the ethics of research is necessary. Statisticians recommend that experiments compare (at least) one new treatment with a standard treatment or control, to allow an unbiased estimate of the difference in treatment effects.

2) Design of experiments, using blocking to reduce the influence of confounding variables, and randomized assignment of treatments to subjects to allow unbiased estimates of treatment effects and experimental error. At this stage, the experimenters and

statisticians write the experimental protocol that shall guide the performance of the experiment and that specifies the primary analysis of the experimental data.

3) Performing the experiment following the experimental protocol and analyzing the data

following the experimental protocol.

4) Further examining the data set in secondary analyses, to suggest new hypotheses for future study.

5) Documenting and presenting the results of the study.

Observational study• An example of an observational

study is one that explores the correlation between smoking and lung cancer. This type of study typically uses a survey to collect observations about the area of interest and then performs statistical analysis.

In this case, the researchers would collect observations of both smokers and non-smokers, perhaps through a case-control study, and then look for the number of cases of lung cancer in each group. . Each of these have different degrees of usefulness in statistical research.

Levels of measurement

There are four main levels of measurement used in statistics:

1) Nominal - have no meaningful rank order among values.

2) Ordinal - have imprecise differences between consecutive values, but have a meaningful order to those values

3) Interval - Interval measurements have meaningful distances between measurements defined, but the zero value is arbitrary (as in the case with longitude and temperature measurements in Celsius or Fahrenheit).

4) Ratio - Ratio measurements have both a meaningful zero value and the distances between different measurements defined; they provide the greatest flexibility in statistical methods that can be used for analyzing the data.

• Key terms used in statistics

Null hypothesis

The best illustration for a novice is the predicament encountered by a jury trial. The null hypothesis, H0, asserts that the defendant is innocent, whereas the alternative hypothesis, H1, asserts that the

defendant is guilty. The indictment comes because of suspicion of the guilt. The H0 (status quo) stands in opposition to H1 and is maintained unless H1 is supported by evidence "beyond a reasonable doubt". However, "failure to reject H0"

in this case does not imply innocence, but merely that the evidence was insufficient to convict. So the jury does not necessarily accept H0 but fails to reject H0. While one can not "prove" a null hypothesis one can test how close it is to being true with a power test, which tests for type II errors.

Error• Working from a null hypothesis

two basic forms of error are recognized:

• Type I errors where the null hypothesis is falsely rejected giving a "false positive".

• Type II errors where the null hypothesis fails to be rejected and an actual difference between populations is missed giving a "false negative".

• Error also refers to the extent to which individual observations in a sample differ from a central value, such as

• the sample or population mean. Many statistical methods seek to minimize the mean-squared error, and these are called "methods of least squares."

• Measurement processes that generate statistical data are also subject to error. Many of these errors are classified as random (noise) or systematic (bias), but other important types of errors (e.g., blunder, such as when an analyst reports incorrect units) can also be important.

• Interval estimation

Most studies will only sample part of a population and so the results are not fully representative of the whole population. Any estimates obtained from the sample only approximate the population value.

Confidence intervals allow statisticians to express how closely the sample estimate matches the true value in the whole population. Often they are expressed as 95% confidence intervals. Formally, a 95% confidence interval for a value is a range where

if the sampling and analysis were repeated under the same conditions (yielding a different dataset), the interval would include the true (population) value 95% of the time.

• Significance

Statistics rarely give a simple Yes/No type answer to the question asked of them. Interpretation often comes down to the level of statistical significance applied to the numbers and often refers to the probability of a value

accurately rejecting the null hypothesis (sometimes referred to as the p-value).

• Referring to statistical significance does not necessarily mean that the overall result is significant in real world terms

• For example, in a large study of a drug it may be shown that the drug has a statistically significant but very small beneficial effect, such that the drug will be unlikely to help the patient in a noticeable way.

Some well-known statistical tests and procedures are:

• Analysis of variance (ANOVA)

• Chi-squared test• Correlation• Factor analysis

• Mann–Whitney U• Mean square weighted devi

ation (MSWD)

• Pearson product-moment correlation coefficient

• Regression analysis

• Spearman's rank correlation coefficient

• Student's t-test• Time series analysis

Criteria in Critiquing an Article

• what kind of a journal article is it: an empirical/research article, or a review of literature?

• First of all, for any type of journal article your critique should include some basic information1

1. Name(s) of the author(s)

2. Title of article

3. Title of journal, volume number, date, month and page numbers

4. Statement of the problem or issue discussed

5. The author’s purpose, approach or methods, hypothesis, and major conclusions.

• Read the article you are to critique once to get an overview. Then read it again, critically. At this

point you may want to make some notes to yourself on your copy (not the library’s copy).

• The following are some questions you may want to address in your critique no matter what type

of article you are critiquing. (Use your discretion. These points don’t have to be discussed in this order, and some may not be pertinent to your particular article.)

1. Is the title of the article appropriate and clear?

2. Is the abstract specific, representative of the article, and in the correct form?

3. Is the purpose of the article made clear in the introduction?

4. Do you find errors of fact and interpretation? (This is a good one! You won’t believe how

often authors misinterpret or misrepresent the work of others. You can check on this by looking up for yourself the references the author cites.)

5. Is all of the discussion relevant?

6. Has the author cited the pertinent, and only the pertinent, literature? If the author has included inconsequential references, or references that are not pertinent, suggest deleting them.

7. Have any ideas been overemphasized or underemphasized? Suggest specific revisions.

8. Should some sections of the manuscript be expanded, condensed or omitted?

9. Are the author’s statements clear? Challenge ambiguous statements. Suggest by examples how clarity can be achieved, but do not merely substitute your style for the author’s.

10. What underlying assumptions does the author have?

11. Has the author been objective in his or her discussion of the topic?

In addition, here are some questions that are more specific to empirical/research articles. 1. Is the objective of the experiment or of the observations important for the field?

2. Are the experimental methods described adequately?

3. Are the study design and methods appropriate for the purposes of the study?

4. Have the procedures been presented in enough detail to enable a reader to duplicate them?

(Another good one! You’d be surprised at the respectable researchers who cut corners in their writing on this point.)

5. Scan and spot-check calculations. Are the statistical methods appropriate?

6. Do you find any content repeated or duplicated? A common fault is repetition in the text of data in tables or figures.

Suggest that tabular data be interpreted of summarized, nor merely repeated, in the text.

A word about your style: let your presentation be well-reasoned and objective. If you passionately disagree (or agree) with the author, let your passion inspire you to new heights of thorough research and reasoned argument.