RESEARCH METHODS IN GEOGRAPHY


RESEARCH METHODS IN GEOGRAPHY

1.0 INTRODUCTION TO THE USE OF GEOGRAPHIC DATA
It is the study of the location and distribution of living things and earth features among which they live.
Geographers study where people, animals and plants live and their relationships with rivers, deserts and other earth features.
They examine where earth features are located, how they came to be there and why their location is important.
To many people geography means different things and a geographer’s work in many cases is misunderstood by the general public.
People see geographers as those who poses knowledge of far distant places or possessing close to encyclopedic knowledge of places and who are able to give you answers (many names and fact files) of different places at a click of a finger tip.
To others geographers are like moving atlases, they are genius on TV quizzes about people and places but have no other value beyond this knowledge.
Yet a third group associate geography with map and map making, simulating charts and globes without realizing that various global challenges and changes that are taking place throughout the world.
Geographers have a lot of work to do that contribute to the national development, We have to emphasize that modern geography doesn’t merely describe places or regions but goes on to analyse the various phenomenon in these places.
In broad terms geographers deals with location, spatial relations, Regional characteristics and the forces that change the earth.
GEOGRAPHERS
-          Analyse the physical landscape and examine the relationships between places and offer explanations on the various observed and how these affects distribution of man and how is many economic and social activities.
-          Explores the relationship between the earth and its people through the study of place, space and environment- asking questions of where, what and also why and how?
-          Investigate the interrelationship between people and their physical environment (facts percell have no meaning it is information which is not the same as knowledge. They only have meaning if they are related or organised into some sort of system). And appreciate the complex interactions of people with their environment.
-          Examine regional differences, patterns and interrelationships and attempt to account for them (the regional framework and analysis of specific regions) this is part of the study of area differences.
-          Emphasize on spatial pattern and relationship so as to get a better understanding of both the physical and human world. In whatever data she/he studied the geographer looks for spatial form and spatial relations- pattern of distribution and interactions.
-          Studies the environment from the holistic perspective (both its physical and human dimension) and thus addresses the natural resources upon which all life depends, their impacts on human activities and the wider social economic, political and cultural consequence of the interrelationship between the two.
This was dominated by Ancient Greeks especially Plato who used the deductive method and Aristotle who used the inductive method. Their main concern was to answer the question what is where? They gave descriptions of places and different phenomena. They did not answer the questions: Why are the phenomena where they are located? And why do they behave that way?
Why are the phenomena located where they are? They believed that the environment dictates the kind of activities to be done at a certain place.
This paradigm developed much in Europe.
It failed to answer the question; what is the influence of man in the environment.
The environment provides different options or alternatives to which you can put it; human beings make decision on what alternatives to take.
 The environment does not dictate decision making.
It failed to realise the interrelations between human beings and the environment
They believed that the phenomena behave as they are behaving due to regional differences.
Climate, soils and vegetation were taken as some of the criteria to define the region.
This paradigm divided the world into natural regions which are unique.
This uniqueness was rejected by some geographers: they claimed that it was difficult to demarcate regions which are permanently unique; it did not come with a clear testable way of assessing human impacts on the environment.
Regionalism changed into spatial analysis of geographic phenomena.
It started in the US. It is an attempt to make Geography systematic science which can make laws and theories. It aimed at making geography scientific by using scientific methods.
In previous paradigms there were no laws and theories. The approaches were descriptive
The scientific approach uses the philosophy of mathematics and statistics to arrive at conclusions
Regionalism in its various forms was the dominant geographical paradigm used in teaching and research in geography after replacing the environmental determinism and possibilism paradigm in 1930s and 1940s. However many geographers blamed it for the low self esteem of the discipline in the 1950s and argued that it did not afford the necessary balance between regional and systematic studies. They also argued that uniqueness of places that regionalism emphasized tended to ignore the search for generalization that would offer better explanations and allow for wider application and insight into geographical phenomenon. They believed that their approach and adoption of quantification by the wider geographical community would make geography to be more respected and recognised academically as capable of contributing worthy knowledge to solve the many problems that the society was facing in the 1960s as opposed to its then status that they considered to be intellectually weak, being held in low esteem by other discipline and being descriptive and lacking in theory.  The main difference with the regional school was the greater faith geographers had in their ability to produce laws and work within the accepted scientific methods that were increasingly defining social science research.
Any research is the logical process, i.e. appears logically. It possesses the following characteristics:
        i.            The research begins with the question in the mind of the researcher. This question should be intelligently asked in the presence of the phenomena that the researcher has observed and which disturbs him. The question may involve unresolved and confusing situation around you.
      ii.            Research requires a plan: It is not aimless, undirected activity. It requires a definite plan direction and design.
To ensure a good plan there should be:
·         A clear statement of the problem
·         Development of hypothesis
·         Data gathering and interpreting design
·         Test of hypothesis and an arrival at factually based conclusion
    iii.            A research requires a clear statement of the problem: Here unanswered questions that the researcher finds indigenous to the research situation must be put clear at the very beginning of the research. Before we begin we need to understand the problem. We look at it objectively.
    iv.            Any research deals with the main problem through sub problems. Most researchable problems have within them other problem areas of lesser breadth and importance
      v.            Research seeks direction through appropriate hypothesis or research questions, having set the research problem and the sub problems. The sub problems are then viewed through logical constructs.  “A hypothesis is a logical supposition, a reasonable guess, an educated assumption which may give direction to thinking with respect to the problem and thus aid in solving it.
    vi.            Research deals with facts and meanings: Having isolated the problem, subdivided it into appropriate sub problems, and formulated hypothesis or research questions which will suggest the direction in which the facts may lie, the next step is to collect whatever facts which may seem to be pertinent to the problem and to organize them into meaningful aggregates capable of being interpreted
  vii.            Research is circular
Science is an objective activity undertaken within very strict rules, and it involves the continuous excitement of search for new discoveries under a certain set of values universally subscribed to within academics.
The main tenets/pillars of academic research
Originality
Original work intends to discover new knowledge, addition of knowledge on existing knowledge, comparing of things and it is not duplicate.
Communality
Sharing of information with the public is expected after work. It can be done I publication, seminar, workshop or forum.
Disinterestedness
Objectivity not being guided by your opinions; use of scientific procedures
Universalism if a research is done in one area it should bring the same results on other areas with similar characteristics
Constructive criticism be ready to receive constructive criticism.
2.4.1 Problem identification: A problem is anything that requires some explanation. A problem must be clearly defined. A problem can cover anything, e.g. population growth and plan, population movement, Dynamics of human settlements, Urbanization process, economic growth, etc.
2.4.2 Gathering available information or data: You need to read widely what has been written about that particular problem. Relevant information that is available must be collected. This data is available in statistical publications, books, journals, News media, census reports, Historical documents, research documents, etc
2.4.3 Primary data or original data collection: Secondary data may not suffice the problem. The research has to collect original data. This is the data one collects from the field. A research advantageously collects from the field data that is relevant to the problem using different data collection techniques.
2.4.4 Classification or summarization of data: Data or facts that are collected must be organized or grouped to suit the study. The process is known as data classification. Items with similar characteristics are arranged in classes. Summarization is done so as to reduce bulkiness. Summarization is done through techniques that give use of numerical descriptive values which come up with measures of central tendency, Deviation
2.4.5 Data analysis: Data is analysed so as to come up with explanations and conclusions. You derive meanings from the data through analysis and interpretation
2.4.6 Data presentation: The summarised data is presented using tables, values graphs, charts, diagrams, maps. Qualitative and quantitative measures help to understand the relationship between values.
A point that needs to be stressed here is that research is hardly conclusive. This is because in exploring one area a researcher comes up with one or several problems that need resolving.
Research needs no to be seen as one time act static and an end itself. Genuine research is dynamic. It creates more problems than it solves. In deed reading through a number of research report you will notice that researchers point to areas of further research a suggestion that their studies uncovered many issues that need to be considered by themselves or other researchers.  Such is the nature of the discovery of truth. In this way therefore research is a circular process.
What is data? Data is the body of information mostly presented in numerical form (sometimes found in a textual form)
Before any statistical analysis can take place data must be collected (Raw data)
·         Data are precise numerical facts:
·         The information they give is quantitative rather than qualitative.
·         They can therefore be manipulated statistically,
·         They can be stored in digital forms e.g. tapes, CD-ROMs etc
·         Data is usually collected for a definite purpose.
·         Collection of data must therefore take time,
·         Involve measurements and surveys of various types.
·         The justification to collect data is to test a theory or hypothesis
·         The quality of data depends on reliability and accuracy of a researcher.
·         Care must be taken during data collection.
·         To maintain the quality of data certain things must be avoided in data collection: These include: Making mistakes, Subjectivity, biasness.
·          The collection of data and methods/ techniques must suit the purpose of research.
·          Data should be valid and reliable. To have good data you need to be objective rather than subjective.
Davis (1974) Insisted that the common feature of geographical data is the fact that it is spatially distributed over time and space. Geographical data have time and space.
The values of geographical data have been related to points, areas and lines. For instance when dealing with population data, the points can be used to represent the population density.
Geographical data can take various forms including:
Altitude: Heights of landscapes, always presented in Metres. This data can be presented in form of contours.
Rainfall: A rain gauge is used to get the amount of rainfall in mm. This data can be presented in the form of isohyets.
Temperature: Presented in the form of isolines
Population statistics: Presented in the form of dots
Traffic flows: Presented in flow line map forms\
The aim of collecting all these data is to solve geographical problems
Geographical data can be;
Individual data provides precise and specific values of every item in the sample population. This data is very informative, thus very difficult to tabulate if the data set is too large. It is suitable if the population is small.
Grouped data: This represents the grouped/class values information. The groups are formed arbitrary e.g. age groups. It is convenient when large numbers are involved in research
Discrete data: Data presented in whole numbers due to their nature e.g. Human beings, cars, etc
Continuous data: Presented in the value over a given range, temperature, rainfall, height, etc. It is the type of data where you can get fractions.
Primary and secondary data:
Primary data: Information acquired directly from the field
Secondary data: The kind of information obtained from other people’s findings
-They help to facilitate description:
ü  Summarising or converting information into mathematical language
ü  enables one to easily understand and interpret the phenomena. It enables easy comparison of results.
ü  Enables the understanding of the phenomena.
ü  It enables the reduction of massiveness of data.
ü   It is good for the manageability of information.
ü   Enables the researcher to quantify data by giving numbers to data in a way that data becomes objective and look scientific.
-Statistical methods enable facilitation of induction/ making of inferences. Generally the whole information is very difficult is very difficult to study.
-Statistical methods make it easier to generalise information about population from the sample. It enables to make inferences about the whole population leading to objective decisions.
-Statistical methods enable researchers to test the significance of the results.
-They test the relationships between sample data whether they are significant or a result of chance.
-Statistical methods allow the making of predictions: Predicting what may happen in future. This requires understanding of past events. The past events on the context of geography are spatial. They may be past while existing. With this knowledge prediction of the future is possible
Limited time: the amount of time available to a researcher determines the research design, the type of data to be collected, analysis strategy, etc
Reliability and accuracy. This mostly concerned with stability and consistency. If not acquired the data collected can not be reliable.
Lack of reliability and accuracy leads to biases and invalidity. Highly unreliable measures can not be valid.
-Inability to reach certain populations (inaccessibility). Certain populations may not be accessible e.g. due to remoteness (topography)
-Data disaggregation
-Introduction of errors
Global warming, Loose of biodiversity, Pollution &Exposition of finite resources.
To solve this problem the developing countries has to exact pressure on natural resources.
Spatial diffusion have been fostered by ICT revolution in the way world have been unified in terms of corporate and finance for Example agricultural information for multilateral corporations.   Change from agriculture to industry which leads to change from village to urban.
·       From religion racism
·       Cultural conflict and conflict over natural resources
 e.g. environmental degradation such as deforestation and overstocking.
Research involves carrying out a diligent inquiry or critical examination of a given phenomenon such as a critical analysis of existing conclusion or theories visa vies newly discovered facts.
The purpose for any research include all or some of the following:
        i.            To discover new knowledge ie new ideas or new facts
      ii.            To identify and describe new phenomenon
    iii.            To make predictions and make estimation of a phenomenon
    iv.            Enable control                                                                                                      Offer explanation of a phenomenon based upon described characteristics    ( give a critical reasons why something is happening) for example there is a very high dropout rate why                                                                                       Why there is low crop production or why road accident or impacts of rainfall variability or what can maintain price of a particular crop in the market.
      v.            Enable theory development or confirmation, validation of existing theories (basic research) or develop new ideas that strengthen a theory.
    vi.            Solve a specific problem i.e. in agriculture genetically modified food (GMF)
Research is classified according to
                        i.          Data collection
                       ii.          Analysis
                       iii.          Purpose
·       Applied research
·       Basic research
·       Action research
·       Evaluation research
·       Qualitative research
·       Quantitative research
·       Survey research
·       Historical research
·       Descriptive research
·       Case study research
·       Experimental research
·       From existing literature ie. systematic reading of previous research work and or published books
·       Existing theories
·       Opinion/ insights from experts/ peers
·       Media reports (things which are frequently reported ie news papers, radios, TV
·       Personal experience/ practical issue ( the work related experiences ie technological change and experience.
·       New policy
       i.          Survey
     ii.          Case study
   iii.          Experimental strategy
   iv.          Ethnography
It is characterized by one common thing wide and inclusive coverage, Bringing things up to date. Getting snapshot of how things are at a specific time during the survey.
It is an in-depth study of a particular situation or event
Manipulation of circumstances, identifying significant factors, introducing or excluding some factors from the situation, observing effects (manipulation and control)
7.4 Ethnography
Here is not an interview to people for little time but one need to spend a lot of time with people whose culture you want to understand.
Example why people prefers this? Why they live there and how they passive life.
There is no one right strategy or correct strategy in doing a research.
There is no best strategy but the one which can help to solve a problem is the best.
The strategy should be taken prior for the research so choose the best suited according to the purpose.
There are a number of criteria to consider and these include
       i.          Relevance
     ii.          Feasibility
   iii.          Accuracy
   iv.          Objectivity
     v.          Coverage
   vi.          Ethics
Does the research you intend to carry out address current issue in a society
a)     Current – commonly talk about and affect people ie environmental degradation, governance
                   (Corruption) the impact of governance on management and sustainable utilization of natural resources (disease environment and poverty)
b)     Will your research build upon existing knowledge? Is it going to make a contribution on what is being known?
c)     Are you going to use the existing theory? are specific theory being tested
d)     Is your research coming with new theory?
Is the question about be done? (Can your research be done?)
Criteria for feasibility
a)     Time – is there sufficient time for you to do a research, i.e. to collect data, analyse and come up with results. How much time are you locating in design, analyse and writing a report.
b)      Resources – do you have enough resources to cover your research (i.e. financial resources)
c)     Accessibility – information can be available but not accessible. The research design should make sure that information is accessible. Ie one is doing a research in rain season when roads are not passable. Or assume the information available is for nationals and not for foreigners.
 Criteria for accuracy
a)     Will the research you want to carry out provide true and honest findings?
b)     Precise and detailed data (full and honest answer to questions)
c)     Do you as a researcher focus on vital issue
Criteria for objectivity
a)     Will the research give you a fair and balanced picture?
b)     Will the research provide an option of free for personal values believes and background
c)     Will the researcher maintain an open mind about the findings as well as be able to recognise limitations about the approach taken. 
·       You need to question whether the all right things have been included
·       All the questions should cover the issues being investigated ie people and events. The extent of responses ( the response rate)
·       Ethics has to do rights and feelings affected by research that you conduct.
(Because of money respondents can give or not give or exaggerate the information)
·       Avoid deceiving people who are going to give you data  use an informed concent ( truth information)
·       Avoid misrepresentation
·       Protect the identities of people whom you are conducting a research on.
Geographers use specialized research methods to study earth features and human activities. These methods include;
Field study:  A technique that relies on direct observation as the means of learning about the earth’s surface and the patterns resulting from human activity. Geographers travel to regions to answer specific questions about the area or to learn about unfamiliar geographic relationships.
Mapping: This is one of the geographers’ most basic activities. Many aspects of geographic research can be shown on maps. Maps present in a simplified form complex pieces of geographic information. They can easily describe the location, characteristics and patterns of geographic elements.
Interviewing: Observation alone can not answer all geographic questions. At times geographers want to study the attitudes people have towards certain places or how their surroundings is affected by their beliefs and activities. This information can be obtained by interviewing groups of people. Researches often do not interview the entire group, instead they interview a portion of the group scientifically selected to represent the entire population (Sampling).
-          Interviews can be formal when guided or informal when guided by a topic.
-          They are face to face and telephone interviews
Advantages of interviews:
§  Enable discussion among the researcher and the correspondent
§  Help to have information on certain groups through telephone interviews
Disadvantages of interviews
·         Time consuming and costly
·         Inaccuracy of information due to forgetfulness, shy, or biasness
·         The researcher may employ research assistants who are not competent.
·         Lack standards during evaluation.
Focus groups: Acquiring information from a group of 10–20 people. It helps them to understand and voice some of the geographic problems they face. A group should be representative of the whole population. A focus group enables people with different views to discuss their differences, challenge assumptions and come to a collective understanding of the geographic problems. This method gives very brief precise and specific information about the problem. They create new knowledge which was not obtained through other methods.
 Quantitative methods: With the aid of the computer geographers often test their research by using quantitative (mathematical and statistical) methods. These methods help to simplify complex information and to present it in a form that is more easily understood. They also help geographers find the patterns in geographic elements and determine which factors affecting a particular element are the most important.
The use of scientific instruments: This is very crucial to geographic research. Geographers use remote sensing devices to identify and study hard to reach or very large physical features. Such devices are instruments that observe and record information from a distance. These devices include aerial and satellite cameras, infrared (heat sensitive) films, and radar. These devices record information about weather systems, patterns of vegetation growth, the existence of pollution, etc.  Some instruments measure environmental characteristics such as weather gauges, which measure and record temperature, humidity, wind speed and direction and air pressure.
Geography is a field study subject, concerned with accurate observation, recording and interpretation of the variable nature of the human and physical landscapes.
The geographers’ laboratory is in the field, the local environment.
Types of field work:
Field excursion (Field trip): Refers to the trip round the locality or further a field in order to visit places of geographical interest. Students (researchers) observe, listen to lectures by experts (resource persons). Although it is difficult to structure it has the advantage of bringing students into reality of the environment. They are given the opportunity to identify problems of development for later class discussion.
Field study: Refers to the practice whereby students are taken to permanent field centers or laboratories, chosen and maintained by geography departments, for purpose of studying geographic patterns and processes. Students may closely examine and analyze a piece of landscape to understand spatial variations. It involves intensive investigation.
Field research: Refers to fieldwork organized in the context of problem solving approach. A problem of study is stated. A hypothesis put forward for testing; data collection; analysis; hypothesis testing, Conclusion.
10.3 Historical background of Fieldwork in Geography
Change has been present throughout the long development of geography.
ü  There have been a number of different phases or trends in the discipline.
ü  Throughout all this change over the centuries, however, a few things have remained constant.
ü   the subject matter of geography hasn't really changed                             Since the time of the ancient Greeks, geographers have been concerned with the Earth's surface as the home of mankind                                                              Something else that has not changed is the fact that geography has always been a discipline of observation
ü  Observation is simply the most basic way of understanding the fundamental components of geography
-geographers have been observers for centuries
-Homer and other Greeks who observed their surroundings and wrote about them are today recognized as geographers as much as they are by other disciplines
ü  Fieldwork has evolved from its traditional, observational-based origins to a diversity of learning and teaching processes that, since the 1960s and 1970s, have been characterised by increased orientation around study of geographical processes (cf observation of form) and research and problem-solving approaches. Such approaches have necessarily demanded development of subject-specific technical skills, but also the opportunities provided by fieldwork for developing transferable skills (for example teamwork, leadership) and student employability were recognised in the 1980s when such skills became explicit learning objectives of fieldwork (Kent et al, 1997).
ü  Observation has formally been incorporated into geography through fieldwork.
ü  fieldwork is nothing more than systematic observation by a geographer of his or her subject matter
ü   anyone can do fieldwork, and every good geographer does
Virtually anyone can do it because fieldwork is, at its most fundamental, just going out and looking at the land
-all the training you need is knowing what to look for
-knowing what to look for involves training in your respective area
-physical geographers, for example, need to understand geomorphology before going out to research the erosion pattern of a slope
-economic geographers need to understand land use types before going out to chart economic patterns in American cities
Fieldwork is important to geography because it contributes so fundamentally to geographical research and to our basic understanding of the Earth's surface.
·       To understand history in its fullest sense, one cannot just read books about past events or what are commonly called secondary sources
·       To understand geography or do geographic research, one must consult primary sources in this respect; geographers certainly make use of some of the same primary sources as researchers in other fields do
·       Geographers doing research spend much time in the archives looking at original documents like census manuscripts
·       Geography, however, has another primary source that is quite different from those used in other fields; this, of course, is the landscape
·       The landscape is the primary source of the geographer, whether he or she is a physical, cultural, or economic geographer
-it can be rural or urban
-it contains all of the essential facts of geography and, many would say, the means of explaining those facts
i. Be curious and observant
-you must want to do fieldwork, and you must keep your eyes open
ii.   Take clear, organized notes
-fieldwork is just sightseeing unless you can use the information later
iii.    Pay careful attention to your location, making good use of maps
-no matter how detailed your observations are, they are of little value in geography if you cannot link them to a location
-this is where maps come in handy in the field
-making notes about a site at its location on a good map lends precision to your fieldwork
-increasingly, you can note your location accurately by using GPS
-Global Positioning System receivers are lightweight and portable
-they are also becoming quite accurate
-better models can even record and store data for sample locations; you can later download that data directly into a GIS
iv.    Be consistent: fieldwork is literally data collection, whether it is soil or plant types or religious patterns, so consistency is important for accurate results
The value of good fieldwork will not usually be seen in the field, but will instead show up later . . . when you analyze your field observations.
o   remember, fieldwork is data collection
o   your observations are thus raw data
o   if you have observed things systematically and recorded these observations consistently, your analysis of the data will go smoothly
o   you will also be able to do something with your data
-most basic is mapping similar observations
-then, interpret and explain the pattern
-finally, compare the pattern to other patterns
Approaches to Field Work
Historically, two views have tended to dominate fieldwork, at least in American geography (Deductive and Inductive Methods).
Deductive Method
o   one of these was common at the University of Chicago
-in this view, geographers studied a particular problem in depth and then went into the field to look for answers to the problem
-this involved the deductive method
-this method can obviously work, but it is very easy to go into the field and simply look until you find what you are looking for.
Inductive Method
o   another view was held by Carl Sauer at the University of California, Berkeley
-Sauer was probably the strongest advocate of fieldwork in American geography
-he made all of his students to fieldwork, mainly in Mexico and South America
-he himself conducted fieldwork almost every year of his professional life
-he reputedly once said that any mode of transportation faster than a mule was too fast for fieldwork, and he preferred walking
-Sauer's fieldwork philosophy was just the opposite of the Chicago view
-Sauer felt geographers should identify vague topics
-they should then conduct thorough, unbiased fieldwork and simply see what problems and answers the landscape yielded
-this involved the inductive method
-more sound logically and scientifically, in many ways
-the upshot if this was that Sauer send his students into the field with little more than a notebook
-students were not told how to do fieldwork, for everyone does it differently
-they were certainly not told what to look for
-it was really on the job training
-they include step-by-step instructions on a wide range of techniques and skills
-they also include a series of exercises on each of the major topics related to fieldwork
-there is also a superb reading list attached to this site
It is not possible to observe the all population, so we observe the sub set of population which is called sample.
One major characteristics of population is that they are never homogeneous. Population is always heterogeneous. And therefore the value of attributes of which we want to collect information from is also heterogeneous. So we get a representative sample to make inferences about a population. And this inference influences the decision making processes. Example what Tanzanians regional division should be based on?
There are two major sampling techniques these are
·       Probability sampling
·       Non probability sampling
A.    PROBABILITY SAMPLING
1.     RANDOM SAMPLING
        i.            Simple random sampling
      ii.             Stratified random sampling
    iii.            Systematic sampling
    iv.            Mult stage sampling
B.    NON RANDOM SAMPLING
        i.            Cluster sampling
      ii.            Judgemental sampling
    iii.            Accessibility sampling
    iv.            Quarter sampling
                   
C.     
Perhaps the most frequently asked question concerning sampling is, "What size sample do I need?" The answer to this question is influenced by a number of factors, including the purpose of the study, population size, the risk of selecting a "bad" sample, and the allowable sampling error.
This paper reviews criteria for specifying a sample size and presents several strategies for determining the sample size.
In addition to the purpose of the study and population size, three criteria usually will need to be specified to determine the appropriate sample size: the level of precision, the level of confidence or risk, and the degree of variability in the attributes being measured (Miaoulis and Michener, 1976). Each of these is reviewed below.
The Level of Precision
The level of precision, sometimes called sampling error, is the range in which the true value of the population is estimated to be. This range is often expressed in percentage points, (e.g., ±5 percent), in the same way that results for political campaign polls are reported by the media. Thus, if a researcher finds that 60% of farmers in the sample have adopted a recommended practice with a precision rate of ±5%, then he or she can conclude that between 55% and 65% of farmers in the population have adopted the practice.
The Confidence Level
The confidence or risk level is based on ideas encompassed under the Central Limit Theorem. The key idea encompassed in the Central Limit Theorem is that when a population is repeatedly sampled, the average value of the attribute obtained by those samples is equal to the true population value. Furthermore, the values obtained by these samples are distributed normally about the true value, with some samples having a higher value and some obtaining a lower score than the true population value. In a normal distribution, approximately 95% of the sample values are within two standard deviations of the true population value (e.g., mean). In other words, this means that, if a 95% confidence level is selected, 95 out of 100 samples will have the true population value within the range of precision specified earlier (Figure 1). There is always a chance that the sample you obtain does not represent the true population value. Such samples with extreme values are represented by the shaded areas in Figure 1. This risk is reduced for 99% confidence levels and increased for 90% (or lower) confidence levels.
Degree of Variability
The third criterion, the degree of variability in the attributes being measured refers to the distribution of attributes in the population. The more heterogeneous a population, the larger the sample size required to obtain a given level of precision. The less variable (more homogeneous) a population, the smaller the sample size. Note that a proportion of 50% indicates a greater level of variability than either 20% or 80%. This is because 20% and 80% indicate that a large majority do not or do, respectively, have the attribute of interest. Because a proportion of .5 indicates the maximum variability in a population, it is often used in determining a more conservative sample size, that is, the sample size may be larger than if the true variability of the population attribute were used.
There are several approaches to determining the sample size. These include using a census for small populations, imitating a sample size of similar studies, using published tables, and applying formulas to calculate a sample size. Each strategy is discussed below.
Using a Census for Small Populations
One approach is to use the entire population as the sample. Although cost considerations make this impossible for large populations, a census is attractive for small populations (e.g., 200 or less). A census eliminates sampling error and provides data on all the individuals in the population. In addition, some costs such as questionnaire design and developing the sampling frame are "fixed," that is, they will be the same for samples of 50 or 200. Finally, virtually the entire population would have to be sampled in small populations to achieve a desirable level of precision.
Using a Sample Size of a Similar Study
Another approach is to use the same sample size as those of studies similar to the one you plan. Without reviewing the procedures employed in these studies you may run the risk of repeating errors that were made in determining the sample size for another study. However, a review of the literature in your discipline can provide guidance about "typical" sample sizes which are used.
Using Published Tables
A third way to determine sample size is to rely on published tables which provide the sample size for a given set of criteria. Table 1 and Table 2 present sample sizes that would be necessary for given combinations of precision, confidence levels, and variability. Please note two things. First, these sample sizes reflect the number of obtained responses, and not necessarily the number of surveys mailed or interviews planned (this number is often increased to compensate for non response). Second, the sample sizes in Table 2 presume that the attributes being measured are distributed normally or nearly so. If this assumption cannot be met, then the entire population may need to be surveyed.
Size of

Sample
Size (n) for
Precision (e) of
Populatin
       ±3%
        ±5%
                  ±7%
                 ±10%
500
      A
222
145
83

600
     A
240
152
86

700
     A
255
158
88

800
     A
267
163
89

900
     A
277
166
90

1,000
     A
286
169
91

2,000
714
333
185
95

3,000
811
353
191
97

4,000
870
364
194
98

5,000
909
370
196
98

6,000
938
375
197
98

7,000
959
378
198
99

8,000
976
381
199
99

9,000
989
383
200
99

10,000
1,000
385
200
99

15,000
1,034
390
201
99

20,000
1,053
392
204
100

25,000
1,064
394
204
100

50,000
1,087
397
204
100

100,000
1,099
398
204
100

>100,000
1,111
400
204
100

Size of
Sample
Size (n) for precision of
Population
 ±5%
 ±7%
 ±10%
100
81
67
51

125
96
78
56

150
110
86
61

175
122
94
64

200
134
101
67

225
144
107
70

250
154
112
72

275
163
117
74

300
172
121
76

325
180
125
77

350
187
129
78

375
194
132
80

400
201
135
81

425
207
138
82

450
212
140
82

Using Formulas to Calculate a Sample Size
Although tables can provide a useful guide for determining the sample size, you may need to calculate the necessary sample size for a different combination of levels of precision, confidence, and variability. The fourth approach to determining sample size is the application of one of several formulas
·       Formulate a plan for doing the statistical analysis during the design stage of the project. Know how every question will be analyzed and be prepared to handle missing data. If you cannot specify how you intend to analyze a question or use the information, do not use it in the survey.
·       Give your questionnaire a title that is short and meaningful to the respondent. A questionnaire with a title is generally perceived to be more credible than one without
·       Use simple and direct language. The questions must be clearly understood by the respondent. The wording of a question should be simple and to the point
·       Place the most important items in the first half of the questionnaire
·       Items on a questionnaire should be grouped into logically coherent sections. Grouping questions that are similar will make the questionnaire easier to complete, and the respondent will feel more comfortable
There are good and bad questions. The qualities of a good question are as follows:
1. Evokes the truth. Questions must be non-threatening. Anonymous questionnaires that contain no identifying information are more likely to produce honest responses than those identifying the respondent. If your questionnaire does contain sensitive items, be sure to clearly state your policy on confidentiality.
2. Asks for an answer on only one dimension. A good question asks for only one "bit" of information. The purpose of a survey is to find out information. A question that asks for a response on more than one dimension will not provide the information you are seeking. For example, another questionnaire asks, "Were you satisfied with the quality of our food and service?" Again, if the respondent answers "no", there is no way to know whether the quality of the food, service, or both were unsatisfactory.
3. Can accommodate all possible answers. Asking a question that does not accommodate all possible responses can confuse and frustrate the respondent. For example, consider the question: What is your occupation: a) Teacher b) Nurse……………
·       Questionnaires are very cost effective when compared to face-to-face interviews. This is especially true for studies involving large sample sizes and large geographic areas. Written questionnaires become even more cost effective as the number of research questions increases.
·       Questionnaires are easy to analyze. Data entry and tabulation for nearly all surveys can be easily done with many computer software packages.
·       Questionnaires are familiar to most people. Nearly everyone has had some experience completing questionnaires and they generally do not make people fearful.
·       Questionnaires reduce bias. There is uniform question presentation and no middle-man bias. The researcher's own opinions will not influence the respondent to answer questions in a certain manner. There are no verbal or visual clues to influence the respondent.
·       Questionnaires are less intrusive than telephone or face-to-face surveys. When a respondent receives a questionnaire in the mail, he is free to complete the questionnaire on his own time-table. Unlike other research methods, the respondent is not interrupted by the research instrument.
·       One major disadvantage of written questionnaires is the possibility of low response rates. Low response is the curse of statistical analysis. It can dramatically lower our confidence in the results. Response rates vary widely from one questionnaire to another (10% - 90%), however, well-designed studies consistently produce high response rates.
·       Another disadvantage of questionnaires is the inability to probe responses. Questionnaires are structured instruments. They allow little flexibility to the respondent with respect to response format. In essence, they often lose the "flavor of the response" (i.e., respondents often want to qualify their answers). By allowing frequent space for comments, the researcher can partially overcome this disadvantage. Comments are among the most helpful of all the information on the questionnaire, and they usually provide insightful information that would have otherwise been lost.
·       Nearly ninety percent of all communication is visual. Gestures and other visual cues are not available with written questionnaires. The lack of personal contact will have different effects depending on the type of information being requested. A questionnaire requesting factual information will probably not be affected by the lack of personal contact. A questionnaire probing sensitive issues or attitudes may be severely affected.
·       When returned questionnaires arrive in the mail, it's natural to assume that the respondent is the same person you sent the questionnaire to. This may not actually be the case. Many times business questionnaires get handed to other employees for completion. Housewives sometimes respond for their husbands. Kids respond as a prank. For a variety of reasons, the respondent may not be who you think it is. It is a confounding error inherent in questionnaires.
·       Finally, questionnaires are simply not suited for some people. For example, a written survey to a group of poorly educated people might not work because of reading skill problems. More frequently, people are turned off by written questionnaires because of misuse.
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