REFLECTION................

hello mam,

       Research Methodology classes are going on very well.

      Day by day am very interested for learning new things from you. so, am very happy about that, this week you discussed about internal and external validity,establishment of reliability and along with that you thought us about methods of checking validity and reliability,characteristics of good test  etc..........

     The concept was very clearly explained.The  illustrations which  was given by you was very interesting.

The class notes which you gave was very simple and easy to grasp the content.

     Am also referring some books related to the topic 



                                                                  THANK YOU MAM

Reflection.....

Hi mam,

        This week as learner i learnt ample number of things..You taught us about three types of  tools and explained about the sub terms in  detail with relevant illustrations so that the concept was very easy to follow.

       This week i learnt many new things about the subject and am very happy to share this......I was very clear how to proceed over my research topic as  u said about the definition,sample,content and format.

      You also discussed about content validity,criterion related evidence of validity which is divided into two predict validity and concurrent validity and u also gave very beautiful example for this, along with that validity co-efficient and construct validity was explained in a clear manner.

   I fully enjoyed this week as a learner..

                                                                    THANK UUUUU ,MAM

Assignment:

1. What is data?

.Data is a collection of facts, such as values or measurements.

It can be numbers, words, measurements, observations or even just descriptions of things.

Qualitative vs Quantitative

Data can be qualitative or quantitative.

• Qualitative data is descriptive information (it describes something)

Quantitative data, is numerical information (numbers)

2.       Explain the term ‘Instrumentation’.

Instrumentation is a branch of physics which deals with the measuring and controlling variables in a process industry, the instruments related to the process variables and its calibration. Some of  the industrial process variables are Level, Pressure, Temperature, Humidity, Flow, pH, Force, Speed etc,. The technology which used to design and develop an instrument for the measurement and control is called instrumentation technology.

Definition: Instrumentation is defined as "the art and science of measurement and control".

3.The three different ways in which data can be collected are:

       a)observation

       b)questionnaire

       c)interview

4.       Explain ‘data-collection instrument’.

        Refers to the device used to collect data, such as a paper questionnaire or computer assisted interviewing system.

5.       List down the various types of instruments and describe them in detail.

The various types of instruments are researcher  complete instrument, subject complete instrument and informant instrument

Researcher complete instruments:

1.   Rating scale 2. Interview schedule 3. Tally sheet 4. Flow chart 5. Performance check list 6. Anecdotal records 7. Time-emotion logs

Subject complete instruments:

1.questionnaires 2. Self checklist 3. Attitude scale 4. Performance inventories 5. aptitude test 6. Achievement test 7. Performance test 8. Projective devices 9. Sociometric devices

6.       Explain what is meant by the term ‘unobtrusive measures’ 

     Unobtrusive measures are measures that don't require the researcher to intrude in the research context. Direct and participant observation require that the researcher be physically present. This can lead the respondents to alter their behavior in order to look good in the eyes of the researcher. A questionnaire is an interruption in the natural stream of behavior. Respondents can get tired of filling out a survey or resentful of the questions asked.

Unobtrusive measurement presumably reduces the biases that result from the intrusion of the researcher or measurement instrument. However, unobtrusive measures reduce the degree the researcher has control over the type of data collected. For some constructs there may simply not be any available unobtrusive measures.

7.       Name the types of measurement scales you have learnt and give examples of each.

      An easy way to have a paper rejected is to have used either an incorrect scale/statistic combination or to have used a low powered statistic on a high powered set of data.

• Nominal
• Ordinal
• Interval
• Ratio

---

Nominal

The lowest measurement level you can use, from a statistical point of view, is a nominal scale.A nominal scale, as the name implies, is simply some placing of data into categories, without any order or structure.
A physical example of a nominal scale is the terms we use for colours. The underlying spectrum is ordered but the names are nominal.
In research activities a YES/NO scale is nominal. It has no order and there is no distance between YES and NO.


and statisticsThe statistics which can be used with nominal scales are in the non-parametric group. The most likely ones would be:


mode
crosstabulation - with chi-square
There are also highly sophisticated modelling techniques available for nominal data.

---

Ordinal

An ordinal scale is next up the list in terms of power of measurement.The simplest ordinal scale is a ranking. When a market researcher asks you to rank 5 types of beer from most flavourful to least flavourful, he/she is asking you to create an ordinal scale of preference.
There is no objective distance between any two points on your subjective scale. For you the top beer may be far superior to the second prefered beer but, to another respondant with the same top and second beer, the distance may be subjectively small.
An ordinal scale only lets you interpret gross order and not the relative positional distances.


and statisticsOrdinal data would use non-parametric statistics. These would include:


Median and mode
rank order correlation
non-parametric analysis of variance
Modelling techniques can also be used with ordinal data.

---

Interval

The standard survey rating scale is an interval scale.
When you are asked to rate your satisfaction with a piece of software on a 7 point scale, from Dissatisfied to Satisfied, you are using an interval scale.
It is an interval scale because it is assumed to have equidistant points between each of the scale elements. This means that we can interpret differences in the distance along the scale. We contrast this to an ordinal scale where we can only talk about differences in order, not differences in the degree of order.
Interval scales are also scales which are defined by metrics such as logarithms. In these cases, the distances are note equal but they are strictly definable based on the metric used.
and statistics
Interval scale data would use parametric statistical techniques:
Mean and standard deviation
Correlation - r
Regression
Analysis of variance
Factor analysis
Plus a whole range of advanced multivariate and modelling techniquesRemember that you can use non-parametric techniques with interval and ratio data. But non-parametric techniques are less powerful than the parametric ones.

---

Ratio

A ratio scale is the top level of measurement and is not often available in social research.The factor which clearly defines a ratio scale is that it has a true zero point.
The simplest example of a ratio scale is the measurement of length (disregarding any philosophical points about defining how we can identify zero length).The best way to contrast interval and ratio scales is to look at temperature. The Centigrade scale has a zero point but it is an arbitrary one. The Fahrenheit scale has its equivalent point at -32o. (Physicists would probably argue that Absolute Zero is the zero point for temperature but this is a theoretical concept.) So, even though temperature looks as if it would be a ratio scale it is an interval scale. Currently, we cannot talk about no temperature - and this would be needed if it were a ration scale.

hi mam..

 Classes are going on well

      Last class you discussed about 'data', it was very clearly explained by you mam.
     You explained about three types of tools or instrument
                                   a)Researcher tool
                                   b)subject tool
                                   c)Informant tool

  The concept was very well explained by you based on some simple examples.The examples was based on the class room so that it was very easy to understand the topic without any doubt.
       
  You asked me to write objectives for new English books referring the old book .I have tried my level best in writing the objectives for that. I have also collected some information based on my research topic i.e. writing skill.

                  Am learning new thing everyday mam.

         I hope my journey with you will change my life. 

                                                                                                                  Thank you mam

Reflection

Hello Mam,

       Good afternoon ,

                   " Advance happy vinayagar chadurthi" 

    Research methodology classes are going on.

    This week in our class you discussed generalisability, population generalisability, ecological generalisability, external validity, sampling error, voluntary sampling, incidental sampling and so on.

     The topics were explained very clearly by you. I was able to understand the concepts taught by you. I also got an idea to relate these topics in research area. 

       This week friday we had short discussion  about our research topic you gave us a lots of books regarding our research topic. I found out my topic that is, writing skills in that book .

    I am also collecting valuable information from the book. I am working over the topic. The book was fascinating me. I am referring some library books.

    It gives me immense pleasure to join hands with you. I am learning new things from you every day mam.

     Susan mam has come all the way to our Pondicherry University as a Guest Lecturer. I was very much inspired by her way of teaching. She shared with us the experience of teaching in her place and was very patient in answering our questions. Her class was very interactive. 

     our dean mam Lalithamma also handled research methodology classes which was very interesting. 

     This week the teachers day celebrations were very enjoyable and the speech of all the teachers were inspiring to me.

    Thank you mam.

Assignment...

1. ‘Generalizability’ in Sampling:

A sample should be as large as the researcher can obtain a reasonable expenditure of time and energy as large as they reasonably can.

2. Distinguish sample from population:

A sample is a small proportion of a population selected for observation and analysis. By observing the characteristics of the sample, one can make certain inferences about the characteristics of the population from which it is drawn. But a population is any group of individuals that have one or more characteristics in common that are of interest to the researcher.

3. meaning of the term “representative sample”:

A subset of a statistical population that accurately reflects the members of the entire population. A representative sample should be an unbiased indication of what the population is like. In a classroom of 30 students in which half the students are male and half are female, a representative sample might include six students: three males and three females.

4.Explain how a target population differs from an accessible population.

Target population (universe):

The entire group of people or objects to which the researcher wishes to generalize the study findings

Meet set of criteria of interest to researcher

Examples

All institutionalized elderly with Alzheimer's

All people with AIDS

Accessible population:

the portion of the population to which the researcher has reasonable access; may be a subset of the target population

May be limited to region, state, city, county, or institution

Examples

All institutionalized elderly with Alzheimer's in St. Louis county nursing homes

All people with AIDS in the metropolitan St. Louis area.

5. What is meant by randomization? Explain ‘random selection’ and ‘random assignment’ in  sampling?

In this sampling technique, the researcher must guarantee that every individual has an equal opportunity for selection and this can be achieved if the researcher utilizes randomization.

Random selection is how you draw the sample of people for your study from a population. 

Randomassignment is how you assign the sample that you draw to different groups or treatments in your study.

6. Three ways of obtaining  Random Sampling:

Simple random sampling:

Simple random sampling means that every member of the sample is selected from the total population in such a manner that all members of the population have essentially the same probability of being selected.

Incidental sampling:

It applies to those group which are used chiefly because they are easily or readily constituted radon, sample of any definable population. 

Purposive sampling:

It can be considered a form of stratified sampling in that the selection of cases is governed by some criterion acting as a secondary control.

7. What are the situations in which a researcher goes for non-random sampling?

Non-random sampling is useful when time is limited, a sampling frame is not available, the research budget is very tight or when detailed accuracy is not important.

A researcher may not be able to obtain a random or stratified sample, or it may be too expensive. A researcher may not care about generalizing to a larger population. The validity of non-probability samples can be increased by trying to approximate random selection, and by eliminating as many sources of bias as possible, in that situation a researcher goes for non-random sampling.

8. Explain non-random sampling techniques with examples.

Forms of sampling that do not adhere to probability methods. Probability methods choose samples using random selection and every member of the population has an equal chance of selection. Some types of nonrandom sampling still aim to achieve a degree of representativeness without using random methods. Several different techniques are associated with this approach, for example accidental or convenience sampling; snowball sampling; volunteer sampling; quota sampling, and theoretical sampling. Convenience samples are also known as accidental or opportunity samples. The problem with all of these types of samples is that there is no evidence that they are representative of the populations to which the researchers wish to generalize. 

9.  What does a table of random numbers mean?

A table of numbers generated in an unpredictable, haphazard sequence. Tables of random numbers are used to create a random samples. A random number table is therefore also called a random sample table. A random number table is a list of numbers, composed of the digits 0, 1, 2, 3, 4, 5, 6, 7, 8, and 9. Numbers in the list are arranged so that each digit has no predictable relationship to the digits that preceded it or to the digits that followed it.

10. Explain what is meant by the term ‘ external validity’.

This refers to the extent to which the results of a study can be generalized or extended to others. For example, if a study on a drug is only conducted on white, middle aged, overweight, women with diabetes, can the results of the study be generalized to the rest of the population? Are the results only valid to the population studied? Researchers go to great lengths to select a group of people for the study (a sample) that is representative enough that the results can be extended to lots of people.

11. Explain ‘population generalizability’ and  ‘ ecological generalizability’.

Population generalizability:  It refers to the degree to which a sample represents the population of interest.

Ecological generalizability:  The degree to which results of a study can be extended to other settings of the condition or settings other than those that prevalent in a particular study.

12.Write briefly on ‘sample size’ and ‘sampling ratio’.

Sample size: The determination of sample size is a common task for many organizational researchers. Inappropriate, inadequate, or excessive sample sizes continue to influence the quality and accuracy of research. 

Sample ratio:Sampling ratio is size of sample divided by size of population.

13. What does sampling error mean? Explain.

Sampling error is simply the difference between the value of parameter and that of corresponding statistic or the difference between population value and sample value.