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APPLICATION OF STATISTICAL METHODS IN RESEARCH

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Presentation on theme: "APPLICATION OF STATISTICAL METHODS IN RESEARCH"— Presentation transcript:

1 APPLICATION OF STATISTICAL METHODS IN RESEARCH
DR. M I PATEL DIRECTOR MERCHANT SCIENCE COLLEGE, BASNA

2 TYPES OF RESEARCH BASIC RESEARCH APPLIED RESEARCH
PROBLEM ORIENTED RESEARCH PROBLEM SOLVING QUANTITATIVE RESEARCH QUALOTATIVE RESEARCH

3 Basic Research The research which is done for knowledge enhancement, the research which does not have immediate commercial potential. The research which is done for human welfare, animal welfare and plant kingdom welfare. It is called basic, pure, fundamental research. The main motivation is to expand man's knowledge, not to create or invent something. According to Travers, “Basic Research is designed to add to an organized body of scientific knowledge and does not necessarily produce results of immediate practical value.” Such a research is time and cost intensive.

4 Applied Research Applied research is designed to solve practical problem of the modern world, rather than to acquire knowledge for knowledge’s sake. The goal of applied research is to improve the human condition. It focus on analysis and solving social and real life problems. This research is generally conducted on large scale basis, it is expensive. As such, it often conducted with the support of some financing agency like government , public corporation , world bank, UNICEF, UGC etc.

5 According to hunt, “applied research is an investigation for ways of using scientific knowledge to solve practical problems” for example:- improve agriculture crop production, treat or cure a specific disease, improve the energy efficiency homes, offices, how can communication among workers in large companies be improved? Applied research can be further classified as problem oriented and problem solving research.

6 Problem oriented research
Research is done by industry apex body for sorting out problems faced by all the companies. e.g.:- WTO does problem oriented research for developing countries, in India agriculture and processed food export development authority (APEDA) conduct regular research for the benefit of agri.-industry.

7 Problem solving This type of research is done by an individual company for the problem faced by it. Marketing research and market research are the applied research. For e.g.:- Videocon international conducts research to study customer satisfaction level, it will be problem solving research. In short, the main aim of applied research is to discover some solution for some pressing practical problem.

8 Quantitative Research
This research is based on numeric figures or numbers. Quantitative research aim to measure the quantity or amount and compares it with past records and tries to project for future period. In social sciences, “quantitative research refers to the systematic empirical investigation of quantitative properties and phenomena and their relationships”. The objective of quantitative research is to develop and employ mathematical models, theories or hypothesis pertaining to phenomena. The process of measurement is central to quantitative research because it provides fundamental connection between empirical observation and mathematical expression of quantitative relationships. Statistics is the most widely used branch of mathematics in quantitative research. Statistical methods are used extensively with in fields such as economics and commerce. Quantitative research involving the use of structured questions, where the response options have been Pre-determined and large number of respondents is involved. eg:-total sales of soap industry in terms of rupees cores and or quantity in terms of lakhs tones for particular year, say 2008,could be researched, compared with past 5 years and then projection for 2009 could be made.

9 Qualitative Research Qualitative research presents non-quantitative type of analysis. Qualitative research is collecting, analyzing and interpreting data by observing what people do and say. Qualitative research refers to the meanings, definitions, characteristics, symbols, metaphors, and description of things. Qualitative research is much more subjective and uses very different methods of collecting information, mainly individual, in-depth interviews and focus groups. The nature of this type of research is exploratory and open ended. Small number of people are interviewed in depth and or a relatively small number of focus groups are conducted. Qualitative research can be further classified in the following type.

10 Phenomenology:-a form of research in which the researcher attempts to understand how one or more individuals experience a phenomenon e.g.:-we might interview 20 victims of Bhopal tragedy. Ethnography:- this type of research focuses on describing the culture of a group of people. A culture is the shared attributes, values, norms, practices, language, and material things of a group of people e.g.:-the researcher might decide to go and live with the tribal in Andaman island and study the culture and the educational practices. Case study:-is a form of qualitative research that is focused on providing a detailed account of one or more cases. e.g.:-we may study a classroom that was given a new curriculum for technology use.

11 Historical research:-it allows one to discuss past and present events in the context of the present condition, and allows one to reflect and provide possible answers to current issues and problems. e.g.:-the lending pattern of business in the 19th century. In addition to the above, we also have the descriptive research. Fundamental research, of which this is based on establishing various theories

12 Also the research is classified in to 1. Descriptive research 2
Also the research is classified in to 1. Descriptive research 2. Analytical research 3. Fundamental research 4. Conceptual research 5. Empirical research 6. One time research or longitudinal research 7. Field-setting research or laboratory research or simulation research 8. Clinical or diagnostic research 9. Exploratory research 10.Historical research 11.conclusion oriented research 12.case study research 13.short term research

13 Application of Statistics in The Field Research

14 Why Study Statistics? Statistics is the science of collecting, analyzing and making inference from data. Statistics is a particularly useful branch of mathematics that is not only studied theoretically by advanced mathematicians but one that is used by researchers in many fields to organize, analyze, and summarize data.  Statistical methods and analyses are often used to communicate research findings and to support hypotheses and give credibility to research methodology and conclusions.  It is important for researchers and also consumers of research to understand statistics so that they can be informed, evaluate the credibility and usefulness of information, and make appropriate decisions.  

15 STATISTICS – WHAT AND WHY
THE WORD STATISTICS REFERS EITHER TO QUANTITATIVE INFORMATION OR A METHOD OF DEALING WITH QUANTITATIVE INFORMATION. WBESTER DEFINED STATISTICS AS THE CLASSIFIED FACTS RESPECTING THE CONDITION OF THE PEOPLE IN A STATE.

16 STATISTICS IS NOT A BODY OF SUBSTENTIVE KNOWLEDGE BUT A BODY OF METHODS FOR ORGANIZING KNOWLEDGE.
IT IS A SCIENCE OF COLLECTION, ORGANIZATION, PRESENTATION, ANALYSIS AND INTERPRETATION OF NUMERICAL DATA.

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21 Sequence of Statistical Investigation
Stage – 1: Planning of Statistical Investigation Stage – 2: Collection of Data Stage – 3: Editing of Data Stage – 4: Presentation of Data Stage – 5: Analysis of Data Stage – 6: Interpretation of Data Stage – 7: preparation of the Report

22 Planning of Statistical Investigation
Object and Scope of enquiry Formulation of Statistical Units Types of Investigation Degree of Accuracy

23 Establishing Goals The first step in any survey is deciding what you want to learn. The goals of the project determine whom you will survey and what you will ask them. If your goals are unclear, the results will probably be unclear. Some typical goals include learning more about: The potential market for a new product or service Ratings of current products or services Employee attitudes Customer/patient satisfaction levels Reader/viewer/listener opinions Association member opinions Opinions about political candidates or issues Corporate images These sample goals represent general areas. The more specific you can make your goals, the easier it will be to get usable answers.

24 Selecting Your Sample There are two main components in determining whom you will interview. The first is deciding what kind of people to interview. Researchers often call this group the target population. If you conduct an employee attitude survey or an association membership survey, the population is obvious. If you are trying to determine the likely success of a product, the target population may be less obvious. Correctly determining the target population is critical. If you do not interview the right kinds of people, you will not successfully meet your goals. The next thing to decide is how many people you need to interview. Statisticians know that a small, representative sample will reflect the group from which it is drawn. The larger the sample, the more precisely it reflects the target group. However, the rate of improvement in the precision decreases as your sample size increases. For example, to increase a sample from 250 to 1,000 only doubles the precision. You must make a decision about your sample size based on factors such as: time available, budget and necessary degree of precision. The Survey System (and this Web site) includes a sample size calculator that can help you decide on the sample size (jump to the calculator page for a general discussion of sample size considerations).

25 Collecting Data Once you have decided what types of data you need for your study, you can determine whether your data can be gathered from existing sources/databases or whether you need to collect new information through other means.  Even when using existing data, it is important to know how the data was collected so that the limitations of the generalizability of results may be determined and the proper analyses may be performed. 

26 Survey Design Knowing what the client wants is the key factor to success in any type of business. News media, government agencies and political candidates need to know what the public thinks. Associations need to know what their members want. Large companies need to measure the attitudes of their employees. The best way to find this information is to conduct a survey. This chapter is intended primarily for those who are new to survey research. It discusses options and provides suggestions on how to design and conduct a successful survey project. It does not provide instruction on using specific parts of The Survey System, although it mentions parts of the program that can help you with certain tasks.

27 Collection of Data Sources of Secondary Data
The values recorded in an experiment or observation are called Data. The Data is of Two types : A. Primary Data B. Secondary Data Sources of Secondary Data A. Published sources B. Unpublished sources

28 Methods of data collection
A. Direct personal investigation B. Indirect oral investigation C. Information through correspondents D. The questionnaire method E. Experiments F. Census G. Sampling method

29 Interviewing Methods

30 Personal Interviews An interview is called personal when the Interviewer asks the questions face-to-face with the Interviewee. Personal interviews can take place in the home, at a shopping mall, on the street, outside a movie theater or polling place, and so on.

31 Telephone Surveys Surveying by telephone is the most popular interviewing method in the USA. This is made possible by nearly universal coverage (96% of homes have a telephone).

32 Mail Surveys Mail surveys are among the least expensive.
This is the only kind of survey you can do if you have the names and addresses of the target population, but not their telephone numbers. The questionnaire can include pictures - something that is not possible over the phone. Mail surveys allow the respondent to answer at their leisure, rather than at the often inconvenient moment they are contacted for a phone or personal interview. For this reason, they are not considered as intrusive as other kinds of interviews.

33 Computer Direct Interviews
These are interviews in which the Interviewees enter their own answers directly into a computer. They can be used at malls, trade shows, offices, and so on. The Survey System's optional Interviewing Module and Interview Stations can easily create computer-direct interviews. Some researchers set up a Web page survey for this purpose.

34 Internet/Intranet (Web Page) Surveys
Web surveys are rapidly gaining popularity. They have major speed, cost, and flexibility advantages, but also significant sampling limitations. These limitations make software selection especially important and restrict the groups you can study using this technique.

35 Scanning Questionnaires
Scanning questionnaires is a method of data collection that can be used with paper questionnaires that have been administered in face-to-face interviews; mail surveys or surveys completed by an Interviewer over the telephone. The Survey System can produce paper questionnaires that can be scanned using Remark Office OMR (available from CRS). Other software can scan questionnaires and produce ASCII Files that can be read into The Survey System.

36 Question Types Researchers use three basic types of questions: multiple choice, numeric open end and text open end (sometimes called "verbatim"). Examples of each kind of question follow:

37 Rating Scales and Agreement Scales are two common types of questions that some researchers treat as multiple choice questions and others treat as numeric open end questions. Examples of these kinds of questions are:

38 Editing of Data Editing is done to make the data consistent and uniform, complete and accurate. It is the process of editing is by no means an unimportant and routine operation; rather it requires marked ability scrupulous and rigid adherence to scientific objectivity.

39 Definition - What does Data Organization mean?
Data organization, in broad terms, refers to the method of classifying and organizing data sets to make them more useful. Some IT experts apply this primarily to physical records, although some types of data organization can also be applied to digital records.

40 Types of Classification:
Presentation of Data After having collected that data, it is classified and presented in tabulated form to make it intelligible Types of Classification: Geographical Chronological Qualitative Quantitative

41 Tabulation of Data Parts of Table Table number Title Head note Caption
Stub Body Foot Note Source

42 Graphical Representation of Data

43 Introduction Whenever verbal problems involving a certain situation is presented visually before the learners, it makes easier for the learner to understand the problem and attempt its solution. Similarly, when the data are presented pictorially (or graphically) before the learners, it makes the presentation eye-catching and more intelligible. The learners can easily see the salient features of the data and interpret them.

44 Inventor of graphs: William Play fair ( ), Scottish engineer and political economist, is the principal inventor of statistical graphs. In 1786, he published “Commercial and Political Atlas” that contained 44 charts.

45 Continued.. He invented three of the four basic forms of graph:
The statistical line graph The bar graph The pie graph

46 Types of Graphs Line graphs -Polygraph Bar graphs Pie graphs
Flow Charts

47 1. Line Graph The line graphs are usually drawn to represent the time series data Example: temperature, rainfall, population growth, birth rates and the death rates.

48 Line Graph

49 Polygraph Polygraph is a line graph in which two or more than two variables are shown on a same diagram by different lines. It helps in comparing the data. Examples which can be shown as polygraph are: The growth rate of different crops like rice, wheat, pulses in one diagram. The birth rates, death rates and life expectancy in one diagram. Sex ratio in different states or countries in one diagram.

50 Polygraph

51 Bar graphs It is also called a columnar diagram. The bar diagrams are drawn through columns of equal width. Following rules were observed while constructing a bar diagram: (a) The width of all the bars or columns is similar. (b) All the bars should are placed on equal intervals/distance. (c) Bars are shaded with colours or patterns to make them distinct and attractive.

52 Types of Bar graphs Three Types of Bar graphs are used to represent different data sets: The simple bar diagram Compound bar diagram Polybar diagram

53 The simple bar diagram A simple bar diagram is constructed for an immediate comparison. It is advisable to arrange the given data set in an ascending or descending order and plot the data variables accordingly. However, time series data are represented according to the sequencing of the time period.

54 The simple bar diagram

55 Compound bar diagram When different components are grouped in one set of variable or different variables of one component are put together, their representation is made by a compound bar diagram. In this method, different variables are shown in a single bar with different rectangles.

56 Compound bar diagram

57 Polybar diagram The line and bar graphs as drawn separately may also be combined to depict the data related to some of the closely associated characteristics such as the climatic data of mean monthly temperatures and rainfall.

58 Polybar diagram

59 Pie graphs Pie diagram is another graphical method of the representation of data. It is drawn to depict the total value of the given attribute using a circle. Dividing the circle into corresponding degrees of angle then represent the sub– sets of the data. Hence, it is also called as Divided Circle Diagram.

60 Pie graphs

61 Flow Maps/Chart Flow chart is a combination of graph and map. It is drawn to show the flow of commodities or people between the places of origin and destination. It is also called as Dynamic Map. Transport map, which shows number of passengers, vehicles, etc., is the best example of a flow chart.

62 Conclusion If the information is presented in tabular form or in a descriptive record, it becomes difficult to draw results. Graphical form makes it possible to easily draw visual impressions of data. The graphic method of the representation of data enhances our understanding. It makes the comparisons easy. Besides, such methods create an imprint on mind for a longer time

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65 Measures of Dispersion or Deviation
Dispersion or spread is the degree of the scatter or variation of the variable about a central value. Standard Deviation(S.D.) Karl Pearson introduced the concept of standard Deviation in 1893. It is defined as the positive square – root of the arithmetic mean of the square of the deviations of the given observation from there arithmetic mean. It is represented by the Greek letter ð (Small sigma)

66 Regression Analysis Regression is the measures of the average relationship between two or more variables in terms of the original units of the data. In Regression analysis, two variables are involved. One variable is called dependent variable and the other is called independent variable.

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68 Correlation Analysis Correlation Analysis is the study of relationship between two or more variables. It is the co-variation of two variables. The measure of correlation is called Correlation Coefficient.

69 Chi-Square Test and Goodness of Fit
Chi-Square Test (x2) is a measure to study the difference of actual and expected frequencies. The test is based on events or frequencies and not based on mean or S.D, etc.

70 Analysis of Variance (ANOVA)
Analysis of variance refers to the examination of differences among the samples it is used to examine the significance of the difference amongst more thane two sample means at the same time. We take two estimates of population variance that is one based on between samples of variance and the other within sample variance

71 These two estimates of population variance are compared with ‘F’ test as follows.
Variance between samples F= Variance within samples

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