Rai University , 24-25 November 2014 Dr Kishor Bhanushali Associate Professor Unitedworld School of Business Mob: 9898422620 Email: kishorkisu@gmail.com Rai University , 24-25 November 2014

Research Proposal The Problem and statement of the problem. The Review of literature or theoretical framework of the study. The Hypotheses and objectives. The Methodology and procedure of the study. Educational implications or significance of the problem. Definitions, assumptions and delimitations. A tentative structure of the report. Bibliography.

Research Process Formulating the research problem Extensive literature survey Developing the hypothesis Preparing the research design Determining sample design Collecting the data; Execution of the project; Analysis of data Hypothesis testing Generalizations and interpretation Preparation of the report or presentation of the results, i.e., formal write-up of conclusions reached.

Research Design (i) What is the study about? (ii) Why is the study being made? (iii) Where will the study be carried out? (iv) What type of data is required? (v) Where can the required data be found? (vi) What periods of time will the study include? (vii) What will be the sample design? (viii) What techniques of data collection will be used? (ix) How will the data be analysed? (x) In what style will the report be prepared?

Measurement Measurement is a relatively complex and demanding task, specially so when it concerns qualitative or abstract phenomena By measurement we mean the process of assigning numbers to objects or observations properties like weight, height, etc., can be measured directly with some standard unit of measurement, but it is not that easy to measure properties like motivation to succeed, ability to stand stress and the like Technically speaking, measurement is a process of mapping aspects of a domain onto other aspects of a range according to some rule of correspondence

Measurement Scales Nominal scale : Simply a system of assigning number symbols to events in order to label them. - basketball players Ordinal scale : Places events in order - student’s rank Interval scale : Intervals are adjusted in terms of some rule, lack of a true zero Ratio scale : absolute or true zero of measurement-height, weight, marks

Sources of Error in Measurement Respondent : reluctant to express strong negative feeling, fatigue, boredom, anxiety, Situation: distortions Measurer: behaviour, style and looks Instrument :defective measuring instrument, complex words

Tests of Sound Measurement Validity ,Reliability, Practicality Validity refers to the extent to which a test measures what we actually wish to measure Reliability has to do with the accuracy and precision of a measurement procedure Practicality is concerned with a wide range of factors of economy, convenience, and interpretability

Scaling Measurement problem in measuring attitudes and opinions Procedures for attempting to determine quantitative measures of subjective abstract concepts Scaling describes the procedures of assigning numbers to various degrees of opinion, attitude and other concepts (I) making a judgement about some characteristic of an individual and then placing him directly on a scale that has been defined in terms of that characteristic and (ii) constructing questionnaires in such a way that the score of individual’s responses assigns him a place on a scale

Scale Classification Bases (a) subject orientation; characteristics of the respondent (b) response form; categorical and comparative (c) degree of subjectivity; subjective personal preferences or simply make non-preference judgement (d) scale properties; nominal, ordinal, interval and ratio scales (e) number of dimensions : ‘unidimensional’ and ‘multidimensional’ scales (f) scale construction techniques

Scale Classification Bases (a) subject orientation; characteristics of the respondent (b) response form; categorical and comparative (c) degree of subjectivity; subjective personal preferences or simply make non-preference judgement (d) scale properties; nominal, ordinal, interval and ratio scales (e) number of dimensions : ‘unidimensional’ and ‘multidimensional’ scales (f) scale construction techniques

Hypothesis Testing Hypothesis testing enables us to make probability statements about population parameter(s) Mere assumption or some supposition to be proved or disproved. Formal question that he intends to resolve. Predictive statement, capable of being tested by scientific methods Hypothesis states what we are looking for and it is a proposition which can be put to a test to determine its validity

Characteristics of Hypothesis Hypothesis should be clear and precise Hypothesis should be capable of being tested Hypothesis should state relationship between variables Hypothesis should be limited in scope and must be specific Hypothesis should be stated as far as possible in most simple terms Hypothesis should be consistent with most known facts Hypothesis should be amenable to testing within a reasonable time Hypothesis must explain the facts that gave rise to the need for explanation

Null Hypothesis And Alternative Hypothesis The null hypothesis and the alternative hypothesis are chosen before the sample is drawn (the researcher must avoid the error of deriving hypotheses from the data that he collects and then testing the hypotheses from the same data) Alternative hypothesis is usually the one which one wishes to prove and the null hypothesis is the one which one wishes to disprove Null hypothesis should always be specific hypothesis

The Level Of Significance 5 per cent level of significance means that researcher is willing to take as much as a 5 per cent risk of rejecting the null hypothesis when it (H0) happens to be true. Thus the significance level is the maximum value of the probability of rejecting H0 when it is true and is usually determined in advance before testing the hypothesis

Decision rule or test of hypothesis Given a hypothesis H0 and an alternative hypothesis Ha, we make a rule which is known as decision rule according to which we accept H0(i.e., reject Ha) or reject H0(i.e., accept Ha).

Type I And Type II Errors We may reject H0 when H0 is true and we ma Type I error means rejection of hypothesis which should have been accepted Type II error means accepting the hypothesis which should have been rejected Type I error is denoted by α(alpha)known as α error, also called the level of significance of test

Two-tailed And One-tailed Tests

Procedure For Hypothesis Testing Making a formal statement Selecting a significance level Deciding the distribution to use Selecting a random sample and computing an appropriate value Calculation of the probability Comparing the probability

Flow Diagram For Hypothesis Testing

Unitedworld School of Business Thanks Dr Kishor Bhanushali Associate Professor Unitedworld School of Business Mob: 9898422620 Email: kishorkisu@gmail.com