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100 | _aKOTHARI C R | ||
245 | 0 | _aRESEARCH METHODOLOGY METHODS AND TECHNOLOGY | |
260 | _bNEW AGE INTERNATIONAL | ||
650 | _aResearch Methodology: An Introduction 1 Meaning of Research Objectives of Research Motivation in Research Types of Research Research Approaches Significance of Research Research Methods versus Methodology Research and Scientific Method Importance of Knowing How Research is Done Research Process Criteria of Good Research Problems Encountered by Researchers in India Defining the Research Problem What is a Research Problem? Selecting the Problem Necessity of Defining the Problem Technique Involved in Defining a Problem An Illustration Research Design Meaning of Research Design Need for Research Design xii Research Methodology Features of a Good Design Important Concepts Relating to Research Design Different Research Designs Basic Principles of Experimental Designs Developing a Research Plan . Sampling Design Census and Sample Survey Implications of a Sample Design Steps in Sampling Design Criteria of Selecting a Sampling Procedure Characteristics of a Good Sample Design Different Types of Sample Designs How to Select a Random Sample? Random Sample from an Infinite Universe Complex Random Sampling Designs Measurement and Scaling Techniques Measurement in Research Measurement Scales Sources of Error in Measurement Tests of Sound Measurement Technique of Developing Measurement Tools Scaling Meaning of Scaling Scale Classification Bases Important Scaling Techniques Scale Construction Techniques 6. Methods of Data Collection Collection of Primary Data Observation Method Interview Method Collection of Data through Questionnaires Collection of Data through Schedules Difference between Questionnaires and Schedules Some Other Methods of Data Collection Collection of Secondary Data Selection of Appropriate Method for Data Collection Case Study Method Guidelines for Constructing Questionnaire/Schedule Guidelines for Successful Interviewing Difference between Survey and Experiment Processing and Analysis of Data Processing Operations Some Problems in Processing Elements/Types of Analysis Statistics in Research Measures of Central Tendency Measures of Dispersion Measures of Asymmetry (Skewness) Measures of Relationship Simple Regression Analysis Multiple Correlation and Regression Partial Correlation Association in Case of Attributes Other Measures Appendix: Summary Chart Concerning Analysis of Data Sampling Fundamentals Need for Sampling Some Fundamental Definitions Important Sampling Distributions Central Limit Theorem Sampling Theory Sandler’s A-test Concept of Standard Error Estimation Estimating the Population Mean () Estimating Population Proportion Sample Size and its Determination Determination of Sample Size through the Approach Based on Precision Rate and Confidence Level Determination of Sample Size through the Approach Based on Bayesian Statistics Research Methodology Testing of Hypotheses-I (Parametric or Standard Tests of Hypotheses) What is a Hypothesis? Basic Concepts Concerning Testing of Hypotheses Procedure for Hypothesis Testing Flow Diagram for Hypothesis Testing Measuring the Power of a Hypothesis Test Tests of Hypotheses Important Parametric Tests Hypothesis Testing of Means Hypothesis Testing for Differences between Means Hypothesis Testing for Comparing Two Related Samples Hypothesis Testing of Proportions Hypothesis Testing for Difference between Proportions Hypothesis Testing for Comparing a Variance to Some Hypothesized Population Variance Testing the Equality of Variances of Two Normal Populations Hypothesis Testing of Correlation Coefficients Limitations of the Tests of Hypotheses Chi-square Test Chi-square as a Test for Comparing Variance Chi-square as a Non-parametric Test Conditions for the Application of 2 Test Steps Involved in Applying Chi-square Test Alternative Formula Yates’ Correction Conversion of 2 into Phi Coefficient Conversion of 2 into Coefficient by Contingency Important Characteristics of 2 Test Caution in Using 2 Test Analysis of Variance and Covariance Analysis of Variance (ANOVA) What is ANOVA? The Basic Principle of ANOVA ANOVA Technique Setting up Analysis of Variance Table Short-cut Method for One-way ANOVA Coding Method Two-way ANOVA ANOVA in Latin-Square Design Analysis of Co-variance (ANOCOVA) ANOCOVA Technique Assumptions in ANOCOVA Testing of Hypotheses-II (Nonparametric or Distribution-free Tests) Important Nonparametric or Distribution-free Test Relationship between Spearman’s r’s and Kendall’s W Characteristics of Distribution-free or Non-parametric Tests Conclusion Multivariate Analysis Techniques Growth of Multivariate Techniques Characteristics and Applications Classification of Multivariate Techniques Variables in Multivariate Analysis Important Multivariate Techniques Important Methods of Factor Analysis Rotation in Factor Analysis R-type and Q-type Factor Analyses Path Analysis Appendix: Summary Chart: Showing the Appropriateness of a Particular Multivariate Technique . Interpretation and Report Writing Meaning of Interpretation Why Interpretation? Technique of Interpretation: Precaution in Interpretation Significance of Report Writing Different Steps in Writing Report Layout of the Research Report Types of Reports Oral Presentation Mechanics of Writing a Research Report Precautions for Writing Research Reports The Computer: It’s Role in Research The Computer and Computer Technology The Computer System Important Characteristics The Binary Number System Computer Applications Computers and Researcher | ||
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