Introduction: Research in business, What is research? Business research defined, Criteria of good research, The manager-research relationship. Types of research, Research and scientific method; Scientific Thinking: Styles of thinking, The thought process: Reasoning- Deduction, Induction, Reflective thinking and the scientific method, Understanding theory: and connections- concepts, Constructs, Definitions, Variables, propositions and hypotheses, Theory and models; The Research process: Phases of research process, Research needs, Formulating the problem, Designing the study, Sampling, Research proposal, Pilot testing, Data collection, Analysis and interpretation, Reporting the results, the value of research information, Decision theory approach; The research proposal: Value, Types, Structuring the Research proposal Executive Summary, Problem Statement, Research Objectives, Literature Review, Importance, Benefits of the study, Research Design, Data Analysis, Nature and Form of Results, Budget, Schedule, Special Resources - Evaluating the Research Proposal. The Design of Research: What is Research Design? Exploratory Studies, Descriptive Studies, Causal Studies -the concept of cause, causal relationships, Testing causal hypothesis. Measurement: The Nature of Measurement - What is measured? Measurement Scales- Nominal, ordinal, Interval, Ratio, Sources of Measurement Differences Characteristics of Sound Measurement: Reliability - Stability, Equivalence, Internal Consistency Error Sources, The Cronbach's Alpha; Validity - External Validity - Statistical Conclusion Validity, Internal Validity - Content Validity, Criterion Related Validity, Construct Validity; Practicality Economy. Convenience, Interpretability. Scaling Design: Scaling Defined, Scale Classification: Response, Rating Scales, Ranking Scales; Scale Construction Techniques Arbitrary Scales. Consensus Scaling. Item Analysis. Cumulative Scales, Factor Scales, Other Scaling Techniques. Methods Sampling Design: Probability's of Sampling Why sample? What is Good sample? Types of Sampling Design; Probability Sampling - Steps, Sampling Concepts: Sampling Frame, Sample Size Determination: complex Probability Sampling - Systematic Sampling, Stratified Sampling, Cluster Sampling: Non - probability Sampling - Methods - Purposive Sampling. Hypothesis Testing: What is hypothesis? Testing Approaches. Statistical Significance. The login of Hypothesis Testing - Null Hypothesis. Alternative Hypothesis, one-tailed and two-tailed test, Type 1 and Type II Error. Power of a Test: Statistical procedure: Tests of Significance: Types of Tests - Parametric - t and z test and Non parametric tests chi-square test. Measure of Association: Bivariate correlation Analysis - Pearson's product Moment Coefficient r. The assumption of r, Computation of and testing oft. Correlation Matrix, Partial Correlation and Multiple Correlation; Interpretation of Correlation Coefficients: Bivariate Linear Regression Method of Least Squares, Predictions, Testing the Goodness of Fit, ABIVAM ABCIVA. Distribution tests rank transformations for single samples Matching samples to distribution, robustness, transformation of ranks, implications of efficiency, The Kolmogorov Goodness of Fit Test: Contingency Tables: The median test, Measures of Dependence - The Chi-Square Goodness-of-Fit Test. Cochran's test for related observation q. Log-linear models, field of Applications. Qualitative Dependent Variable Data: Dichotomous classification or multi classification, Discriminant or multiple discriminant analysis, Logit or probit analysis, Latent variable through items wise analysis factor analysis. Methods for paired samples and based on ranks: Comparisons in pairs, Sign test, filed or application, two independent samples Wilcoxon Mann Whitney Test, Several Independent Samples, Test for qualify of variance, Field of Application. The Structure and the Model: The Model, Functional Forms and Stochastic Terms, Specification of the Model and Disturbance Term. Regression and Correlation Model (1): The Framework of the Ordinary Least Squares Regression Model, The Mathematics of the OLS Method, The nature of the Disturbances Assumption on the Disturbance in a Regression Model, Rank Condition in a Multiple Regression Model, Extension of OLS to the Multiple Regression Model, properties of the OLS method BLUE Unbiasedness of OLS Estimator, Best(Efficient) Linear Estimator. Regression and Correlation Model(II): Estimation of Parameter of Regression, Estimation of Variance of Beta hat Estimator, Interpretation of Regression Result. Heteroscedasticity: Violation of Homoscedasticity, Implication of heteroscedastic on estimation of parameter and its significance, Estimation of the presence of Heteroscedasticity - Goldfield - Quant Test, and Correction of the problem. Serial Correlation: What is serial correlation, First order Auto- regressive Model of Disturbance Term, Test ot identify auto correlation Durbin- Watson Test, Implication S/E, OLS in presence of serial correlation-First Difference Method, Cochran- Orcutt Method, Durbin's Method. Report Writing: Research Report Format- Prefatory items, Introduction- Problem Statement, Research objectives, Background; Methodology- Sampling Design, Research Design, Data collection, Data Analysis Method, Limitation: Findings- Results and interpretation: Conclusions- Summary and conclusion, Recommendation/ Policy implications: Appendixes, References/ Bibliography, Draft Report and Finalization of report.