Marketing Research.

Format:

Book

Author/Creator:

Bajpai, Naval.

Naval Bajpai

Series:

Always learning.

Always learning

Language:

English

Subjects (All):

Marketing research--India.

Marketing research.

Marketing research--Methodology.

Physical Description:

1 online resource (657 pages)

Edition:

1st ed.

Place of Publication:

Noida : Pearson India, 2015.

Summary:

* The Research in Action feature links the concepts discussed in the chapter to actual industry practice* The case study at the end of each chapter acquaints learners with a variety of organizational scenarios that they may encounter in the future* Numerous examples and problems framed using real data from Indiastat.com and CMIE highlight the business applications of marketing research methods* Marginal definitions reinforce critical concepts and provide simple descriptions for complex theories* Modern statistical software programs explain multivariate statistical techniques using a step-by-step approach.

Contents:

Intro

Brief Contents

Contents

About the Author

Preface

I Introduction to Marketing Research

1 Marketing Research: An Introduction

1.1 Introduction

1.2 Difference Between Basic and Applied Research

1.3 Defining Marketing Research

1.4 Roadmap to Learn Marketing Research

1.5 Marketing Research: A Decision Making Tool in the Hands of Management

1.6 Use of Software in Data Preparation and Analysis

1.7 Ethical Issues in Marketing Research

Summary 19

Key Terms

Discussion Questions

Case Study

2 Marketing Research Process Design

2.1 Introduction

2.2 Marketing Research Process Design

Summary 41

II Research Design Formulation

3 Measurement and Scaling

3.1 Introduction

3.2 What Should be Measured?

3.3 Scales of Measurement

3.4 Four Levels of Data Measurement

3.5 The Criteria for Good Measurement

3.6 Measurement Scales

3.7 Factors in Selecting an Appropriate Measurement Scale

Summary

4 Questionnaire Design

4.1 Introduction

4.2 What is a Questionnaire?

4.3 Questionnaire Design Process

5 Sampling and Sampling Distributions

5.1 Introduction

5.2 Sampling

5.3 Why Is Sampling Essential?

5.4 The Sampling Design Process

5.5 Random Versus Non-Random Sampling

5.6 Random Sampling Methods

5.7 Non-Random Sampling

5.8 Sampling and Non-Sampling Errors

5.9 Sampling Distribution

5.10 Central Limit Theorem

5.11 Sample Distribution of Sample Proportion p

Numerical Problems

III Sources and Collection of Data

6 Secondary Data Sources

6.1 Introduction

6.2 Meaning of Primary and Secondary Data.

6.3 Benefits and Limitations of Using Secondary Data

6.4 Classification of Secondary Data Sources

6.5 Roadmap to Use Secondary Data

7 Data Collection: Survey and Observation

7.1 Introduction

7.2 Survey Method of Data Collection

7.3 A Classification of Survey Methods

7.4 Evaluation Criteria for Survey Methods

7.5 Observation Techniques

7.6 Classification of Observation Methods

7.7 Advantages of Observation Techniques

7.8 Limitations of Observation Techniques

8 Experimentation

8.1 Introduction

8.2 Defining Experiments

8.3 Some Basic Symbols and Notations in Conducting Experiments

8.4 Internal and External Validity in Experimentation

8.5 Threats to the Internal Validity of the Experiment

8.6 Threats to the External Validity of the Experiment

8.7 Ways to Control Extraneous Variables

8.8 Laboratory Versus Field Experiment

8.9 Experimental Designs and their Classification

8.10 Limitations of Experimentation

8.11 Test Marketing

9 Fieldwork and Data Preparation

9.1 Introduction

9.2 Fieldwork Process

9.3 Data Preparation

9.4 Data Preparation Process

9.5 Data Analysis

IV Descriptive Statistics and Data Analysis

10 Descriptive Statistics: Measures of Central Tendency

10.1 Introduction

10.2 Central Tendency

10.3 Measures of Central Tendency

10.4 Prerequisites for an Ideal Measure of Central Tendency

10.5 Mathematical Averages

10.6 Positional Averages

10.7 Partition Values: Quartiles, Deciles, and Percentiles

Case Study.

11 Descriptive Statistics: Measures of Dispersion

11.1 Introduction

11.2 Measures of Dispersion

11.3 Properties of a Good Measure of Dispersion

11.4 Methods of Measuring Dispersion

11.5 Empirical Rule

11.6 Empirical Relationship Between Measures of Dispersion

11.7 Chebyshev's Theorem

11.8 Measures of Shape

11.9 The Five-Number Summary

11.10 Box-and-Whisker Plots

11.11 Measures of Association

12 Statistical Inference: Hypothesis Testing for Single Populations

12.1 Introduction

12.2 Introduction to Hypothesis Testing

12.3 Hypothesis Testing Procedure

12.4 Two-Tailed and One-Tailed Tests of Hypothesis

12.5 Type I and Type II Errors

12.6 Hypothesis Testing for a Single Population Mean Using the z Statistic

12.7 Hypothesis Testing for a Single Population Mean Using the t Statistic (Case of a Small Random Sample When n < 30)

12.8 Hypothesis Testing for a Population Proportion

13 Statistical Inference: Hypothesis Testing for Two Populations

13.1 Introduction

13.2 Hypothesis Testing for the Difference Between Two Population Means Using the z Statistic

13.3 Hypothesis Testing for the Difference Between Two Population Means Using the t Statistic (Case of a Small Random Sample, n1, n2 < 30, When Population Standard Deviation is Unknown)

13.4 Statistical Inference About the Difference Between the Means of Two Related Populations (Matched Samples)

13.5 Hypothesis Testing for the Difference in Two Population Proportions

13.6 Hypothesis Testing About Two Population Variances (F Distribution)

14 Analysis of Variance and Experimental Designs

14.1 Introduction

14.2 Introduction to Experimental Designs

14.3 Analysis of Variance

14.4 Completely Randomized Design (One-Way ANOVA)

14.5 Randomized Block Design

14.6 Factorial Design (Two-Way ANOVA)

15 Hypothesis Testing for Categorical Data (Chi-Square Test)

15.1 Introduction

15.2 Defining x2-Test Statistic

15.3 x2 Goodness-of-Fit Test

15.4 x2 Test of Independence: Two-Way Contingency Analysis

15.5 x2 Test for Population Variance

15.6 x2 Test of Homogeneity

16 Correlation and Simple Linear Regression Analysis

16.1 Measures of Association

16.2 Introduction to Simple Linear Regression

16.3 Determining the Equation of a Regression Line

16.4 Using MS Excel for Simple Linear Regression

16.5 Using Minitab for Simple Linear Regression

16.6 Using SPSS for Simple Linear Regression

16.7 Measures of Variation

16.8 Statistical Inference About Slope, Correlation Coefficient of the Regression Model, and Testing the Overall Model

17 Multivariate Analysis I: Multiple Regression Analysis

17.1 Introduction

17.2 The Multiple Regression Model

17.3 Multiple Regression Model with Two Independent Variables

17.4 Determination of Coefficient of Multiple Determination (R2), Adjusted R2, and Standard Error of the Estimate

17.5 Statistical Significance Test for the Regression Model and the Coefficient of Regression

17.6 Indicator (Dummy Variable Model)

17.7 Collinearity

18 Multivariate Analysis lI: Discriminant Analysis and Conjoint Analysis

18.1 Discriminant Analysis

18.2 Conjoint Analysis

19 Multivariate Analysis III: Factor Analysis, Cluster Analysis, Multidimensional Scaling and Correspondence Analysis

19.1 Factor Analysis

19.2 Cluster Analysis

19.3 Multidimensional Scaling

19.4 Correspondence Analysis

20 Sales Forecasting

20.1 Introduction

20.2 Types of Forecasting Methods

20.3 Qualitative Methods of Forecasting

20.4 Time Series Analysis

20.5 Components of Time Series

20.6 Time Series Decomposition Models

20.7 The Measurement of Errors in Forecasting

20.8 Quantitative Methods of Forecasting

20.9 Freehand Method

20.10 Smoothing Techniques

20.11 Exponential Smoothing Method

20.12 Double Exponential Smoothing

20.13 Regression Trend Analysis

20.14 Seasonal Variation

20.15 Solving Problems Involving all Four Components of Time Series

20.16 Autocorrelation and Autoregression

V Result Presentation

21 Presentation of Result: Report Writing

21.1 Introduction

21.2 Organization of the Written Report

21.3 Tabular Presentation of Data

21.4 Graphical Presentation of Data

21.5 Oral Presentation

VI Applications of Marketing Research

22 Marketing Mix Research: Product, Price, Place and Promotion Research

22.1 Introduction

22.2 Marketing Mix: Meaning

22.3 New Product Research

22.4 Pricing Research

22.5 Distribution (Place) Research

22.6 Promotional Research

Appendix

Index.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

93-325-4467-0

OCLC:

922020097