Short Title:Market Research: Quantitative Methods
Full Title:Market Research: Quantitative Methods
Module Code:DMKT H3014
 
ECTS credits: 5
NFQ Level:7
Module Delivered in 2 programme(s)
Module Contributor:Colm McGuinness
Module Description:This module will develop the student’s skills and abilities for quantitative business research, statistical work, data mining, and analytical problem solving. It builds upon the Marketing Statistics module, and prepares the ground for further modules in later semesters.
Learning Outcomes:
On successful completion of this module the learner will be able to
  1. Determine an appropriate research design, including the development of a suitable questionnaire, to address a formulated hypothesis for a statistical problem derived from a business context.
  2. Collect, prepare and code data for data analysis using a software package.
  3. Carry out a detailed descriptive analysis of univariate, bi-variate and multivariate data, including the use of correlation.
  4. Select and carry out a range of inferential tests for nominal, ordinal and interval variables.
  5. Apply multiple regression techniques and fully explain and justify their power and limitations from their foundational theory.
  6. Discuss and explain the assumptions that these statistical techniques rely on and their resulting limitations.
 

Module Content & Assessment

Indicative Content
Survey Data
Research designs. Observational and Experimental studies. Pitfalls of designs. Ethics. Developing indicators for concepts. Validity. Reliability. Sampling techniques. The construction and administration of Questionnaires. Data coding and preparation for analysis. Factor analysis and scale creation.
Descriptive Statistics
Review of descriptive statistics for nominal, ordinal and interval variables.
Inferential Statistics
Review of hypothesis testing; the meaning and interpretations of Statistical significance, Type I and II errors and an overview of the concept of statistical Power. Calculation and interpretation of correlation coefficients for nominal, ordinal, interval and mixed variables. Sampling distributions and Inferential statistics for correlation coefficients. The calculation and importance of statistical and practical effect size estimates. Confidence intervals for correlation coefficients. The definition and interpretation of Cronbach’s alpha. The Central limit theorem and its importance for statistical testing. The properties, uses and assumptions of T tests: Single, Paired, Unpaired. Reporting the results of T-tests. Multiple comparison and familywise error rates. Effect sizes.
ANOVA
Analysis of Variance (ANOVA): its assumptions and techniques for assumption checking, execution and reporting. Post-hoc testing. Least significant differences. Review of experimental designs: Full and partial factorial designs and effect estimation, Main effects and interaction effects. Main effects and interaction plots.
Linear Regression
Linear and multiple regression: Assumptions and assumption checking, execution and reporting. Stepwise regression in exploratory analysis. The problems of collinearity. An overview of Principal components analysis and its applications. Linearization for non-linear variables. R2 and R2adj. Confidence and prediction intervals. The use of dummy/indicator variables. Tests on regression coefficients, and confidence intervals for regression coefficients.
Non-parametric Statistics
Inferential statistics for nominal and ordinal data: use of the Chi-square distribution in tests for independence. Confidence intervals for a proportion. Non-parametric testing: Single, Paired, Unpaired tests of medians.
Indicative Assessment Breakdown%
Course Work Assessment %50.00%
Final Exam Assessment %50.00%
Course Work Assessment %
Assessment Type Assessment Description Outcome addressed % of total Assessment Date
Practical/Skills Evaluation Project (Integrated across subjects if possible). 1,2,3,4,5,6 30.00 Week 11
Open-book Examination Weekly exercises 1,2,3,4,5,6 20.00 Every Week
Final Exam Assessment %
Assessment Type Assessment Description Outcome addressed % of total Assessment Date
Formal Exam Final Exam 1,3,4,5,6 50.00 End-of-Semester

ITB reserves the right to alter the nature and timings of assessment

 

Indicative Module Workload & Resources

Indicative Workload: Full Time
Frequency Indicative Average Weekly Learner Workload
Every Week 2.00
Every Week 2.00
Every Week 4.00
Resources
Recommended Book Resources
  • David de Vaus., Surveys in social research, 6th Ed. Ed., New York; Routledge [ISBN: 0415530180]
  • McClave, J. T., Benson, P. G., Sincich, T. L. 2013, Statistics for Business and Economics, 12th Ed. Ed., Pearson [ISBN: 1292023295]
Supplementary Book Resources
  • Alan Buckingham and Peter Saunders 2004, The survey methods workbook, Polity Oxford [ISBN: 0745622453]
  • Ajai S. Gaur, Sanjaya S. Gaur, Statistical Methods for Practice and Research: A Guide to Data Analysis Using SPSS, Sage Publications Pvt. Ltd [ISBN: 8132101006]
  • Frederick L. Coolidge, Statistics, Sage Publications, Inc [ISBN: 1412991714]
  • Reinhart, A 2015, Statistics Done Wrong: The Woefully Complete Guide, No Starch Press [ISBN: 1593276206]
  • W. Michael Kelley, Robert A. Donnelly, The Humongous Book of Statistics Problems: Translated for People Who Don't Speak Math, Alpha [ISBN: 1592578659]
This module does not have any article/paper resources
This module does not have any other resources

Module Delivered in

Programme Code Programme Semester Delivery
BN_BDMKT_8 Bachelor of Arts (Honours) in Digital Marketing 6 Mandatory
BN_BDMKT_7 Bachelor of Arts in Digital Marketing 6 Mandatory