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Course Info

  • QUANTITATIVE RESEARCH METHODS ANALYSIS

QUANTITATIVE RESEARCH METHODS ANALYSIS

About this Course

Quantitative Research Method Analysis course aims to equip students with statistical tools needed in their academic research. This course will teach students to use both SPSS statistical software and Smart PLS software. The only prerequisite in this course is basic mathematics knowledge and determination to learn. We believe students need to know how to use the statistical tools and, more importantly, to know the purpose of each statistical tool. Both the know-how and know why will enable students to apply the suitable statistical tools in their research. We divide this course into two parts. This first part will cover the basic descriptive and inferential statistics covering data preparation, preliminary data analysis, explore relationships between variables and compare groups. The second part will introduce structural equation modelling (SEM) analysis, a popular statistical tool in business management research. At the end of this course, students should be able to: - 1. Organise data preparation process that includes data entry, data screening and preliminary data analysis. 2. Determine the correct statistical tools in academic research 3. Integrate lifelong learning skills related to statistical tools and software in their academic research.

Course Syllabus

Syllabus Info
Data Preparation
1.1 Data preparation process - Coding and Data entry
1.2 Data Screening – Data editing, data transformation and missing value

Preliminary Data Analysis
2.1 Descriptive analysis: numerical and graphical methods.
2.2 Preliminary data analysis: reliability scale and choosing the right statistical methods.

Explore Relationship Between Variables Part 1
3.1 Correlation
3.2 Partial Correlation
3.3 Multiple Regression
3.4 Logistic Regression

Explore Relationship Between Variables Part 2
4.1 Factor Analysis

Compare Groups - Between Quantitative Data and Quantitative Data (Parametric)
5.1 T-test - Independence equal variance and Independence unequal variance
5.2 T-test - dependence
5.3 Analysis of Variance - ANOVA

Compare Groups - Non-parametric Statistics
6.1 Chi-square test for goodness of fit
6.2 Chi-square test for independence
6.3 McNemar's Test
6.4 Cochran's Q Test
6.5 Kappa Measure of Agreement
6.6 Mann-Whitney U Test
6.7 Wilcoxon Signed Rank Test
6.8 Kruskal-Wallis Test
6.9 Friedman Test

Multivariate Analysis - Structural Equation Modelling - Part 1
7.1 Introduction to SEM
7.2 Path Model
7.3 Path Model Estimation

Multivariate Analysis - Structural Equation Modelling - Part 2
8.1 Assessing Reflective Measurement Models
8.2 Assessing Formative Measurement Models
8.3 Assessing Structural Model
8.4 Mediator Analysis
8.5 Moderation Analysis

Frequently Asked Questions

Course FAQ
Q1 : What can I learn from this course?
A1 : You will learn two things from this course. This first is how to carry out the basic descriptive and inferential statistics covering data preparation, preliminary data analysis, explore relationships between variables and compare groups. The second is to use structural equation modelling (SEM) analysis, a popular statistical tool in business management research.

Q2 : Do I need to purchase and to install any statistical software?
A2 : Yes, you need to install SPPS software and SMART-PLS software. We will give you instructions on how to install the software in the course.

Q3 : I am not very good with numbers and calculation, will I be able to follow this course?
A3 : Absolutely yes, as this course required only a basic knowledge of mathematics but a tremendous amount of commitment and perspiration to learn.