A Minimal Book Example
Preface
Course schedule
1
Introduction
1.1
Welcome to Market Research!
1.2
Course Objectives
1.3
Software
1.4
To do list
1.4.1
Form groups (2-3 students per group)
1.4.2
Install Excel, R & Rstudio on your own laptop/PC
1.4.3
Syllabus Quiz (non-graded/Individual work)
1.4.4
Post your introduction on Canvas (non-graded/Individual work)
1.4.5
Use Hypothesis.is for social annotations and discussions - Basic Marketing Research -Chapter 2 (Individual work)
1.4.6
Install R & RStudio before the end of Week 2
2
Research Design
2.1
Check list for Week 2 (due by 9/04/2020)
2.2
Introduction
2.3
Research Objectives & Limitations
2.4
A coffee owner’s marketing research problem
2.4.1
In-class discussion questions
2.5
Analyzing the relationship between advertising and sales
3
Secondary Research (due by 9.11)
3.1
Checklist for Week 3
3.2
Overview
3.3
Sources of Secondary Data
3.4
Perform Secondary Data Research
3.5
Annotations & Discussion questions
4
t-test & ANOVA
4.1
Warm-up activity for fun - can you replace my name with yours using the following functions?
4.1.1
If you are a first-time R user, please follow the following tip to set up your working directory:
4.1.2
Research design - Review our Research Design tutorial
4.2
Introduction
4.2.1
Research design issues
4.2.2
Variable Description
4.2.3
Step 1:
4.2.4
Step 2:
4.2.5
Step 3: Perform a t-test using Excel or R
4.2.6
Step 3.1 Perform a t-test using Excel
4.2.7
Step 3.2 (Preparation & debugging)
4.2.8
Step 4: Wrap-up - interpret the results
4.2.9
Descriptive Analysis 1:
4.2.10
Descriptive Analysis 2:
4.2.11
Descriptive analysis 3 - Compare the mean of sales with the two different ad types
4.3
Assumption check 1
4.3.1
Let’s build a more elegant boxplot with ggplot (the most elegant and aesthetically pleasing graphics framework available)
4.3.2
First we convert the variable ad_type from a numeric to a factor variable
4.4
Assumption check 2
4.5
t-test
4.5.1
Google & StackOverflow are definitely the top go-to choices for developers and programmers at any level
4.5.2
Reference
5
Basic regression analysis
5.1
What is a regression analysis?
5.2
Example Regression equation:
5.3
Real world examples
5.4
Introduction
5.4.1
Pre-Processing
5.5
Read the data - alternative solution
5.6
Data cleanup and exploratory analysis
5.7
Exploratory analysis (explained)
5.8
Attendance by Day Of Week/month
5.9
Evaluate Attendance by Weather
5.10
Strip Plot of Attendance by opponent or visiting team
5.11
Reference
6
Sampling/Experimental Design
7
Survey Development
8
Bivariate Data Analysis
9
Cluster analysis
10
Multidimensional Scaling/Advanced methods
11
Advanced methods
12
Advanced methods
13
Advanced methods
14
Advanced methods
References
Published with bookdown
An Outline of the Overall Course Structure for MKTG4000
Chapter 10
Multidimensional Scaling/Advanced methods