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 9
Cluster analysis