This is a summary for the course 'Business Research II'. This summary contains all the material that has been covered during the hearing and lectures as well as the substance that has been covered in the chapters of the books.
Chapter 16 - Introductions and Conclusions.…………………………………………………………….p.47+p.48
Chapter 17 - Revising Style - Telling Your Story Clearly…………………………………………..…p.49+p.50
1
,Study guide
This part of the summary serves as a guide and a clear overview of what exactly has to learned for
the upcoming exam. Underneath are the learning objectives & assessment goals, and a personal
opinion on what would the best approach in studying for the course of ‘Business Research’.
Learning objectives & Assessment goals
As Business Research is technically 2 courses thrown into 1, the learning goals are in a way all over
the place. Underneath is a screenshot of what the module manual says.
Exam layout
’
Personal opinion
Learning goal 3 – 6 are based on statistics. Together this takes account for 60% of the exam. So the
main focus should be on understanding all equations and formulas, as well as the basics of
correlation and hypotheses testing. In an odd chain of event, there will also be questions about SPSS
(5% so that should be around 2 questions), so it is recommended to take some time to learn the
software. Don’t dwell too much on the book summaries of business research as the theory isn’t very
deep and practical. This should prepare you for the exam. Good luck!
2
, Statistics
Week 1 (Q3)
Scales of measurement
In business research we recognise 4 scales of measurement: nominal, ordinal, interval, and ratio. The
differences between these are shown below:
It is important to recognize that there is a hierarchy implied in the level of measurement idea. At
lower levels of Measurement, assumptions tend to be less restrictive an data analysis tend to be less
sensitive. At each level up the hierarchy, the current level includes all of the qualities of the one
below it and adds something new. In general, it is desirable to have a higher level of measurement
(e.g. interval or ratio) rather than a lower one (nominal or ordinal)
Descriptive statistics vs inferential statistics
Descriptive statistics: describing the characteristics of a set of data (entire population)
• mean, modus, median, standard deviation
• making tables and charts
Inferential statistics: using data of a smaller group to conclude something about the bigger group
• sample versus population
• estimating
• testing
3
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