Contents
Unit 1 – What is empirical research?.......................................................................2
Unit 2 – What are clear research questions?...........................................................5
Unit 3 – What are data?.......................................................................................... 6
Unit 4 – Handling data with software – R................................................................8
Unit 5 – Conceptualizing constructs......................................................................12
Unit 6 – Operationalization and data collection....................................................14
Unit 7 – Measuring constructs using content analysis..........................................15
Unit 8 – Two aspects of data quality.....................................................................18
Unit 9 – Displaying univariate data in R................................................................20
Unit 10 – Summarizing ratio variables..................................................................23
Unit 11 – Distributions and Z-scores in R..............................................................25
Unit 12 – Causality and bivariate causal hypotheses............................................29
Unit 13 – Visualizing and analysing bivariate relationship in R.............................32
Unit 14 – Causality and the effect of thrd variables..............................................36
Unit 15 – Research designs for testing causal hypotheses...................................39
Unit 16 – Elaboration analysing multi-variate relationships using tables..............43
Unit 17 - Elaboration analysing multi-variate relationships using tables..............46
Unit 18 – Visualizing multivariate relationships using R.......................................49
Unit 19 – Sampling............................................................................................... 52
Unit 20 – First steps towards inference certainty about means............................55
Unit 22 – Research ethics..................................................................................... 57
Unit 23 – Normal distribution................................................................................ 60
Unit 24 – Describing the association between two variables................................62
Unit 26 – Data collection methods and measurement..........................................65
1
,Unit 1 – What is empirical research?
Learning objectives; after this unit, you will be able to:
1. explain what is meant with empirical research and which steps can be taken
according to the wheel of science;
Empirical research involves collecting and analysing data from observations or
experiments to gain knowledge about a specific topic. It is based on measurable
evidence rather than theories or beliefs. The wheel of science is a model
describing the iterative process of scientific research, consisting of steps like
observation, forming hypotheses, testing these hypotheses through experiments,
and then developing theories. These theories lead to new observations,
continuing the cycle.
The Wheel of Science is a conceptual model that illustrates the cyclical nature
of scientific research. It emphasizes the iterative process through which scientific
knowledge is generated, tested, and refined. The model typically includes the
following key steps, though these can vary slightly depending on the source:
Observation: The process begins with observing a phenomenon or identifying a
research question that needs exploration. Observations might be derived from
the natural world, previous studies, or specific areas of interest.
Hypothesis: Based on initial observations, scientists propose a hypothesis or a
tentative explanation for the phenomenon being studied. The hypothesis should
be testable through empirical research.
Experimentation/Testing: Scientists then design experiments or gather data to
test the hypothesis. This step involves collecting evidence through controlled
experiments, surveys, or observations, often using a systematic and methodical
approach.
Analysis: The collected data is analyzed to determine whether it supports or
refutes the hypothesis. Statistical methods, models, or qualitative analysis may
be used depending on the nature of the data.
Conclusion/Interpretation: Based on the analysis, scientists draw conclusions
about the validity of the hypothesis. If the hypothesis is supported, it may be
refined or further developed. If it is not supported, the hypothesis may be revised
or rejected.
Theory Development: Over time, as more data is collected and tested,
hypotheses can contribute to the formation of broader scientific theories or
principles. A theory is a well-substantiated explanation of an aspect of the natural
world that can be repeatedly tested and confirmed.
New Questions: The conclusions and theories generated through the research
process often lead to new questions or areas of investigation. These questions
may prompt further observation, restarting the cycle.
This cyclical process is depicted as a "wheel" because science is a dynamic,
continuous process, where new findings lead to new questions, perpetuating
2
,ongoing discovery and refinement of knowledge. Each cycle of the wheel builds
upon previous research, leading to deeper understanding.
2. differentiate between induction and deduction;
Induction is reasoning from specific observations to broader generalizations. For
example, observing that the sun rises every morning and concluding that the sun
always rises is an inductive process.
Deduction, on the other hand, is reasoning from general principles to specific
conclusions. For example, starting with the theory that all birds have wings and
deducing that a sparrow, being a bird, must also have wings.
3. recognize and explain the steps that can be taken in the decision making
process;
The decision-making process is a structured approach to solving problems or
choosing the best course of action. The main steps include:
1. Identifying the problem or decision to be made
2. Gathering relevant information
3. Generating alternatives or possible solutions
4. Evaluating the options
5. Choosing the best solution
6. Implementing the decision
7. Reviewing the decision and its consequences
4. explain the relationship between systematic decision making and
systematically answering empirical questions;
Systematic decision-making involves a structured and logical process to
evaluate options and make choices, while systematically answering empirical
questions means using a structured research process to find evidence-based
answers to specific questions. Both processes rely on a clear framework to
minimize biases and ensure that conclusions or decisions are grounded in reliable
evidence and logical reasoning.
5. formulate a relevant research question in the context of a specific phase in a
decision making process;
A relevant research question is a clear and focused inquiry that aligns with
the specific needs of a phase in the decision-making process. For example, during
the "gathering information" phase, a relevant research question might be, "What
are the main factors influencing customer satisfaction in this market?" The
formulation of such questions guides the research to provide actionable insights
for decision-making.
6. recognize and mention examples of confirmation bias;
Confirmation bias is the tendency to focus on information that supports one's
existing beliefs or hypotheses while ignoring or undervaluing evidence that
3
, contradicts them.
Examples:
Only reading news articles that align with one’s political beliefs.
Ignoring negative feedback about a favored product and emphasizing
positive reviews.
Interpreting ambiguous evidence as supportive of one's preconceived
notions.
7. explain how systematic empirical research helps avoiding the confirmation
bias.
Systematic empirical research reduces confirmation bias by requiring
researchers to follow a structured methodology that prioritizes objectivity. This
includes:
Collecting data from multiple, unbiased sources.
Using standardized methods to gather and analyze data.
Testing hypotheses against evidence rather than assumptions.
Peer review and replication of findings to ensure conclusions are not based
solely on selective interpretations.
By adhering to these practices, empirical research ensures findings are
more reliable and less influenced by personal biases.
4
Unit 1 – What is empirical research?.......................................................................2
Unit 2 – What are clear research questions?...........................................................5
Unit 3 – What are data?.......................................................................................... 6
Unit 4 – Handling data with software – R................................................................8
Unit 5 – Conceptualizing constructs......................................................................12
Unit 6 – Operationalization and data collection....................................................14
Unit 7 – Measuring constructs using content analysis..........................................15
Unit 8 – Two aspects of data quality.....................................................................18
Unit 9 – Displaying univariate data in R................................................................20
Unit 10 – Summarizing ratio variables..................................................................23
Unit 11 – Distributions and Z-scores in R..............................................................25
Unit 12 – Causality and bivariate causal hypotheses............................................29
Unit 13 – Visualizing and analysing bivariate relationship in R.............................32
Unit 14 – Causality and the effect of thrd variables..............................................36
Unit 15 – Research designs for testing causal hypotheses...................................39
Unit 16 – Elaboration analysing multi-variate relationships using tables..............43
Unit 17 - Elaboration analysing multi-variate relationships using tables..............46
Unit 18 – Visualizing multivariate relationships using R.......................................49
Unit 19 – Sampling............................................................................................... 52
Unit 20 – First steps towards inference certainty about means............................55
Unit 22 – Research ethics..................................................................................... 57
Unit 23 – Normal distribution................................................................................ 60
Unit 24 – Describing the association between two variables................................62
Unit 26 – Data collection methods and measurement..........................................65
1
,Unit 1 – What is empirical research?
Learning objectives; after this unit, you will be able to:
1. explain what is meant with empirical research and which steps can be taken
according to the wheel of science;
Empirical research involves collecting and analysing data from observations or
experiments to gain knowledge about a specific topic. It is based on measurable
evidence rather than theories or beliefs. The wheel of science is a model
describing the iterative process of scientific research, consisting of steps like
observation, forming hypotheses, testing these hypotheses through experiments,
and then developing theories. These theories lead to new observations,
continuing the cycle.
The Wheel of Science is a conceptual model that illustrates the cyclical nature
of scientific research. It emphasizes the iterative process through which scientific
knowledge is generated, tested, and refined. The model typically includes the
following key steps, though these can vary slightly depending on the source:
Observation: The process begins with observing a phenomenon or identifying a
research question that needs exploration. Observations might be derived from
the natural world, previous studies, or specific areas of interest.
Hypothesis: Based on initial observations, scientists propose a hypothesis or a
tentative explanation for the phenomenon being studied. The hypothesis should
be testable through empirical research.
Experimentation/Testing: Scientists then design experiments or gather data to
test the hypothesis. This step involves collecting evidence through controlled
experiments, surveys, or observations, often using a systematic and methodical
approach.
Analysis: The collected data is analyzed to determine whether it supports or
refutes the hypothesis. Statistical methods, models, or qualitative analysis may
be used depending on the nature of the data.
Conclusion/Interpretation: Based on the analysis, scientists draw conclusions
about the validity of the hypothesis. If the hypothesis is supported, it may be
refined or further developed. If it is not supported, the hypothesis may be revised
or rejected.
Theory Development: Over time, as more data is collected and tested,
hypotheses can contribute to the formation of broader scientific theories or
principles. A theory is a well-substantiated explanation of an aspect of the natural
world that can be repeatedly tested and confirmed.
New Questions: The conclusions and theories generated through the research
process often lead to new questions or areas of investigation. These questions
may prompt further observation, restarting the cycle.
This cyclical process is depicted as a "wheel" because science is a dynamic,
continuous process, where new findings lead to new questions, perpetuating
2
,ongoing discovery and refinement of knowledge. Each cycle of the wheel builds
upon previous research, leading to deeper understanding.
2. differentiate between induction and deduction;
Induction is reasoning from specific observations to broader generalizations. For
example, observing that the sun rises every morning and concluding that the sun
always rises is an inductive process.
Deduction, on the other hand, is reasoning from general principles to specific
conclusions. For example, starting with the theory that all birds have wings and
deducing that a sparrow, being a bird, must also have wings.
3. recognize and explain the steps that can be taken in the decision making
process;
The decision-making process is a structured approach to solving problems or
choosing the best course of action. The main steps include:
1. Identifying the problem or decision to be made
2. Gathering relevant information
3. Generating alternatives or possible solutions
4. Evaluating the options
5. Choosing the best solution
6. Implementing the decision
7. Reviewing the decision and its consequences
4. explain the relationship between systematic decision making and
systematically answering empirical questions;
Systematic decision-making involves a structured and logical process to
evaluate options and make choices, while systematically answering empirical
questions means using a structured research process to find evidence-based
answers to specific questions. Both processes rely on a clear framework to
minimize biases and ensure that conclusions or decisions are grounded in reliable
evidence and logical reasoning.
5. formulate a relevant research question in the context of a specific phase in a
decision making process;
A relevant research question is a clear and focused inquiry that aligns with
the specific needs of a phase in the decision-making process. For example, during
the "gathering information" phase, a relevant research question might be, "What
are the main factors influencing customer satisfaction in this market?" The
formulation of such questions guides the research to provide actionable insights
for decision-making.
6. recognize and mention examples of confirmation bias;
Confirmation bias is the tendency to focus on information that supports one's
existing beliefs or hypotheses while ignoring or undervaluing evidence that
3
, contradicts them.
Examples:
Only reading news articles that align with one’s political beliefs.
Ignoring negative feedback about a favored product and emphasizing
positive reviews.
Interpreting ambiguous evidence as supportive of one's preconceived
notions.
7. explain how systematic empirical research helps avoiding the confirmation
bias.
Systematic empirical research reduces confirmation bias by requiring
researchers to follow a structured methodology that prioritizes objectivity. This
includes:
Collecting data from multiple, unbiased sources.
Using standardized methods to gather and analyze data.
Testing hypotheses against evidence rather than assumptions.
Peer review and replication of findings to ensure conclusions are not based
solely on selective interpretations.
By adhering to these practices, empirical research ensures findings are
more reliable and less influenced by personal biases.
4
