ERP Lecture 1

17 flashcards · Other · by Daniel F.

1. Empirical research method

   Research question: Observe the world, think, read the literature theory/literature: Motivate the research (convince the reader), describe the research gap and state the contribution Hypothesis/prediction: Variables Data & Methodology: data collection and measurement Analysis of Data: Graphical & descriptive, modelling

2. Research question / objective

   What do you want to study and understand? practically relevant theoretically relevant fill research gap interesting

3. Testing hypotheses

   Testing the testable predictions Predictions Identify and define variables Dependent variable (the variable that is being affected) Independent variable(s) (variable(s) that affect/predict the dependent variable Collect data Measurement Analyze data Graphically & Descriptively fit a model conclude, discuss

4. Validity and types

   Do I measure what I want to measure? Internal validity - The extent to which a study establishes a causal relationship between variables without being influenced by confounding factors ensures that the observed effect is truly due to the independent variable and not other factors or variables External validity - The extent to which the results of a study can be generalized to other contexts, populations, or settings ensures that the findings are applicable beyond the specific conditions of the…

5. Factors of a good study

   Validity, Generalizability, Reliability

6. Generalizability

   Are findings from a sample or study applicable to the broader population? Sample has to be representative.

7. a good sample is

   Relevant Complete Precise Up to date has no selection bias

8. Selection Bias

   Sample is not random, and may not be representative of the population Careful about the interpretation of your results and the conclusions you draw

9. Reliability

   Consistency of a measurement A reliable measure produces the same results under consistent conditions A measure can be reliable but consistently wrong, leading to inaccurate results (systematic errors)

10. Ways to organize data

    Cross-sectional: Many subjects at a given point in time Time series: Same single subject over a certain period of time Panel (longitudinal): Multiple subjects, different observations for these subjects over a period of time

11. Types of data sources

    Primary : Collected by researcher Secondary: Collected by other agencies

12. Endogeneity

    regressor is correlated to error term Omitted Variables: When a relevant variable is not included in the model, it may be absorbed into the error term Measurement Error: If an explanatory variable is measured with error, it can create a correlation between the variable and the error term Simultaneity: When there is a bidirectional causal relationship between the dependent and independent variables Sample Selection Bias: Selection bias occurs when study samples systematically differ from target…

13. Data types / levels of measurement

    categorical variables Nominal genders; colors; marital status nationality binary: yes/no no order no equal/defined distance conduct analysis using dummy variables Ordinal 1st, 2nd and 3rd prize, product quality rating, How satisfied you are with this lecture? Logical order no equal distance Quantitative Variables Interval (scale) Information about differences between points on a scale, Celsius scalre ordered equal distance no absolute 0 Ratio weight, height, number of people, money earned, dist…

14. Dummy Variable Trap

    there should be always n-1 dummy variables

15. Likert scale

    Scale 1-7, ordinal

16. Primary vs secondary data

    Primary data (surveys): Allows customized questions specific to research objectives Captures current perceptions directly from stakeholders Provides control over what is measured Drawbacks: time-consuming, potentially low response rates, sampling bias Secondary data (online datasets): More cost-effective and time-efficient Often larger sample sizes with established methodologies Allows for comparisons across companies Drawbacks: may not perfectly align with research questions, less control over…

17. levels of analysis

    scales at which social phenomena can be examined. micro-level, focusing on individual interactions and agency e.g. person family household neighborhood meso-level, examining groups, organizations, and communities e.g. Tribe, Community, Village, town, city, state macro-level, analyzing broader societal structures, institutions, and global systems. e.g. Nation, Society, Civilization, International, Global,