Scientific research, research, data analysis, HRM Human Resource Management, explanatory research, scientific method, industrial psychology, evaluation research, non-experimental designs, experimental designs, quasi-experimental designs, laboratory studies, quantitative research, qualitative research, observation, interviews, case study, tests, rating scales, questionnaires, psychological measures, mediator, moderator
This document is the summary of a course that presents the different ways in which research can be conducted in Science, as well as the method of data analysis.
Science is a more formal, rigorous approach in the quest for truthful knowledge. It relies on objectivity and rationality
- Objectivity: refer to the methods and procedures we use to gather "evidence" in support of claims.
- Rationality: refers to judgments we make concerning the validity of claims. The focus is on the interpretation of the evidence and conclusions drawn.
[...] Scientific Research and Data Analysis Research What is science? Goals = understand, predict, and control some phenomenon The science method: Science is a more formal, rigorous approach in the quest for truthful knowledge - Relies on objectivity and rationality Objectivity: refer to the methods and procedures we use to gather "evidence" in support of claims. Rationality: refers to judgments we make concerning the validity of claims. The focus is on the interpretation of the evidence and conclusions drawn. Steps in the scientific method: Research ideas: we observe the world around us. [...]
[...] One way to ensure objectivity in research is to design the research in such a way that all other possible explanations, other than the one being tested, is eliminated. A series of decisions need to be made before the research actually begins Research design is determined by answering the following questions: Will research be conducted in a laboratory under controlled conditions, or in the field? Who will the participants be? If there are different conditions in the research (e.g. some participants exposed to the condition and others not), how will participants be assigned to the various conditions? What will the variables of interest be? [...]
[...] Correlation coefficient: the measure of association most commonly used. Statistics assessing the bivariate, linear association between 2 variables. Provides information about both the magnitude (numerical value) and the direction of the relationship between two variables. Moderators: Moderators are factors that affect the relationship between variables, representing conditions under which associations are either stronger or weaker Mediators: A mediator is a factor that explains or accounts [partly or predominantly] for the relationship between variables (i.e. x is related to y because of mediating factor z). [...]
[...] Three types of designs: 1. Experimental: - Participants are randomly assigned to different conditions - Any differences that appear after experimental treatment are to conform to cause-effect relationships. - Not always possible to assign participants randomly to a condition 2. Quasi-experimental: - Participants are assigned to different conditions, but random assignment to conditions is not possible 3. Non-experimental designs: - Researcher gathers information without introducing any condition or treatment - "Independent variable" to describe the treatment or antecedent condition - "Dependent variable" to describe the subsequent behaviour of the research participant - 2 common non-experimental designs: Observational design: the researcher observes employee behaviour and systematically records what is observed Survey design: research strategy in which participants are asked to complete a questionnaire or survey. [...]
[...] Qualitative research methods: Rely on observation, interviews, case study, and analysis of diaries or written documents. Data Analysis Appropriate and accurate data analysis is critical in order to come to credible conclusions. When done badly, data analysis can be confusing, or worse misleading. Descriptive statistics: Summarise, organise, and describe a sample of data 1. Measures of central tendency: indicates where the centre of a distribution is located Mean: average Median: middle Mode: occurs the most 2. Variability The extent to which scores in a distribution vary Standard deviation: deviation from a mean score Variance: squared standard deviation 3. [...]
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