Summary of the research design: Explain whether it's a cross-sectional, longitudinal, experimental, or observational study

Ciccarelli: Psychology_5 (5th Edition)
5th Edition
ISBN:9780134477961
Author:Saundra K. Ciccarelli, J. Noland White
Publisher:Saundra K. Ciccarelli, J. Noland White
Chapter1: The Science Of Psychology
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The purpose of this study is to contribute to a better understanding of workplace dynamics and develop strategies for creating more inclusive and respectful work environments. Methodology: Qualitative interviews to collect data from a diverse sample of employees across various industries. Main Hypothesis:

There is a significant relationship between age and workplace bullying, with age serving as a predictor of the occurrence and experiences of bullying.

 

Please follow the Outline for the Methods Section of Quantitative Research Proposal of the study above: specific sec5ons may vary depending on the nature of the study, the field of research, and any guidelines or requirements specified by journals or institutions:

  1. Introduction to Methods

Brief overview of the research question or problem. Summary of the research design: Explain whether it's a cross-sectional, longitudinal, experimental, or observational study.

  1. Participants

Sample size, Justification for sample size, Power analysis, if applicable Sampling method, Randomized or non-randomized Stratification factors, if any Demographics, Age range, Gender distribution, Other relevant demographic details Inclusion and exclusion criteria Ethical considerations, Informed consent, IRB approval, Anonymity and confidentiality

  1. Materials

Instruments used, Surveys or questionnaires, Software, Equipment, Validation and reliability Information, For pre-existing  instruments, For instruments developed for this study

  1. Procedures

Pre-study procedures, Pilot testing, if applicable Recruitment process

Allocation to groups, if applicable, Data collection methods Surveys, Observations, Tests, Timeframe, Follow-up, if applicable Data management Data storage. Data quality checks

  1. Experimental Design (if applicable)

Control group Intervention group Blinding, if applicable Randomization method Variables, Independent variables Dependent variables Confounding variables

  1. Data Analysis

Descriptive statistics, Inferential statistics, Tests used (e.g., t-tests, ANOVA, regression) Jus5fica5on for the tests above, Software used to analyze the data Treatment of missing data

  1. Quality Control

Internal validity measures, External validity measures

  1. Ethical Considerations in Data Analysis

Data integrity, Multiple comparisons problem, if applicable Transparency and replicability

  1. Limitations

Methodological limitations, Sample limitations

 

 

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