
Терминологические словосочитание которые используют в научной речи


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Terminological Word Combinations Used in Scientific Discourse
In scientific discourse, there are several terminological word combinations that are commonly used. These combinations help to convey specific meanings and concepts within the scientific community. Here are some examples:
1. Hypothesis testing: This refers to the process of formulating and testing hypotheses in order to determine their validity or falsity. It involves collecting data, analyzing it, and drawing conclusions based on statistical evidence.
2. Experimental design: This refers to the plan or blueprint that outlines the steps and procedures for conducting an experiment. It includes details such as the selection of participants, the manipulation of variables, and the measurement of outcomes.
3. Statistical significance: This term is used to determine whether the results of a study are unlikely to have occurred by chance. It involves calculating the probability that the observed results are due to the variables being studied, rather than random variation.
4. Control group: This refers to a group of participants in an experiment who do not receive the experimental treatment or intervention. The control group is used as a baseline for comparison to determine the effects of the treatment.
5. Literature review: This is a critical analysis of existing research and scholarly articles on a specific topic. It involves identifying gaps in knowledge, summarizing key findings, and providing a context for the current study.
6. Methodology: This refers to the overall approach or strategy used to conduct research. It includes the selection of research methods, data collection techniques, and data analysis procedures.
7. Peer-reviewed: This term describes the process by which research articles are evaluated by experts in the field before they are published. Peer review ensures the quality and validity of the research.
8. Sample size: This refers to the number of participants or observations included in a study. A larger sample size generally increases the statistical power and generalizability of the findings.
9. Null hypothesis: This is a statement that assumes there is no relationship or difference between variables being studied. It is tested against an alternative hypothesis to determine if there is sufficient evidence to reject the null hypothesis.
10. Data analysis: This refers to the process of organizing, cleaning, and interpreting data to uncover patterns, relationships, and trends. It involves using statistical techniques and software to analyze the collected data.
These are just a few examples of the terminological word combinations commonly used in scientific discourse. The use of these terms helps to ensure clear communication and understanding within the scientific community.


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