CCRP Ultimate Trivia Quiz For Researchers!

Explanation
General blinding is not a type of blinding. The commonly known types of blinding in research studies are single blinding and double blinding. Single blinding refers to when either the participants or the researchers are unaware of the treatment being administered. Double blinding involves both the participants and the researchers being unaware of the treatment assignment. Tertiary blinding, on the other hand, is not a recognized type of blinding in research studies. Therefore, the correct answer is General blinding.

Explanation
A hypothesis is known as an educated guess in clinical research. It is a statement that is proposed based on existing knowledge and observations, and it serves as a starting point for further investigation. A hypothesis is testable and can be supported or rejected through experimentation and data analysis.

Explanation
A working hypothesis is a hypothesis proposed for further research. It is an initial assumption or proposition that is used as a basis for further investigation and experimentation. It is subject to testing and refinement as more evidence is gathered. Unlike a true hypothesis, which is already supported by evidence, a working hypothesis is a starting point that is used to guide the research process and generate new knowledge.

Explanation
Fruitfulness refers to the potential of a research hypothesis to explain further phenomena in the future. A fruitful hypothesis is one that can generate new insights, discoveries, or explanations beyond the initial research question. It suggests that the hypothesis has the capacity to lead to further advancements in knowledge and understanding within the field of study.

Explanation
The degree of fit of an hypothesis with the existing knowledge is called conservatism. This refers to the extent to which the hypothesis aligns with the established beliefs, theories, or principles in a particular field or domain. A conservative hypothesis is one that is in line with the existing knowledge and does not introduce radical or revolutionary ideas. It builds upon and extends the current understanding, rather than challenging or contradicting it.

Explanation
The average of a clinical research data is called the mean. The mean is calculated by adding up all the values in the data set and dividing the sum by the total number of values. It provides a measure of the central tendency of the data and is commonly used to summarize and compare different groups or treatments in clinical research.

Explanation
The observation that occurs most frequently in a clinical research is called the mode. The mode represents the value or category that appears the most frequently in a dataset. In the context of clinical research, this could refer to the most common symptom, treatment, or outcome observed among the participants. The mode is a useful measure of central tendency that helps identify the most prevalent observation in a study.

Explanation
The allocation of research hypothesis to cases is called "scope." Scope refers to the range or extent of the research hypothesis and how it applies to different cases or situations. It involves determining the boundaries and limitations of the hypothesis and identifying the specific cases or contexts to which it is applicable. This helps researchers define the focus and objectives of their study and ensures that their hypothesis is relevant and applicable to the specific cases they are investigating.

Explanation
Accuracy is the statistical term that is irrelevant in clinical research. Accuracy refers to how close a measured value is to the true value. In clinical research, the focus is more on the precision and validity of the data rather than the accuracy. Accuracy is more commonly used in fields such as engineering or physics where exact measurements are crucial. In clinical research, other statistical terms like mean, mode, and confidence interval are more relevant for analyzing and interpreting data.

Explanation
Standard deviation is a measure of the dispersion or spread of a set of data values. It quantifies the amount of variation or deviation from the mean. Therefore, it is a statistical deviation. Analysis of variance, T Test, and F Test are all statistical techniques used to analyze and compare data sets, making them statistical deviations.