Sure! Here are the definitions for each of the terms you requested:
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Statistics: Statistics is a branch of mathematics dealing with the collection, analysis, interpretation, presentation, and organization of data. It helps in making informed decisions based on numerical data and is used in various fields, including science, business, and social sciences. Statistics can be descriptive, summarizing data through measures such as mean, median, and mode, or inferential, allowing conclusions to be drawn about a population based on a sample.
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Population: In statistics, a population refers to the entire group of individuals or items that share a characteristic and are the subject of a statistical study. The population can be finite or infinite and can encompass people, animals, objects, or events. For instance, in a study analyzing the average height of adults in a city, the population would include all adults living in that city.
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Sample: A sample is a subset of a population selected for analysis. It is used in statistics to make inferences about the entire population without examining every individual or item. Samples can be randomly selected or derived through specific sampling methods, and they should ideally represent the population to minimize bias and allow for accurate conclusions.
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Outlier: An outlier is a data point that significantly differs from the other observations in a dataset. It is an unusually high or low value that can occur due to variability in the measurement or indicate that there is an error in the data collection process. Outliers can have a considerable effect on statistical analyses, potentially skewing results, and thus they may require special attention when interpreting data.
If you have any further questions or need more detailed explanations, feel free to ask!
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