The features of Statistical Statement are that
it gives the definite information and
gives the data of specific period.

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Features of a Statistical Statement:

A statistical statement is a claim or assertion about a population or a sample based on data analysis. It provides information about a particular characteristic or relationship within a given population. Here are two key features of a statistical statement:

1. Quantitative Information:
A statistical statement provides quantitative information about a population or a sample. It presents numerical data that can be measured, counted, or compared. This quantitative information allows researchers and statisticians to analyze and interpret the data objectively. Some examples of quantitative information in statistical statements include means, medians, percentages, standard deviations, and correlation coefficients.

Quantitative information in a statistical statement is essential because it allows for precise comparisons and enables decision-making based on evidence. It helps in understanding the magnitude, direction, and significance of the results obtained from data analysis. Without quantitative information, statistical statements would lack the necessary precision and clarity required for making informed decisions.

2. Measure of Uncertainty:
Another crucial feature of a statistical statement is that it incorporates a measure of uncertainty. Statistical analysis acknowledges that any conclusion drawn from a sample may not perfectly represent the entire population. Therefore, statistical statements often include measures such as confidence intervals or p-values to quantify the level of uncertainty associated with the results.

Confidence intervals: These provide a range of values within which the true population parameter is likely to fall. For example, a 95% confidence interval for the mean height of a population might be stated as "The mean height is estimated to be between 165 cm and 170 cm with 95% confidence." This indicates that if the same study were repeated multiple times, 95% of the confidence intervals would capture the true population mean.

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Including a measure of uncertainty in statistical statements helps to convey the reliability and generalizability of the results. It acknowledges that there is always some degree of uncertainty associated with statistical inference and encourages researchers to consider the limitations and potential sources of error in their analyses.

In summary, a statistical statement provides quantitative information about a population or sample and incorporates measures of uncertainty to account for the variability and limitations of the data. These features allow researchers and decision-makers to make informed judgments based on evidence and to assess the reliability and significance of the statistical findings.