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What does the score mean?
In statistics, there are only two forms of alternating symbols, and the ratio of the number of units with or without a symbol to the total number of units is called a number. Equivalent to percentage, 10% is 10%, not 1%, 35% is 35%, and 85% is 85%.

One number is the fraction of another number, generally referring to the ratio: standard labor should be found in the production group, compared with each other and evaluated as a number. Usually used in industrial and agricultural production, indicating the increase of output. A few percent is a few tenths.

For example, grain output increased by "20%". "20%" means two tenths, which means that the grain output has increased by 20%.

Extended data:

When calculating a number, there are two numbers, A and B. Find the ratio of B and A and turn the ratio into a pure decimal. Then the pure decimal is called the number from B to A. The first digit after the decimal point is called "Cheng" or "Minute", and the second digit after the decimal point is called "Li".

For example, if the planned grain output is 50,000 Jin and the actual grain output is 1 10,000 Jin, then the grain yield increase percentage is 1.275 = 0.2, that is, the grain yield is increased by 20%.

Reciprocal method of numbers and other numbers: fraction X 10 = decimal number/10 = decimal number (number divided by 10 equals decimal number) decimal number X 10 = percentage.

Related concepts are particularly worth discussing. Statistical analysis of data sets may show that two variables (two attributes in a matrix) tend to change together as if they are related.

For example, research journals on people's income and age of death may find that the average life expectancy of the poor is often shorter than that of the rich. These two variables are called correlation. But in fact, we can't directly infer that there is a causal relationship between these two variables; See related inference causality (logical fallacy).

If the sample is the representative of the matrix, the inferences and conclusions made by the sample can be extended to the whole matrix. The biggest problem is to decide whether the sample is enough to represent the whole matrix. Statistics provides many methods to estimate and correct the randomness (error) in the process of sample collection and data collection, just like the experiment designed by experience mentioned above. See experimental design.

To understand randomness or probability, you must have basic mathematical concepts. Mathematical statistics (usually called statistical theory) is a branch of applied mathematics, which uses probability theory to analyze and verify the theoretical basis of statistics.

Any statistical method is effective only when the system or matrix meets the basic assumptions of methodology. Misuse of statistical data may lead to serious errors in description or inference, which may affect social policies, medical practice and the reliability of bridges or nuclear power generation plans.

Even if statistics are correctly applied, the results may be difficult for non-experts to state. For example, significant changes in statistical data may be caused by random variables in the sample, but this significance may be contrary to public intuition. Facing the information obtained by quoting statistical data in daily life, people need some statistical skills (or doubts).

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