Students who graduate from statistics, if they learn well, can be well used in basic research in many different disciplines such as medicine, physics, finance and computer. Statistics can now cross other disciplines well, such as financial statistics, biostatistics, mathematical statistics and so on.
It is the application of statistics in many industries and the intersection of so many disciplines that determines the employment prospects of students majoring in statistics are very broad. There are five categories of statistical employment: finance, IT, teachers, pharmacy and others. Either way, it is a high-paying industry.
Statistics, for example, is a foundation for the development of artificial intelligence, which is closely integrated with computers. ThomasJSargent, winner of the Nobel Prize in Economics, said that artificial intelligence is actually statistics, but in a very flowery language, it is actually statistics. Many formulas are very old, but all artificial intelligence uses statistics to solve problems.
Each link of statistical work:
1, model selection and establishment. In mathematical statistics, a model refers to some assumptions about the studied population, which usually specifies a certain type of population distribution. The establishment of the model should be based on probability knowledge, professional knowledge of the studied problem, past experience and samples (data) extracted from the population.
2. Data collection. There are three ways: comprehensive observation, sampling observation and arranging specific experiments. Comprehensive observation, also known as general survey, refers to observing each individual in the group and determining the required indicators. Sampling observation, also known as spot check, refers to extracting a part from the population and measuring its related index values. The research content in this field constitutes a branch of mathematical statistics. This is called a sampling survey.
3, arrange specific experiments to collect data, these specific experiments should be representative, and make the data easy to analyze. The mathematical problems involved constitute another branch of mathematical statistics, that is, the content of experimental design.
4. data collation. The purpose is to extract useful information contained in the data. One form is to make an appropriate chart, such as a scatter chart, to reflect the general rules or general trends implied in the data. The other form is to calculate some numerical features to describe some aspects of the sample, such as simple descriptive statistics such as sample mean and sample variance.
5. Statistical inference. It refers to drawing some conclusions about the population distribution according to the population model and the samples taken from the population. The collection and arrangement of data is the necessary preparation for statistical inference, which is the main task of mathematical statistics.