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What are the Gauss-Markov assumptions?

The Gauss-Markov assumptions are a group of assumptions used in linear regression analysis. They include the assumption that the influencing factors (the predictor variables) are independent of each other, the relationship between the influencing factors and the dependent variable is linear, the variance of the dependent variable is constant, and the residuals are normally distributed. The Gauss-Markov assumptions form the basis for linear regression analysis.

What is descriptive statistics?

Descriptive statistics is a form of statistics used to analyze and describe data. Descriptive statistics uses various procedures and techniques to extract and interpret information from large data sets. These include performing counts, calculating means, creating charts and graphs, and calculating correlation coefficients. Descriptive statistics can help gain a better understanding of the nature of data by helping to identify patterns and trends in the data.

What is the basic population?

The population is the set of all objects about which information is collected in a particular survey. It is the basis for creating a statistical survey and can consist of people, things, events or other elements.

What is a random sample?

A sample is a subset of a larger group selected to collect specific information. It is used to collect representative information about the entire group without checking each individual. A sample allows researchers to quickly and efficiently gather information about a large group of people or things.

What is the Bayes theorem?

Bayes theorem is a mathematical theorem that allows to calculate the probability of an event based on known information. It is commonly used in statistics, machine learning, and artificial intelligence. It allows predicted probabilities to be updated based on new information. It also helps determine the cause of an event. It was named after the English mathematician Thomas Bayes, who developed it in the 18th century.