The correct answer is: True.
Statistical inference is the process of drawing conclusions about a population based on a sample of that population. It is a fundamental tool in statistics, and is used in a wide variety of fields, including science, business, and government.
There are two main types of statistical inference: parametric and nonparametric. Parametric inference assumes that the population data follows a particular distribution, such as a normal distribution. Nonparametric inference does not make any assumptions about the distribution of the population data.
Statistical inference can be used to make a variety of conclusions, including:
- Estimating the population mean or proportion
- Testing hypotheses about the population mean or proportion
- Making predictions about future data
Statistical inference is a powerful tool, but it is important to use it correctly. If the assumptions of the statistical test are not met, the results of the test may be invalid. It is also important to understand the limitations of statistical inference. Statistical inference can never provide certainty, only probability.
Here is a brief explanation of each option:
- A. True: Statistical inference is the process of drawing formal conclusions from data. This means that we use data to make inferences about a population, such as the population mean or proportion.
- B. False: Statistical inference is not the process of drawing conclusions from data. This is because statistical inference is a formal process that uses mathematical models to make inferences about a population.