Inferential statistics

What Inferential statistics is

Inferential statistics is a branch of statistics that uses sample data to draw conclusions about the population from which the sample was taken. It involves making predictions or inferences about a larger population based on information gathered from a sample group.

The steps for inferential statistics include the following:

  1. Collect the data: The data can be collected through surveys, experiments, or other methods.

  2. Analyze the data: This involves using descriptive statistics to summarize the data and using inferential statistics to draw conclusions.

  3. Interpret the results: Results should be interpreted in the context of the research question or hypothesis.

  4. Report the results: Results should be reported in a way that is easy to understand.

Examples

  1. A survey of 1,000 adults in the United States is used to estimate the proportion of Americans who own a smartphone.
  2. An experiment is conducted to compare the effectiveness of two different teaching methods.
  3. A sample of 100 college students is used to make inferences about the population of college students in the United States.
  4. The mean height of a sample of 10-year-old children is calculated and used to infer the mean height of 10-year-old children in the population.
  5. The correlation between study hours and exam scores is calculated to infer the relationship between the two variables.

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