what is the difference between description and inferential statistics?

Answer 1

Descriptive statistics-

These are numbers that are used to consolidate a large amount of information. Any average, for example, is a descriptive statistic. So, batting averages, average daily rainfall, or average daily temperature are good examples of descriptive statistics.

Inferential statistics-

inferential statistics are used when we want to draw conclusions.
For example when we want to determine if some treatment is better than another, or if there are differences in how two groups perform. A good book definition is using samples to draw inferences about populations.

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DESCRIPTIVE AND INFERENTIAL STATISTICS

Statistics can be divided into two major areas. Descriptive statistics comprises the statistical methods dealing with the collection, tabulation and summarization of data, so as to present meaningful information. Statistical inference, on the other hand, consists of the methods involved with the analysis and interpretation of data that will enable the statistician to develop meaningful inferences about the data. Both subfields are interrelated; while descriptive statistics organizes the collected data in a systematic manner, statistical inference analyzes the data and enables one to produce significant inferences about it.

Answer 2

Inferential Statistics Vs Descriptive Statistics

Answer 3

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RE:
what is the difference between description and inferential statistics?

Answer 4

For the first it's descriptive of the data. For the second, you use the data to fit a model so that you can use the model to infer things about the population.

Ex. Sample 12 people out of 1000 to get their height. You 'describe' the sample with min, mean, mode, max, etc. When you use mean and variance to fit the normal model, then you can infer things such as the range of heights that contain 68% of the population.

Describe characteristics of the sample.
Infer details of the population.

Answer 5

yes