Statistical errors are those which are occurred during the collection of data and it is dependent on the size of the sample selected to study. These are of 2 types:
- Sampling error
- Non-sampling error
Let’s understand this topic in detail.
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What is the ‘population’ or the ‘Universe’?
See, in statistics population or the universe means the total number of items under study.
What is the sample?
It refers to a group or sample of the population from which information is to be calculated or obtained.
Types of Statistical Errors
There are 2 types of errors in statistics:
1. Sampling Error
These are related to the size or nature of the sample selected for the study. I know these are complicated to understand. Let me try again, let’s assume there are 15 people sitting in a coffee shop. To get a review on the service, if I approach only 2 people then my sample size(2) is very small as compared to the population (15).
The sampling error occurs because of the small sample size selected for the study. Due to the small sample, the estimated value (calculated) may be different from the actual value (true).
Sampling Error = Estimated Value – Actual Value
Sampling Error = 10 – 20 = – 10.
2. Non- Sampling Error
These errors are related to the collection of data. These are of the following types:
Error of Measurement
It can occur due to the difference in the scale of measurement and difference in rounding of the procedure adopted by the different investigators.
Error of Non response
It arises when the respondent do not offer the required information.
Error of Misinterpretation
It arises when the respondent fails to interpret the question in the questionnaire.
Error of Calculation
It occurs while adding, subtraction, multiplying or division of data.
Error of Sampling bias
It occurs when a part of the target population, cannot be included in the sample.
I hope it was helpful, you can refer more posts related to the statistics.
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