sampling error.pptx

Research

1. What is error Definition: A statistical error is the (unknown) difference between the retained value and the true value.

2. Sampling vs non-sampling error

3. Sampling error statistical error that occurs when an analyst does not select a sample that represents the entire population of data . As a result, the results found in the sample do not represent the results that would be obtained from the entire population. The difference between the values derived from the sample of a population and the true values of the population parameters is considered a sampling error.

4. Factors Affecting Sampling Error Sampling error is affected by a number of factors including sample size, sample design, the sampling fraction and the variability within the population. In general, larger sample sizes decrease the sampling error, however this decrease is not directly proportional.

5. Categories of Sampling Errors Population Specification Error  – Happens when the analysts do not understand who to survey. For example, for a survey of breakfast cereals, the population can be the mother, children, or the entire family. Selection Error  – Occurs when the respondents’ survey participation is self-selected, implying only those who are interested respond. Selection errors can be reduced by encouraging participation. Sample Frame Error   – Occurs when a sample is selected from the wrong  population  data.

6. Categories of sampling error … Non-Response Error  – Occurs when a useful response is not obtained from the surveys. It may happen due to the inability to contact potential respondents or their refusal to respond . . Sampling Errors- Sampling errors occur when there is a lack of representativeness of the target population in the sample group. This is generally the result of poor sample designing

7. Measure of sampling error Standard Error The most commonly used measure of sampling error is called the standard error (SE).  The standard error is a measure of the spread of estimates around the "true value ". A small standard error indicates that the variation in values from repeated samples is small and, hence there is more likelihood that the sample estimate will be close to the result of an equal complete coverage.

8. Measures of…. Variance The variance is another measure of sampling error, which is simply the square of the standard error Relative Standard Error Another way of measuring sampling error is the relative standard error (RSE) where the standard error is expressed as a percentage of the estimate . The RSE avoids the need to refer to the estimate useful when comparing variability of population estimates with different means . Confidence interval:

9. How to Estimate the Sampling Error? . . The margin of error that is seen in survey results is an estimate of sampling error

10. What are the steps to reduce sampling errors? Increase sample size Divide the population into groups:  Test groups according to their size in the population instead of a random sample . Know your population  

11. Non-sampling error The error that arises in a  data  collection process as a result of factors other than taking a  sample . It is different from sampling error, which is any difference between the  sample values  and the universal values that may result from a limited sampling size. Non-sampling errors have the potential to cause  bias  in  polls ,  surveys  or samples.

12. Types of Non-Sampling Errors 1. Non-response error  it exists when people are given the option to participate but choose not to; therefore, their survey results are not incorporated into the data. 2. Measurement error A measurement error refers to all errors relating to the measurement of each sampling unit. The error often arises when there are confusing questions, low-quality data due to sampling fatigue (i.e., someone is tired of taking a survey), and low-quality measurement tools.

13. 3. Interviewer error Interviewer error occurs when the interviewer (or administrator) makes an error when recording a response. 4. Adjustment error An adjustment error describes a situation where the analysis of the data adjusts it so that it is not entirely accurate. Forms of adjustment error include errors with weighting the data, data cleaning, and imputation

14. 5. Processing error A processing error arises when there is a problem with processing the data that causes an error of some kind. An example will be if the data were entered incorrectly or if the data file is corrupt.