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Types of non-sampling errors?
refers to difference between sample & population that exist only coz of the observations that happened to be selected for the sample.
What is the difference between test of transactions and test of details?
Test of transaction is a test set up to dectect monetary error in accountings. On the other hand, Test of balance are again directed towards detecting monetary errors in the financial statement. The only difference is that testing is concentrated on the balance itself and not the individual transaction which comprise the balance. Through management's assertion, one can derive the objectives.
What is the difference between a mistake and an error in statistics for research?
The Difference between the real value and the expected value creates Error of Origin. Whereas wrong statistical method used in the research or we calculated in a wrong way this is called mistake in stats.Errors are not willingly done but mistakes are done knowinglyError occurs at the stage of Collecting data, Analyzing it or at the time of Interpretation. Whereas Mistakes can be done at any stage of Research.Predicting Error is easy but it is difficult while making mistake in research.One cannot stop Errors but we can stop making mistakes in research.Posted by Elana Bhandari,Jodhpur.
What are the errors in levelling?
there are few types of errors in levelling...... these arr...... 1- instrumental error 2- collimation error 3- errors due to curvature and refraction 4- some other errors also
How does a linear regression allow us to better estimate trends costs and other factors in complex situations?
You question is how linear regression improves estimates of trends. Generally trends are used to estimate future costs, but they may also be used to compare one product to another. I think first you must define what linear regression is, and what the alternative forecast methods exists. Linear regression does not necessary lead to improved estimates, but it has advantages over other estimation procesures. Linear regression is a mathematical procedure that calculates a "best fit" line through the data. It is called a best fit line because the parameters of the line will minimizes the sum of the squared errors (SSE). The error is the difference between the calculated dependent variable value (usually y values) and actual their value. One can spot data trends and simply draw a line through them, and consider this a good fit of the data. If you are interested in forecasting, there are many methods available. One can use more complex forecasting methods, including time series analysis (ARIMA methods, weighted linear regression, or multivariant regression or stochastic modeling for forecasting. The advantages to linear regression are that a) it will provide a single slope or trend, b) the fit of the data should be unbiased, c) the fit minimizes error and d) it will be consistent. If in your example, the errors from regression from fitting the cost data can be considered random deviations from the trend, then the fitted line will be unbiased. Linear regression is consistent because anyone who calculates the trend from the same dataset will have the same value. Linear regression will be precise but that does not mean that they will be accurate. I hope this answers your question. If not, perhaps you can ask an additional question with more specifics.
