What is Bias What is Bias If a statistics is said to be biased if its calculated in a way such that its slightly different from the interest of the population. The following statements are not mutually exclusive like The individuals and the groups are generally more interested to have part in a research project then others that results in the biased samples. The bias is the compensation value that can be considered as the difference to the original value that either subtracted or added. For example Sine function always refers the value between the range -1 to +1. If the positive value is needed not negative value then its needed to preserve the function between the highest and the lowest value mean to say that a bias of one is needed to the result of the sine function. Bias Definition can also be explored as follows â€œA statistical process is called as biased process if the number of the possible outcomes are not the same and its considered that there is a bias towards more likely possible outcomes.â€?
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or “If the possible outcomes are not equally likely of a dice then the dice is said to be biased if all the results that could be get are equally likely.” A survey has finished and according to the result ”a biased sample is the sample that would not reflect the whole population but reflects only the samples.” If a survey is carried out outside a bus station about that how people get to work then definitely the result would be a biased sample because the result and the survey does not deals with the whole or measure population. There are a number of biases such as representative bias, quo bias, home bias, familiar bias, endowment effect bias, mood and optimism bias, overconfidence bias, media and Internet bias etc. Sample selection bias is a type of bias that is caused by choosing non random data for the statistical analysis. The bias exists because of a flaw in the sample selection process where the subset of the data is excluded due to a particular attribute of the population. This exclusion could be a cause for the distorted results. Survivorship bias is the most common type of the sample selection bias. Basically bias refers to the meaning that how far the average statistic lies from the parameter. Biasing deals with the mean error that arises when dealing with the quantity. Errors that are occurred would cancel each other in the long run that are those bias would not do. If a police decided to estimate the average speed of the drivers using the fast lane of the motorway and determine that how it takes place.
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One way that could be followed by the police is to tail the cars using the police petrol cars and then record their speeds as catch the same speed as the police car. This is the example of to obtain a biased result as no driver can exceeds the speed limit slow then a police car behind them. After that the police explores the investigation with the use of an unmarked car and a speed gun that is operated by the constable. This is the example of unbiased method to measure the speed of the cars.
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