![]() ![]() If they repeat the questionnaire days, weeks or months apart and give the same answers, this indicates high test-retest reliability. The consistency of a measure across time: do you get the same results when you repeat the measurement?Ī group of participants complete a questionnaire designed to measure personality traits. Types of reliabilityĭifferent types of reliability can be estimated through various statistical methods. Methods of estimating reliability and validity are usually split up into different types. Validity is harder to assess, but it can be estimated by comparing the results to other relevant data or theory. Reliability can be estimated by comparing different versions of the same measurement. The extent to which the results really measure what they are supposed to measure.īy checking the consistency of results across time, across different observers, and across parts of the test itself.īy checking how well the results correspond to established theories and other measures of the same concept.Ī reliable measurement is not always valid: the results might be reproducible, but they’re not necessarily correct.Ī valid measurement is generally reliable: if a test produces accurate results, they should be reproducible.ĭiscover proofreading & editing How are reliability and validity assessed? The extent to which the results can be reproduced when the research is repeated under the same conditions. Failing to do so can lead to several types of research bias and seriously affect your work. It’s important to consider reliability and validity when you are creating your research design, planning your methods, and writing up your results, especially in quantitative research. Reliability is about the consistency of a measure, and validity is about the accuracy of a measure.opt They indicate how well a method, technique. Reliability and validity are concepts used to evaluate the quality of research. Validity in Research | Difference, Types and Examples non-probability samplingĮliminate grammar errors and improve your writing with our free AI-powered grammar checker. Several common regression techniques can help reduce the influence of outliers on the mean value. If the outlier is confirmed as a valid extreme value, it should not be removed from the dataset. ![]() In this distribution the outlier value has increased the mean value.ĭespite the existence of outliers in a distribution, the mean can still be an appropriate measure of central tendency, especially if the rest of the data is normally distributed. However, it has not changed the middle of the distribution, and therefore the median value is still 57 years.ĥ4, 54, 54, 55, 56, 57, 57, 58, 58, 60, 81Īs the all values are included in the calculation of the mean, the outlier will influence the mean value. This value is much higher than the other values, and could be considered an outlier. The mean is more sensitive to the existence of outliers than the median or mode.Ĭonsider the initial retirement age dataset again, with one difference the last observation of 60 years has been replaced with a retirement age of 81 years. It is important to detect outliers within a distribution, because they can alter the results of the data analysis. Outliers are extreme, or atypical data value(s) that are notably different from the rest of the data. The mode is 54 years, the modal class is 54-56 years, the median is 56 years, and the mean is 57.2 years. The data has been grouped into classes, as the variable being measured (retirement age) is continuous. The following graph shows a larger retirement age data set with a distribution which is right skewed. Although there are exceptions to this rule, generally, most of the values, including the median value, tend to be less than the mean value. In a positively skewed distribution it is common for the mean to be ‘pulled’ toward the right tail of the distribution. In a skewed distribution, the median is often a preferred measure of central tendency, as the mean is not usually in the middle of the distribution.Ī distribution is said to be positively or right skewed when the tail on the right side of the distribution is longer than the left side. When a distribution is skewed the mode remains the most commonly occurring value, the median remains the middle value in the distribution, but the mean is generally ‘pulled’ in the direction of the tails. ![]()
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