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Level of measurement or scale of measure is a classification that describes the nature of information within the values assigned to variables. [1] Psychologist Stanley Smith Stevens developed the best-known classification with four levels, or scales, of measurement: nominal, ordinal, interval, and ratio.
A chart may indicate severe price swings because the chart only shows a portion of the range. When the entire price range is shown, the volatility is much less noticeable. A stock broker who earns fees from commissions can take advantage of interval ratio charts by using perceived volatility to encourage their customers to place more orders.
Spaced repetition with expanding intervals is believed to be so effective because with each expanded interval of repetition it becomes more difficult to retrieve the information because of the time elapsed between test periods; this creates a deeper level of processing of the learned information in long-term memory at each point.
If the dependent variable is continuous—either interval level or ratio level, such as a temperature scale or an income scale—then simple regression can be used. If both variables are time series , a particular type of causality known as Granger causality can be tested for, and vector autoregression can be performed to examine the ...
Some data are measured at the interval level. Numbers indicate the magnitude of difference between items, but there is no absolute zero point. Examples are attitude scales and opinion scales. Some data are measured at the ratio level. Numbers indicate magnitude of difference and there is a fixed zero point. Ratios can be calculated.
This doesn't attempt to teach you a language as you'd expect from a course but is simply a tool for assisting this process, with word lists in different languages and a resources list with external links to videos, blogs and newspapers etc. to help editors acquire a language. Learning a language and reaching a fluent level takes a lot of time ...
A frequency distribution shows a summarized grouping of data divided into mutually exclusive classes and the number of occurrences in a class. It is a way of showing unorganized data notably to show results of an election, income of people for a certain region, sales of a product within a certain period, student loan amounts of graduates, etc.
The correlation ratio was introduced by Karl Pearson as part of analysis of variance. Ronald Fisher commented: "As a descriptive statistic the utility of the correlation ratio is extremely limited. It will be noticed that the number of degrees of freedom in the numerator of depends on the number of the arrays" [1]