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  2. Linear trend estimation - Wikipedia

    en.wikipedia.org/wiki/Linear_trend_estimation

    All have the same trend, but more filtering leads to higher r 2 of fitted trend line. The least-squares fitting process produces a value, r-squared (r 2), which is 1 minus the ratio of the variance of the residuals to the variance of the dependent variable. It says what fraction of the variance of the data is explained by the fitted trend line.

  3. Sample size determination - Wikipedia

    en.wikipedia.org/wiki/Sample_size_determination

    The sample size is an important feature of any empirical study in which the goal is to make inferences about a population from a sample. In practice, the sample size used in a study is usually determined based on the cost, time, or convenience of collecting the data, and the need for it to offer sufficient statistical power. In complex studies ...

  4. Cochran–Armitage test for trend - Wikipedia

    en.wikipedia.org/wiki/Cochran–Armitage_test_for...

    where R 1 = N 11 + N 12 + N 13, and C 1 = N 11 + N 21, etc. . The trend test statistic is = (), where the t i are weights, and the difference N 1i R 2 −N 2i R 1 can be seen as the difference between N 1i and N 2i after reweighting the rows to have the same total.

  5. Trend line (technical analysis) - Wikipedia

    en.wikipedia.org/.../Trend_line_(technical_analysis)

    Chart from 1950 to about 1990, showing how linear scale obscures details by compressing the data. In finance, a trend line is a bounding line for the price movement of a security. It is formed when a diagonal line can be drawn between a minimum of three or more price pivot points.

  6. Trend analysis - Wikipedia

    en.wikipedia.org/wiki/Trend_analysis

    Trend analysis is the widespread practice of collecting information and attempting to spot a pattern. In some fields of study, the term has more formally defined meanings. In some fields of study, the term has more formally defined meanings.

  7. Simple linear regression - Wikipedia

    en.wikipedia.org/wiki/Simple_linear_regression

    The formulas given in the previous section allow one to calculate the point estimates of α and β — that is, the coefficients of the regression line for the given set of data. However, those formulas do not tell us how precise the estimates are, i.e., how much the estimators ^ and ^ vary from sample to sample for the specified sample size.