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Kamus lengkap Kecerdasan Buatan

162
kategori
2.032
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23.060
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Contingency table

Two-dimensional matrix presenting the joint distribution of two categorical variables, with observed counts in each cell crossing the categories.

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Chi-square test

Non-parametric statistical test evaluating the association between categorical variables by comparing observed frequencies to expected frequencies under the null hypothesis.

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Degrees of freedom

Statistical parameter calculated as (number of rows - 1) × (number of columns - 1) in a contingency table, determining the reference distribution of the test.

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p-value

Probability of obtaining a test statistic at least as extreme as the one observed, under the null hypothesis of no association between the variables.

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Independence test

Specific application of the chi-square test checking whether two categorical variables are statistically independent in the studied population.

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Goodness-of-fit test

Chi-square variant comparing an observed distribution to a specified theoretical distribution, to evaluate how well the data fit an expected model.

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Cross-tabulation

Tabular representation summarizing relationships between categorical variables, including absolute frequencies, relative frequencies, and margins for each category.

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Observed frequency

Actual number of individuals in each cell of the contingency table, corresponding to raw data collected in the sample.

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Expected frequency

Theoretical frequency in each cell under the null hypothesis, calculated as (row total × column total) / grand total of the sample.

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Contingency coefficient

Measure of association between categorical variables derived from chi-square, ranging from 0 to a maximum value depending on the table size.

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Cramér's V

Standardized association coefficient ranging from 0 to 1, measuring the strength of the relationship between categorical variables by adjusting chi-square for sample size.

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Fisher's exact test

Alternative test to chi-square for small samples, calculating the exact probability of the observed distribution under the null hypothesis of independence.

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Standardized residuals

Differences between observed and expected frequencies, normalized by their standard deviation, identifying the cells contributing most to the overall dependence.

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Marginal table

Summary of a contingency table presenting row and column totals, essential for calculating expected frequencies and conditional proportions.

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Theoretical frequency

Expected value in each cell if the variables were independent, serving as a reference to evaluate significant deviations in the analysis.

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Pearson's chi-square

Fundamental test statistic calculated as the sum of squared normalized deviations between observed and theoretical frequencies, following a chi-square distribution.

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Mc Nemar Test

Specialized statistical test for paired dichotomous data, assessing changes in proportions between two time measurements on the same sample.

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Yates Correction

Continuity adjustment applied to chi-square for 2×2 tables with small sample sizes, reducing observed frequencies by 0.5 to improve approximation.

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Probability Table

Joint distribution of probabilities for each combination of categories, normalized by the total sample size to facilitate interpretation.

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