StatsUnit12
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Catégorie :Category: nCreator TI-Nspire
Auteur Author: Subzxro
Type : Classeur 3.0.1
Page(s) : 1
Taille Size: 3.27 Ko KB
Mis en ligne Uploaded: 16/04/2025 - 19:46:23
Uploadeur Uploader: Subzxro (Profil)
Téléchargements Downloads: 3
Visibilité Visibility: Archive publique
Shortlink : http://ti-pla.net/a4586255
Type : Classeur 3.0.1
Page(s) : 1
Taille Size: 3.27 Ko KB
Mis en ligne Uploaded: 16/04/2025 - 19:46:23
Uploadeur Uploader: Subzxro (Profil)
Téléchargements Downloads: 3
Visibilité Visibility: Archive publique
Shortlink : http://ti-pla.net/a4586255
Description
Fichier Nspire généré sur TI-Planet.org.
Compatible OS 3.0 et ultérieurs.
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Unit 12 Expected counts with one way table, take expected value / total then multiply by sample size With two way do (Row total * column total) / table total Chi square statistic = (obs. - exp.) ^ 2 / exp. Add all to get overall chi square statistic Df for table (rows - 1)(columns - 1) or (number of categories - 1) When given lin reg table, b is coef second row, a is coef first row/constant, Sb is stdev. Second row and S is population standard deviation. DF IS n - 2. Use InvT to find t value and then use b +- t(Sb) to find confidence interval (Area is half: 90% is 0.05) Confirm: (X^2) Ho: There is no difference (Seagulls dont have landing preference) (X^2) Ha: There is difference (Seagulls do have landing preference) (Linreg) Ho: b = 0 (Linreg) Ha: b < or > 0. Where b = slope of pop reg line relating y to x Conditions: Random: Random sample 200 seagulls or random assignment 10%: DO NOT USE IF EXPERIMENT Large Counts: All expected counts >= 5. (sample size * percentage or use table) (Linreg): Assume ALL Conditions are met. T test for slope is label. Calculate (Linreg): Linreg t test. State t, df, and p value Use Chi square for homogeneity if data come from 2 independent rand samples. (Diff or no diff in distribution) Interpret P value: Assuming distribution of (row label/context) is same for all (context), there is approx. (probability using x^2cdf) of observing diff in (row label) as large or largen than the ones in this study by chance alone. Chi sq independence: Tests for significant association between two categorical variables (is or is not association. Single sample.) Chi sq Goodnes of Fit: Determines if categorical variable follows hypothesized distribution. (Given percentages. Ex: Does data show that seagulls have preference for where they land? Do or do not) Stdev b = stdev / (stdevx * sqrt(n)) Conditions: LINER (Linear, Independent (10%), Normal dist, Equal SD, Random) SEb = s / (sx * sqrt(n - 1)) T test for slope: t = (b-hyp slope)/SEb Made with nCreator - tiplanet.org
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Compatible OS 3.0 et ultérieurs.
<<
Unit 12 Expected counts with one way table, take expected value / total then multiply by sample size With two way do (Row total * column total) / table total Chi square statistic = (obs. - exp.) ^ 2 / exp. Add all to get overall chi square statistic Df for table (rows - 1)(columns - 1) or (number of categories - 1) When given lin reg table, b is coef second row, a is coef first row/constant, Sb is stdev. Second row and S is population standard deviation. DF IS n - 2. Use InvT to find t value and then use b +- t(Sb) to find confidence interval (Area is half: 90% is 0.05) Confirm: (X^2) Ho: There is no difference (Seagulls dont have landing preference) (X^2) Ha: There is difference (Seagulls do have landing preference) (Linreg) Ho: b = 0 (Linreg) Ha: b < or > 0. Where b = slope of pop reg line relating y to x Conditions: Random: Random sample 200 seagulls or random assignment 10%: DO NOT USE IF EXPERIMENT Large Counts: All expected counts >= 5. (sample size * percentage or use table) (Linreg): Assume ALL Conditions are met. T test for slope is label. Calculate (Linreg): Linreg t test. State t, df, and p value Use Chi square for homogeneity if data come from 2 independent rand samples. (Diff or no diff in distribution) Interpret P value: Assuming distribution of (row label/context) is same for all (context), there is approx. (probability using x^2cdf) of observing diff in (row label) as large or largen than the ones in this study by chance alone. Chi sq independence: Tests for significant association between two categorical variables (is or is not association. Single sample.) Chi sq Goodnes of Fit: Determines if categorical variable follows hypothesized distribution. (Given percentages. Ex: Does data show that seagulls have preference for where they land? Do or do not) Stdev b = stdev / (stdevx * sqrt(n)) Conditions: LINER (Linear, Independent (10%), Normal dist, Equal SD, Random) SEb = s / (sx * sqrt(n - 1)) T test for slope: t = (b-hyp slope)/SEb Made with nCreator - tiplanet.org
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