How To Find The Estimated Standard Error
Du siehst YouTube auf Deutsch. Du kannst diese Einstellung unten ändern. Learn more You're viewing YouTube in German. You can change this preference below. Schließen Ja, ich möchte sie behalten Rückgängig machen Schließen Dieses Video ist nicht verfügbar. WiedergabelisteWarteschlangeWiedergabelisteWarteschlange Alle entfernenBeenden Wird geladen... Wiedergabeliste Warteschlange __count__/__total__ How to calculate standard error for the sample mean Stephanie Glen AbonnierenAbonniertAbo beenden6.0396 Tsd. Wird geladen... Wird geladen... Wird verarbeitet... Hinzufügen Möchtest du dieses Video später noch einmal ansehen? Wenn du bei YouTube angemeldet bist, kannst du dieses Video zu einer Playlist hinzufügen. Anmelden Teilen Mehr Melden Möchtest du dieses Video melden? Melde dich an, um unangemessene Inhalte zu melden. Anmelden Transkript Statistik 22.628 Aufrufe 54 Dieses Video gefällt dir? Melde dich bei YouTube an, damit dein Feedback gezählt wird. Anmelden 55 7 Dieses Video gefällt dir nicht? Melde dich bei YouTube an, damit dein Feedback gezählt wird. Anmelden 8 Wird geladen... Wird geladen... Transkript Das interaktive Transkript konnte nicht geladen werden. Wird geladen... Wird geladen... Die Bewertungsfunktion ist nach Ausleihen des Videos verfügbar. Diese Funktion ist zurzeit nicht verfügbar. Bitte versuche es später erneut. Veröffentlicht am 20.09.2013Find more videos and articles at: http://www.statisticshowto.com Kategorie Menschen & Blogs Lizenz Standard-YouTube-Lizenz Mehr anzeigen Weniger anzeigen Wird geladen... Anzeige Autoplay Wenn Autoplay aktiviert ist, wird die Wiedergabe automatisch mit einem der aktuellen Videovorschläge fortgesetzt. Nächstes Video Calculating the Standard Error of the Mean in Excel - Dauer: 9:33 Todd Grande 24.045 Aufrufe 9:33 Calculating mean, standard deviation and standard error in Microsoft Excel - Dauer: 3:38 Stephanie Castle 302.040 Aufrufe 3:38 Understanding Standard Error - Dauer: 5:01 Andrew Jahn 13.114 Aufrufe 5:01 Statistics 101: Standard Error of the Mean - Dauer: 32:03 Brandon Foltz 69.025 Aufrufe 32:03 Standard error of the mean - Dauer: 4:31 DrKKHewitt 16.164 Aufrufe 4:31 Standard Error - Dauer: 7:05 Bozeman Science 174.450 Aufrufe 7:05 How To Solve For Standard Error - Dauer: 3:17 Two-Point-Four 10.201 Aufrufe 3:17 Standard error of the mean | Inferential statistics | Probability and Statistics | Khan Academy - Dauer: 15:15 Khan Academy 498.974 Aufrufe 15:15 Confidence Interval for Population Means in Statistics - Dauer: 8:53 mathtutordvd 124.779 Aufrufe 8:53 Standard
the estimate from a scatter plot Compute the standard error of the estimate based on errors of prediction Compute the standard error using Pearson's correlation Estimate the standard error of the estimate based on a sample Figure 1 shows two regression examples. You can see that in Graph A, the points are closer to the line than they are in Graph B. Therefore, the predictions in Graph A are more accurate than in Graph B. Figure 1. Regressions differing in accuracy of prediction. The standard error of the estimate is a measure of the accuracy of predictions. Recall that the regression line is the line that minimizes the sum of squared deviations of prediction (also called the sum of squares error). The standard error https://www.youtube.com/watch?v=aBXJnvQ6KFk of the estimate is closely related to this quantity and is defined below: where σest is the standard error of the estimate, Y is an actual score, Y' is a predicted score, and N is the number of pairs of scores. The numerator is the sum of squared differences between the actual scores and the predicted scores. Note the similarity of the formula for σest to the formula for σ.  It turns out that σest is the http://onlinestatbook.com/lms/regression/accuracy.html standard deviation of the errors of prediction (each Y - Y' is an error of prediction). Assume the data in Table 1 are the data from a population of five X, Y pairs. Table 1. Example data. X Y Y' Y-Y' (Y-Y')2 1.00 1.00 1.210 -0.210 0.044 2.00 2.00 1.635 0.365 0.133 3.00 1.30 2.060 -0.760 0.578 4.00 3.75 2.485 1.265 1.600 5.00 2.25 2.910 -0.660 0.436 Sum 15.00 10.30 10.30 0.000 2.791 The last column shows that the sum of the squared errors of prediction is 2.791. Therefore, the standard error of the estimate is There is a version of the formula for the standard error in terms of Pearson's correlation: where ρ is the population value of Pearson's correlation and SSY is For the data in Table 1, μy = 2.06, SSY = 4.597 and ρ= 0.6268. Therefore, which is the same value computed previously. Similar formulas are used when the standard error of the estimate is computed from a sample rather than a population. The only difference is that the denominator is N-2 rather than N. The reason N-2 is used rather than N-1 is that two parameters (the slope and the intercept) were estimated in order to estimate the sum of squares. Formulas for a sample comparable to the ones for a population are shown below. Please answer the questions: feedback
to a normally distributed sampling distribution whose overall mean is equal to the mean of the source how to population and whose standard deviation ("standard error") is equal to the standard deviation of the source population divided by the square root ofn. To calculate the standard error how to find of any particular sampling distribution of sample means, enter the mean and standard deviation (sd) of the source population, along with the value ofn, and then click the "Calculate" button. -1sd mean +1sd <== sourcepopulation <== samplingdistribution standard error of sample means = ± parameters of source population mean = sd = ± sample size = Home Click this link only if you did not arrive here via the VassarStats main page. ©Richard Lowry 2001- All rights reserved.