Soal Uas Statistika Inferensial Doc Yayasan Sasmita Jaya Group Universitas Pamulang Sk Mendiknas No 136 D 0 2001 Fakultas Ekonomi Program Studi S1 Course Hero from Check spelling or type a new query. Maybe you would like to learn more about one of these? Check spelling or type a new query. Soal Soal Statistika Inferensial Pdfcoffee Com from We did not find results for: Maybe you would like to learn more about one of these? Check spelling or type a new query.
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Maybe you would like to learn more about one of these? We did not find results for: Residual AnalysisDetecting OutliersAn outlier is an observation that is unusual in comparison with the other data.Minitab classifies an observation as an outlier if its standardized residual value is +2.This standardized residual rule sometimes fails to identify an unusually large observation as being an outlier.This rules shortcoming can be circumvented by using studentized deleted residuals.The |i th studentized deleted residual| will be larger than the |i th standardized residual|.Check spelling or type a new query.
Contoh soal statistik probabilitas tv#
Where the confidence coefficient is 1 - and t/2 is based on a t distribution with n - 2 d.f.Using the Estimated Regression Equation for Estimation and PredictionĬontoh Soal: Reed Auto SalesPoint EstimationIf 3 TV ads are run prior to a sale, we expect the mean number of cars sold to be:y = 10 + 5(3) = 25 carsConfidence Interval for E(yp)95% confidence interval estimate of the mean number of cars sold when 3 TV ads are run is:25 + 4.61 = 20.39 to 29.61 carsPrediction Interval for yp95% prediction interval estimate of the number of cars sold in one particular week when 3 TV ads are run is: 25 + 8.28 = 16.72 to 33.28 cars^
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Some Cautions about theInterpretation of Significance TestsRejecting H0: b1 = 0 and concluding that the relationship between x and y is significant does not enable us to conclude that a cause-and-effect relationship is present between x and y.Just because we are able to reject H0: b1 = 0 and demonstrate statistical significance does not enable us to conclude that there is a linear relationship between x and y. = 1, 3: F.05 = 10.13 Reject H0 if F > 10.13.Test StatisticF = MSR/MSE = 100/4.667 = 21.43ConclusionWe can reject H0.Example: Reed Auto Sales
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in the denominator.į TestHypotheses H0: 1 = 0 Ha: 1 = 0Rejection Rule For =. Where F is based on an F distribution with 1 d.f. Testing for Significance: F TestHypotheses H0: 1 = 0 Ha: 1 = 0Test StatisticF = MSR/MSERejection RuleReject H0 if F > F Where b1 is the point estimateis the margin of erroris the t value providing an areaof a/2 in the upper tail of a t distribution with n - 2 degreesof freedomĬontoh Soal: Reed Auto SalesRejection RuleReject H0 if 0 is not included in the confidence interval for 1.95% Confidence Interval for 1 = 5 +- 3.182(1.08) = 5 +- 3.44/or 1.56 to 8.44/ConclusionReject H0 = 3, t.025 = 3.182 Reject H0 if t > 3.182Test Statisticst = 5/1.08 = 4.63Conclusions Reject H0Ĭonfidence Interval for 1We can use a 95% confidence interval for 1 to test the hypotheses just used in the t test.H0 is rejected if the hypothesized value of 1 is not included in the confidence interval for 1.Ĭonfidence Interval for 1The form of a confidence interval for 1 is: Where t is based on a t distribution with n - 2 degrees of freedom.Ĭontoh Soal: Reed Auto Salest Test Hypotheses H0: 1 = 0 Ha: 1 = 0Rejection Rule For =. Testing for Significance: t TestHypotheses H0: 1 = 0 Ha: 1 = 0Test Statistic Testing for SignificanceAn Estimate of sTo estimate s we take the square root of s 2.The resulting s is called the standard error of the estimate. Testing for SignificanceAn Estimate of s 2The mean square error (MSE) provides the estimateof s 2, and the notation s2 is also used. Testing for SignificanceTo test for a significant regression relationship, we must conduct a hypothesis test to determine whether the value of b1 is zero.Two tests are commonly usedt TestF TestBoth tests require an estimate of s 2, the variance of e in the regression model. Outline MateriPengujian koefisien regresi dengan analisis variansInferensia tentang koefisien korelasi
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Learning OutcomesPada akhir pertemuan ini, diharapkan mahasiswa akan mampu :Mahasiswa akan dapat memilih statistik uji untuk koefisien regresi dan korelasi. Pertemuan 13Regresi Linear dan KorelasiMatakuliah: I0262 Statistik ProbabilitasTahun: 2007Versi: Revisi