Bootstrapping D. Patterson, Dept. of Mathematical Sciences, U. of
... 4. Studentized: The Studentized interval is a variation on the Basic interval. The Basic interval approximates the distribution of T (X)−θ(F ) by the distribution of T (X ∗ )−θ(Fb ). Looking at the difference between the the statistic and what it’s estimating compensates, in one way, for the fact th ...
... 4. Studentized: The Studentized interval is a variation on the Basic interval. The Basic interval approximates the distribution of T (X)−θ(F ) by the distribution of T (X ∗ )−θ(Fb ). Looking at the difference between the the statistic and what it’s estimating compensates, in one way, for the fact th ...
Estimation of the Mean and Proportion
... 110 Chapter 8 Estimation of the Mean and Proportion Example 8-2 According to a report by the Consumer Federation of America, National Credit Union Foundation, and the Credit Union National Association, households with negative assets carried an average of $15,528 in debt in 2002 (CBS.MarketWatch.co ...
... 110 Chapter 8 Estimation of the Mean and Proportion Example 8-2 According to a report by the Consumer Federation of America, National Credit Union Foundation, and the Credit Union National Association, households with negative assets carried an average of $15,528 in debt in 2002 (CBS.MarketWatch.co ...
Distribution Analyses
... A parametric family of distributions is a collection of distributions with a known form that is indexed by a set of quantities called parameters. Methods based on parametric distributions of normal, lognormal, exponential, and Weibull are available in a distribution analysis. This section describes ...
... A parametric family of distributions is a collection of distributions with a known form that is indexed by a set of quantities called parameters. Methods based on parametric distributions of normal, lognormal, exponential, and Weibull are available in a distribution analysis. This section describes ...
Package ‘bootstrap’ February 19, 2015
... A data frame with 14 observations on the following 2 variables. dose a numeric vector, unit rads/100 log.surv a numeric vector, (natural) logarithm of proportion Details There are regression situations where the covariates are more naturally considered fixed rather than random. This cell survival da ...
... A data frame with 14 observations on the following 2 variables. dose a numeric vector, unit rads/100 log.surv a numeric vector, (natural) logarithm of proportion Details There are regression situations where the covariates are more naturally considered fixed rather than random. This cell survival da ...
Linear regression
... for each district, that is, i = 1, . . . , n, where b0 is the intercept of this line and b1 is the slope. (The general notation “b1” is used for the slope in Equation (4.5) instead of “bClassSize” because this equation is written in terms of a general variable Xi.) Equation (4.5) is the linear regre ...
... for each district, that is, i = 1, . . . , n, where b0 is the intercept of this line and b1 is the slope. (The general notation “b1” is used for the slope in Equation (4.5) instead of “bClassSize” because this equation is written in terms of a general variable Xi.) Equation (4.5) is the linear regre ...
+ Confidence Intervals: The Basics
... The confidence interval for estimating a population parameter has the form statistic ± (critical value) • (standard deviation of statistic) where the statistic we use is the point estimator for the parameter. Properties of Confidence Intervals: The user chooses the confidence level, and the margin ...
... The confidence interval for estimating a population parameter has the form statistic ± (critical value) • (standard deviation of statistic) where the statistic we use is the point estimator for the parameter. Properties of Confidence Intervals: The user chooses the confidence level, and the margin ...
0.95
... a) tα /2 and n =18 for the 99% confidence interval (C.I.) for the mean d.f. = 17 From table F, confidence interval=99% and d.f. =17 → tα /2 =2.898 b) tα /2 and n =23 for the 95% confidence interval (C.I.) for the mean d.f. = 22 From table F, confidence interval=95% (C.I.) and d.f. =22 → tα /2 =2.074 ...
... a) tα /2 and n =18 for the 99% confidence interval (C.I.) for the mean d.f. = 17 From table F, confidence interval=99% and d.f. =17 → tα /2 =2.898 b) tα /2 and n =23 for the 95% confidence interval (C.I.) for the mean d.f. = 22 From table F, confidence interval=95% (C.I.) and d.f. =22 → tα /2 =2.074 ...