Chapter 3
... 76. A purchasing agent for a trucking company is shopping for replacement tires for their trucks from two suppliers. The suppliers' prices are the same. However, Supplier A's tires have an average life of 60,000 miles with a standard deviation of 10,000 miles. Supplier B's tires have an average life ...
... 76. A purchasing agent for a trucking company is shopping for replacement tires for their trucks from two suppliers. The suppliers' prices are the same. However, Supplier A's tires have an average life of 60,000 miles with a standard deviation of 10,000 miles. Supplier B's tires have an average life ...
MKgrading2493 - Emerson Statistics
... to the corresponding inference from problem 1? The true difference in mean serum LDL between a population that survives at least 5 years and a population that dies within 5 years is 8.501 mg/dL (SE: 3.36, C: 1.91, 15.09). The resulting p value from this analysis is p=0.012. Thus we can reject the nu ...
... to the corresponding inference from problem 1? The true difference in mean serum LDL between a population that survives at least 5 years and a population that dies within 5 years is 8.501 mg/dL (SE: 3.36, C: 1.91, 15.09). The resulting p value from this analysis is p=0.012. Thus we can reject the nu ...
Moments and the Shape of Histograms
... We need a measure that in some sense “balances” the smaller and the larger observations; we need to allow for a very large observation to offset many small ones. If we look at just two numbers, an obvious measure of the center of location is halfway between; that is, the center is given by (a + b)/2 ...
... We need a measure that in some sense “balances” the smaller and the larger observations; we need to allow for a very large observation to offset many small ones. If we look at just two numbers, an obvious measure of the center of location is halfway between; that is, the center is given by (a + b)/2 ...
Bootstrapping (statistics)
In statistics, bootstrapping can refer to any test or metric that relies on random sampling with replacement. Bootstrapping allows assigning measures of accuracy (defined in terms of bias, variance, confidence intervals, prediction error or some other such measure) to sample estimates. This technique allows estimation of the sampling distribution of almost any statistic using random sampling methods. Generally, it falls in the broader class of resampling methods.Bootstrapping is the practice of estimating properties of an estimator (such as its variance) by measuring those properties when sampling from an approximating distribution. One standard choice for an approximating distribution is the empirical distribution function of the observed data. In the case where a set of observations can be assumed to be from an independent and identically distributed population, this can be implemented by constructing a number of resamples with replacement, of the observed dataset (and of equal size to the observed dataset).It may also be used for constructing hypothesis tests. It is often used as an alternative to statistical inference based on the assumption of a parametric model when that assumption is in doubt, or where parametric inference is impossible or requires complicated formulas for the calculation of standard errors.