Confidence Intervals
... error known as the probable error. For example, an estimate x-bar of the average useful life of a TV picture tube is said to have a probable error of e years if there is a 50% chance that the interval from x-bar – e to x-bar + e has a 50% chance of including the population mean. Calculate the probab ...
... error known as the probable error. For example, an estimate x-bar of the average useful life of a TV picture tube is said to have a probable error of e years if there is a 50% chance that the interval from x-bar – e to x-bar + e has a 50% chance of including the population mean. Calculate the probab ...
Tutorial 6 Regression lines using Mathcad
... “In this puzzle, you should not use your intuition, but let your common sense do the job: the chance that your first choice for a door was correct is 1/3; therefore, the chance that your first choice was wrong is 2/3. So the chance that one of the remaining doors is correct is also 2/3. With the hel ...
... “In this puzzle, you should not use your intuition, but let your common sense do the job: the chance that your first choice for a door was correct is 1/3; therefore, the chance that your first choice was wrong is 2/3. So the chance that one of the remaining doors is correct is also 2/3. With the hel ...
Measures of Dispersion
... Measures the variation of observations from the mean The most common measure of dispersion Takes into account every observation Measures the ‘average deviation’ of observations from mean Works with squares of residuals not absolute values—easier to use in further calculations © 2002 McGraw-Hill Aust ...
... Measures the variation of observations from the mean The most common measure of dispersion Takes into account every observation Measures the ‘average deviation’ of observations from mean Works with squares of residuals not absolute values—easier to use in further calculations © 2002 McGraw-Hill Aust ...
Comparison of precision of systematic sampling with some other
... within group variability is usually referred to as error variance. If the strata are homogeneous, the variability within-groups is expected to be lower than the variability for the population as a whole. From the table (4-2), it is seen that !" > ( # ). As from table (4-6), it is noticed that ! ...
... within group variability is usually referred to as error variance. If the strata are homogeneous, the variability within-groups is expected to be lower than the variability for the population as a whole. From the table (4-2), it is seen that !" > ( # ). As from table (4-6), it is noticed that ! ...
Sample student project - Depression vs. Age
... Everyone feels depressed at times. Illness, the loss of a family member, the breakup of a relationship - these misfortunes and many more are natural causes of sadness and mourning. It is normal to feel depressed about a loss or failure. However, for many people, that feeling of despondency continues ...
... Everyone feels depressed at times. Illness, the loss of a family member, the breakup of a relationship - these misfortunes and many more are natural causes of sadness and mourning. It is normal to feel depressed about a loss or failure. However, for many people, that feeling of despondency continues ...
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.