8.3 PPT
... o 10%?: We are sampling without replacement, so we need to assume that there are at least 10(40) = 400 light-duty engines of this type. • Large Sample: We don’t know if the population distribution of NOX emissions is Normal. Because the sample size is large, n = 40 > 30, we should be safe using a t ...
... o 10%?: We are sampling without replacement, so we need to assume that there are at least 10(40) = 400 light-duty engines of this type. • Large Sample: We don’t know if the population distribution of NOX emissions is Normal. Because the sample size is large, n = 40 > 30, we should be safe using a t ...
What is Error?
... population. 3. Standard deviation of the unknown population is the same as the known population. So, we can take the sample standard deviation as an estimate of the known population. ...
... population. 3. Standard deviation of the unknown population is the same as the known population. So, we can take the sample standard deviation as an estimate of the known population. ...
s10.pdf
... One important application of DES modeling is as an aid in discriminating among alternative designs. Assume we are interested in the value of a single measure of system performance with mean value of . Since we may have various alternative designs which we want to compare the corresponding mean perf ...
... One important application of DES modeling is as an aid in discriminating among alternative designs. Assume we are interested in the value of a single measure of system performance with mean value of . Since we may have various alternative designs which we want to compare the corresponding mean perf ...
data prep and descriptive stats
... Legibility (non-ambiguous) Right informant Consistency e.g. charging something when the person does not ...
... Legibility (non-ambiguous) Right informant Consistency e.g. charging something when the person does not ...
251solnO1 - On
... hypothesis test! Our so-called null hypothesis is H 0 : 400 . Showing that 400 does not fall on the confidence interval constructed from our sample statistic, we have shown that the mean is significantly different from 400 (at the 5% significance level). No. Since is known and n = 64, from the ...
... hypothesis test! Our so-called null hypothesis is H 0 : 400 . Showing that 400 does not fall on the confidence interval constructed from our sample statistic, we have shown that the mean is significantly different from 400 (at the 5% significance level). No. Since is known and n = 64, from the ...
Lecture 1: Random Walks, Distribution Functions
... Assymptotic limit of the binomial distribution for p << 1 Large n, constant mean small samples of large populations ...
... Assymptotic limit of the binomial distribution for p << 1 Large n, constant mean small samples of large populations ...
1 CHECKING MODEL ASSUMPTIONS (CHAPTER 5) The
... Methods for dealing with unequal variance: a. Transform the response variable: Replace Y with h(Y), so that the model becomes • h(Yit) = µ* + τi* + εit* • The εit*'s are independent random variables. • For each i and t, εit* ~ N(0 , σ2) (More on this later) b. Use a method such as Satterthwaite's (p ...
... Methods for dealing with unequal variance: a. Transform the response variable: Replace Y with h(Y), so that the model becomes • h(Yit) = µ* + τi* + εit* • The εit*'s are independent random variables. • For each i and t, εit* ~ N(0 , σ2) (More on this later) b. Use a method such as Satterthwaite's (p ...
Non-Parametric Statistics
... How does one carry out an ANOVA? An ANOVA is conducted by first putting all the samples into one, large sample. The standard deviation of this sample is then found, and called . Next, the value for the range of variation in sample means is found. If the variation between the means is greater than ...
... How does one carry out an ANOVA? An ANOVA is conducted by first putting all the samples into one, large sample. The standard deviation of this sample is then found, and called . Next, the value for the range of variation in sample means is found. If the variation between the means is greater than ...
two-tailed test - Bakersfield College
... variable causes an increase in scores, then the null hypothesis is that the population mean is less than or equal to a given value and the alternative hypothesis is that the population mean is greater than the same value. For ...
... variable causes an increase in scores, then the null hypothesis is that the population mean is less than or equal to a given value and the alternative hypothesis is that the population mean is greater than the same value. For ...
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.