comparing distributions: the two-sample anderson
... than between-condition differences. Finally, the data at one time point are highly correlated with the data at the previous and following time point, influencing the probability of a type I error rate. There are several types of non-parametric or distribution-free (they neither depend on the specifi ...
... than between-condition differences. Finally, the data at one time point are highly correlated with the data at the previous and following time point, influencing the probability of a type I error rate. There are several types of non-parametric or distribution-free (they neither depend on the specifi ...
Review of Probability Table of Contents Part I: Basic
... ∗ If you know P (E), P (F ) and P (E ∪ F ) then you can use the addition rule. ∗ If you know P (E) and P (F |E) then you can use the multiplicative rule. ∗ If you know P (E) and P (F ) and you know that E and F are independent then you can use the multiplicative rule. b) Suppose you want to find P ...
... ∗ If you know P (E), P (F ) and P (E ∪ F ) then you can use the addition rule. ∗ If you know P (E) and P (F |E) then you can use the multiplicative rule. ∗ If you know P (E) and P (F ) and you know that E and F are independent then you can use the multiplicative rule. b) Suppose you want to find P ...
The Construction of Literature Indexes Using SAS
... lines and the source identification is entered on a single line. A detailed description for preparing input is included in the documentation provided in the listing (Figure 6). For the example of Figure 1 the first -two references used 5 lines (cards) each and the last reference used four lines. The ...
... lines and the source identification is entered on a single line. A detailed description for preparing input is included in the documentation provided in the listing (Figure 6). For the example of Figure 1 the first -two references used 5 lines (cards) each and the last reference used four lines. The ...
Null Hypothesis Significance Testing I
... decreasing the variance of the null and alternative distributions. In experimental design it is important to determine ahead of time the number of trials or subjects needed to achieve a desired power. Example 8. Suppose a drug for a disease is being compared to a placebo. We choose our null and alte ...
... decreasing the variance of the null and alternative distributions. In experimental design it is important to determine ahead of time the number of trials or subjects needed to achieve a desired power. Example 8. Suppose a drug for a disease is being compared to a placebo. We choose our null and alte ...
1 Theory: The General Linear Model
... The most frequent criterion used to estimate the GLM parameters is called the least squares criterion. This criterion minimizes the sum of the squared difference between observed and predicted values, the summation being over the observations in the data set. To examine this criterion, subscript the ...
... The most frequent criterion used to estimate the GLM parameters is called the least squares criterion. This criterion minimizes the sum of the squared difference between observed and predicted values, the summation being over the observations in the data set. To examine this criterion, subscript the ...
