# Reviewing Griffith normalisation problem

• hagopbul
In summary, Griffith normalisation is a statistical concept used in scientific research to transform data to a standard scale for easier comparison and analysis. It involves dividing each data point by the total sum of the data, resulting in a normalized value between 0 and 1. This technique is important because it allows for fair comparison and analysis of data with different scales and units, and helps to reduce the impact of outliers. However, it has limitations such as assuming a linear relationship between variables and may not be suitable for datasets with extreme outliers or highly skewed distributions. To apply Griffith normalisation in research, one must first calculate the total sum of the data and then divide each data point by the total sum. This can be done manually or with software programs such
hagopbul
Homework Statement
It is about normalisation I am posting the image of the question down below
Relevant Equations
Integral { psi(X,t) = |psi(X,t)|^2 dx} from X=-inf to X= + inf

My problem is in (b) it written sketch psi (X,0) as function of X , why the answer was like this

I didn't understand the branch from a to b

Best

You are given that between ##x = a## and ##x = b## the wave function is

##\psi(x) = A \frac{b-x}{b-a}##

You should be able to tell that this is linear and has negative slope. What particular aspect of the graph is bothering you?

Thank you solve it just was problem with the rendering the graph made me confused for a moment

TSny

## 1. What is the Griffith normalisation problem?

The Griffith normalisation problem is a statistical issue that arises when comparing two different populations or groups. It refers to the phenomenon where the values of a variable in one group are consistently higher or lower than the values in another group, even though the two groups have similar means and standard deviations.

## 2. How does the Griffith normalisation problem affect data analysis?

The Griffith normalisation problem can lead to biased results and incorrect conclusions if not properly addressed. It can obscure the true differences between groups and can affect the interpretation of statistical tests and models.

## 3. What causes the Griffith normalisation problem?

The Griffith normalisation problem can be caused by a variety of factors, including differences in sample size, measurement error, or underlying population distributions. It can also be a consequence of confounding variables or the choice of statistical methods used for data analysis.

## 4. How can the Griffith normalisation problem be addressed?

Several methods can be used to address the Griffith normalisation problem, including data transformation techniques, such as logarithmic or rank transformations. Another approach is to use statistical models that take into account the differences between groups, such as analysis of covariance (ANCOVA) or generalized linear models (GLMs).

## 5. Is the Griffith normalisation problem a common issue in scientific research?

Yes, the Griffith normalisation problem is a common issue in many fields of scientific research, including biology, psychology, and social sciences. It is important for researchers to be aware of this problem and to properly address it in their data analysis to ensure accurate and reliable results.

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