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## Why would you transform distributions into z-scores?

These scores are a useful way of putting data from different sources onto the same scale. For example, if you wanted **to plot change over time in weight and blood pressure on the same graph** you could transform the raw measurements into Z scores and plot them on the same scale.

## Why is there a need to transform raw scores to z-scores?

By converting a raw score to a z- score, we are expressing that **score on a z-score scale**, which always has a mean of 0 and a standard deviation of 1. In short, we are re-defining each raw score in terms of how far away it is from the group mean. scores is much clearer. … probability of a given score occurring.

## How are z-scores used to transform any distribution?

– Each z-score tells the exact location of the original X value within the distribution. – The z-scores form a **standardized distribution** that can be directly compared to other distributions that also have been transformed into z-scores.

## Why do we need to transform scores?

Why Do We Need to Transform Scores? Converting scores from raw scores into transformed scores has two purposes: **It gives meaning to the scores and allows some kind of interpretation of the scores**. It allows direct comparison of two scores.

## Why Z transform is used in statistics?

Z transformation is **the process of standardization that allows for comparison of scores from disparate distributions**. Using a distribution mean and standard deviation, z transformations convert separate distributions into a standardized distribution, allowing for the comparison of dissimilar metrics.

## What is the purpose of z-scores Quizizz?

A z-score **tells us how many standard deviations a score is from the mean**.

## What is the purpose of z-scores quizlet?

The purpose of z-scores is **to identify and describe the exact location of each score in a distribution & to standardize an entire distribution to understand & compare scores from different tests**.

## Why do researchers use z-scores to determine probabilities What are the advantages to using z-scores?

Z-scores are important because **they offer a comparison between two scores that are not in the same normal distribution**. They are also used to obtain the probability of a z-score to take place within a normal distribution. If a z-score gives a negative value, it means that raw data is lesser than mean.

## What happens when scores are transformed into z-scores?

When **an entire distribution of X values** is transformed into z-scores, the resulting distribution of z-scores will always have a mean of zero and a standard deviation of one.