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Transformations and Assumptions in Statistics

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Transformations and Assumptions in Statistics

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Questions and Answers

Which of the following is NOT a common transformation used to deal with violations of assumptions in statistical analysis?

Reciprocal

Absolute value (correct)

Square root

Log 10

What test is used to test the homogeneity of variance assumption in statistical analysis?

Levene’s test (correct)

ANOVA

Chi-square test

t-test

What is a general limitation of transformations in statistical analysis?

They require complex mathematical calculations

They can't cope with zeroes or negative numbers

They can only be applied to balanced samples

They are unpredictable (correct)

What is the main purpose of using transformations in statistical analysis?

To make the data follow a normal distribution Signup and view all the answers

What is a limitation of using transformations in statistical analysis?

They can't be applied to variables with too much variation Signup and view all the answers

Which statistical test is commonly used to measure the strength and direction of the linear relationship between two continuous/scale variables?

Pearson's correlation Signup and view all the answers

Which aspect of a relationship does Pearson's correlation measure?

Both size/magnitude and direction Signup and view all the answers

What type of variables can Pearson's correlation be used to measure the relationship between?

Continuous/scale variables only Signup and view all the answers

What does statistical significance assess in the context of Pearson's correlation?

Whether the relationship is due to chance Signup and view all the answers

What research question can Pearson's correlation help answer?

What is the nature of the relationship between years of schooling and job prestige? Signup and view all the answers

Study Notes

Transformations in Statistical Analysis

Common transformations:
- Log transformation
- Square root transformation
- Reciprocal transformation
- Box-Cox transformation
Levene's test: Used to test the homogeneity of variance assumption
General limitation of transformations: Can sometimes distort the original data and make it difficult to interpret the results

Purpose of Transformations

To meet the assumptions of statistical tests
To improve the normality of the data
To stabilize the variance of the data

Limitation of Transformations

Can make the data more difficult to interpret

Pearson's Correlation

Test: Used to measure the strength and direction of linear relationship between two continuous/scale variables
Measures: The strength and direction of a linear relationship
Variables: Can be used with continuous/scale variables
Significance: Assesses the probability that the observed relationship is due to chance
Research question: Can help answer whether there is a relationship between two variables and if so, how strong and in what direction it is.

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Description

Test your knowledge on transformations and assumptions in statistics with this quiz. Learn about common transformations such as logarithm, square root, and reciprocal, and how they can help deal with violations of assumptions. Explore graphs and normality tests to see if any transformations worked. Also, discover the importance of homogeneity of variance assumption and how it can be tested using Levene's test.