Podcast
Questions and Answers
Which of the following is NOT a common transformation used to deal with violations of assumptions in statistical analysis?
Which of the following is NOT a common transformation used to deal with violations of assumptions in statistical analysis?
What test is used to test the homogeneity of variance assumption in statistical analysis?
What test is used to test the homogeneity of variance assumption in statistical analysis?
What is a general limitation of transformations in statistical analysis?
What is a general limitation of transformations in statistical analysis?
What is the main purpose of using transformations in statistical analysis?
What is the main purpose of using transformations in statistical analysis?
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What is a limitation of using transformations in statistical analysis?
What is a limitation of using transformations in statistical analysis?
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Which statistical test is commonly used to measure the strength and direction of the linear relationship between two continuous/scale variables?
Which statistical test is commonly used to measure the strength and direction of the linear relationship between two continuous/scale variables?
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Which aspect of a relationship does Pearson's correlation measure?
Which aspect of a relationship does Pearson's correlation measure?
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What type of variables can Pearson's correlation be used to measure the relationship between?
What type of variables can Pearson's correlation be used to measure the relationship between?
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What does statistical significance assess in the context of Pearson's correlation?
What does statistical significance assess in the context of Pearson's correlation?
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What research question can Pearson's correlation help answer?
What research question can Pearson's correlation help answer?
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Study Notes
Transformations in Statistical Analysis
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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.
