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Questions and Answers
What type of research design is used in 'Correlation'?
What type of research design is used in 'Correlation'?
Correlational Research Designs
What is the main focus of the research design 'Correlation'?
What is the main focus of the research design 'Correlation'?
To explore and analyze the relationship between two or more variables.
What is the alternative phrase for 'Variable X'?
What is the alternative phrase for 'Variable X'?
Predictor Variable
Correlation research designs can infer causation.
Correlation research designs can infer causation.
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Which of the following is NOT a valid term for use in correlation research?
Which of the following is NOT a valid term for use in correlation research?
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A perfect positive correlation is represented by r calc = +1.
A perfect positive correlation is represented by r calc = +1.
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A 'r calc' value of 0 indicates a strong negative correlation.
A 'r calc' value of 0 indicates a strong negative correlation.
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'Pearson's r' is used for analyzing quantitative dependent variables including interval and ratio.
'Pearson's r' is used for analyzing quantitative dependent variables including interval and ratio.
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Spearman Rank Order Correlation Coefficient is used for analyzing quantitative dependent variables.
Spearman Rank Order Correlation Coefficient is used for analyzing quantitative dependent variables.
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What type of research design is 'Simple Linear Regression'?
What type of research design is 'Simple Linear Regression'?
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What is the goal of Simple Linear Regression?
What is the goal of Simple Linear Regression?
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Study Notes
Correlation
- Correlational research designs explore relationships between variables.
- Correlation does not imply causation. There is no cause-and-effect relationship between variables.
- To explore the correlation between variables, graphs are often used (e.g. scatterplots).
- Scatterplots show the relationship between variables X and Y and their direction
Types of Correlation
- Positive Correlation: As one variable increases, the other variable tends to increase. Example: Increased hours of study may correlate with improvement in exam scores.
- Negative Correlation: As one variable increases, the other variable tends to decrease. Example: Increased time spent playing video games may correlate with decreased time spent on homework.
- No Correlation: No apparent relationship between variables. Example: No relationship between shoe size and intelligence.
Variables
- Variable X: One of the variables being examined for a relationship.
- Variable Y: Another variable being examined for a relationship.
- Variable Z (example): A third variable that might influence the relationship between X and Y. The relationship between X and Y could be correlated to Variable Z rather than to each other,
Statistical Assessments
- Pearson's r: A measure of the strength and direction of a linear relationship between two quantitative variables (interval or ratio).
- Spearman Rank Order Correlation Coefficient: A measure of the strength and direction of a relationship between two ordinal variables.
Simple Linear Regression
- Predicting values of a dependent variable based on a single predictor variable.
- The linear regression formula allows the researcher to determine a relationship that can be used for prediction.
- Example: predicting a student's final exam score, given the student's score from mid-term exam.
- Use a predictor variable (X) to predict a dependent variable (Y).
Data Visualization
- Scatterplots are used to visualize the relationship between two variables. The plot shows the data points as individual dots. The line connecting most data points illustrates the correlation.
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Description
This quiz explores the concept of correlation in research designs, including the types of correlation such as positive, negative, and no correlation. It emphasizes that correlation does not imply causation and illustrates how scatterplots can be used to visualize relationships between variables. Test your understanding of these fundamental concepts!
