Psych stats correlation vs regression exam review
Review key concepts of correlation and regression in psychology statistics through practical examples and questions to enhance understanding before exams.
Quiz(32 questions)
1. What does the regression analysis output typically include?
Terms in this Study Set(32)
Correlation Basics(16)
What is correlation?
Correlation measures the strength and direction of the relationship between two variables. For example, as the temperature in Fahrenheit increases, ice cream sales often increase.
Types of correlation?
- Positive - Negative - Zero Examples: Positive = height and weight; Negative = miles driven and gas left.
True or False: Correlation implies causation.
False. Correlation does not indicate that one variable causes the other. For example, ice cream sales rise with temperature but do not cause it.
Fill in the blank: A _____ correlation means as one variable increases, the other decreases.
Negative. Example: As the price of gas increases, driving distance may decrease.
What is a correlation coefficient?
A correlation coefficient, often denoted as 'r', quantifies the degree of correlation between variables. Ranges from -1 to 1.
Example of positive correlation.
Height and weight. As height increases, weight tends to increase, suggesting a positive relationship.
What does an r value of 0 indicate?
An r value of 0 indicates no correlation between the two variables. Example: No relationship between shoe size and intelligence.
Comparison: Positive vs Negative correlation.
Positive: Both variables move in the same direction (e.g., study hours and test scores). Negative: Variables move in opposite directions (e.g., exercise frequency and weight).
What does a perfect positive correlation look like?
An r value of 1. Example: If every time you save 100.
Cause → Effect: More study hours → ?
Higher test scores. This shows a positive correlation in educational settings.
How can correlation be used in business?
To analyze customer behavior, such as the relationship between advertising spend and sales revenue. Higher spending may lead to higher sales.
What is a scatter plot?
A scatter plot visually represents the relationship between two variables, showing how one variable may affect another. Points represent data pairs.
True or False: A correlation of -0.8 is stronger than 0.5.
True. A correlation of -0.8 indicates a stronger negative relationship than 0.5 indicates a positive relationship.
Example of zero correlation.
The relationship between a person's shoe size and their score on a math test. No link between the two.
What does a correlation matrix show?
A correlation matrix displays the pairwise correlations between multiple variables, useful for identifying relationships in a dataset.
Correlation in health studies: Example?
Researchers may find a correlation between exercise frequency and cholesterol levels, indicating exercise may relate to heart health.
Regression Analysis(16)
What does regression analysis do?
It predicts the value of a dependent variable based on one or more independent variables.
True or False: Regression can only use one independent variable.
False - Multiple regression uses several independent variables to predict the outcome.
Identify the dependent variable: Rent as a function of location and size.
Rent is the dependent variable; it changes based on location and size.
What is a regression line?
A line that best fits the data points in a scatter plot, representing the relationship between variables.
Explain the term 'slope' in regression.
The slope indicates how much the dependent variable changes for each unit change in the independent variable.
Fill in the blank: In regression, R² shows the __________ of variance explained.
proportion - It indicates how well the independent variables explain the variability of the dependent variable.
Cause → Effect: Increase in advertising budget leads to __________.
higher sales - Typically, a larger budget results in increased consumer awareness and purchases.
How do you interpret a negative slope?
It indicates an inverse relationship: as the independent variable increases, the dependent variable decreases.
What is the purpose of a residual plot?
To assess the fit of a regression model; it shows the difference between observed and predicted values.
True or False: Outliers can significantly affect regression results.
True - Outliers can skew results and affect the slope and intercept of the regression line.
Give an example of predicted vs actual using regression.
Predicted: 1800. Residual: $200.
Compare linear vs. multiple regression.
Linear regression uses one predictor; multiple regression incorporates two or more predictors.
What does multicollinearity mean?
It refers to high correlations between independent variables, making it difficult to determine their individual effects.
Identify the independent variables: Sales predicted from price and promotion.
Price and promotion are the independent variables; they influence sales.
What is the significance of the intercept in regression?
It represents the expected value of the dependent variable when all independent variables are zero.
Fill in the blank: A high R² value indicates __________.
a good fit - It suggests that the model explains a significant amount of variation in the data.
Questions in this Study Set(32)
1. What does the regression analysis output typically include?
2. What does a correlation of 0.85 suggest?
3. In a simple linear regression, if the slope is 3, what does this indicate?
4. Which of the following describes a negative correlation?
5. True or False: The intercept in a regression model represents the value of the dependent variable when all independent variables are zero.
6. Which variable pair likely exhibits zero correlation?
7. In a regression model predicting salary based on years of experience, which variable is dependent?
8. What does an r value of -0.5 indicate?
9. What does R² measure in a regression analysis?
10. Which of the following is NOT a type of correlation?
11. Which of the following statements is true regarding residuals?
12. Which scenario illustrates a perfect positive correlation?
13. What does it mean if a residual plot shows a random distribution of points?
14. If the correlation coefficient is -1, what does it suggest?
15. Which of the following is NOT a type of regression analysis?
16. How can correlation be misleading?
17. If a regression equation is Y = 50 + 2X, what is the predicted value of Y when X is 10?
18. In which situation would you expect a positive correlation?
19. What is multicollinearity in regression analysis?
20. Which correlation indicates the strongest relationship?
21. If the p-value associated with a coefficient is less than 0.05, what does this imply?
22. What is the main purpose of a scatter plot?
23. In multiple regression, what does it mean if one variable has a low p-value while others have high p-values?
24. What would an r value of 0.1 suggest about the variables?
25. What is the purpose of stepwise regression?
26. Which variable pair might show a negative correlation?
27. What does the term 'overfitting' mean in the context of regression?
28. What does a correlation matrix help researchers do?
29. Which of the following best describes the purpose of regression analysis?
30. True or False: Correlation does imply causation.
31. In a regression model, which statement about the independent variable is true?
32. Which of the following is an example of a positive correlation?
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