Correlation and Regression Review

What is a correlation coefficient?

• The correlation coefficient is a statistical measure that measures the strength and direction of the linear relationship between two variables.

• The correlation coefficient is a measure of the probability of a relationship between two variables.

• The correlation coefficient is a measure of the difference between two variables.

• The correlation coefficient is a measure of the spread of data points around the mean.

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What does a correlation coefficient of 0 indicate?

• Perfect positive linear relationship

• No linear relationship

• Perfect negative linear relationship

• Weak positive linear relationship

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What is linear regression?

• A method used to calculate the mean of a dataset.

• A machine learning algorithm used to classify data into different categories.

• A technique used to analyze time series data.

• A statistical method used to model the relationship between a dependent variable and one or more independent variables.

What is a scatter plot?

• A scatter plot is a type of plot that is used to display categorical data.

• A scatter plot is a type of plot that uses polar coordinates instead of Cartesian coordinates.

• A scatter plot is a type of plot or mathematical diagram using Cartesian coordinates to display values for typically two variables for a set of data points.

• A scatter plot is a type of plot that displays values for only one variable.

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You want to determine if there is an association between the number of years of work experience and the salary of employees in a company. What is the appropriate statistical test to use?

• Correlation Analysis

• Regression Analysis

• Independent Samples t-Test

• Paired Samples t-Test

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The correlation coefficient (r) between the number of hours spent studying and exam scores for a group of students is 0.75. What is the coefficient of determination (r-squared)?

• 0.75

• 1.5

• 0.56

• 0.65

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You have been provided with a dataset containing information about the average temperature (in degrees Celsius) and the daily ice cream sales (in dollars) for a local ice cream parlor over the past year. Your task is to determine the relationship between temperature and ice cream sales. Using correlation and regression analysis, which of the following statements is most likely to be true?

• There is a positive correlation between temperature and ice cream sales, suggesting that as temperature increases, ice cream sales also increase.

• There is a negative correlation between temperature and ice cream sales, indicating that as temperature rises, ice cream sales decrease.

• There is no correlation between temperature and ice cream sales, meaning that temperature does not have a significant impact on ice cream sales.

• The data is inconclusive, and no meaningful correlation can be determined between temperature and ice cream sales.

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You are examining the correlation between the hours of exercise per week and a person's body weight. After calculating the correlation coefficient, you find a value of 0.25. What does this correlation coefficient suggest?

• There is a strong positive correlation between exercise hours and body weight, indicating that more exercise leads to higher body weight.

• There is a strong negative correlation between exercise hours and body weight, suggesting that more exercise results in lower body weight.

• There is a weak positive correlation between exercise hours and body weight, but the relationship is not very strong.

• There is no correlation between exercise hours and body weight.

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You are given the slope (m) of a linear regression model as 2.5 and the y-intercept (b) as 10. What is the equation of the regression line?

• y = 2.5x

• y = 10 + 2.5x

• y = 2.5 + 10x

• y = 10 - 2.5x

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In a linear regression model for the cost of a product in Philippine Pesos (PHP), the equation is given as: Cost(PHP) = 1000 + 10(Quantity). If the cost of a product is 4,000 php, how many items were purchased (Quantity)?

• 300 items

• 400 items

• 500 items

• 600 items

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