# Unit 3 - BUSINESS STATISTICS- BBA 2nd Sem

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Question 1: What does the Karl Pearson Coefficient of Correlation measure?

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Answer - A

Description: The Karl Pearson Coefficient of Correlation measures the strength and direction of a linear relationship between two variables.

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Question 2: In correlation, if the coefficient is -0.90, what does it indicate?

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Answer - B

Description: A coefficient of -0.90 indicates a strong negative correlation, suggesting that as one variable increases, the other decreases.

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Question 3: Which type of correlation is suitable for categorical data?

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Answer - C

Description: Point-biserial correlation is appropriate for assessing the correlation between a continuous variable and a dichotomous (categorical) variable.

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Question 4: What does a correlation coefficient of 0.15 signify?

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Answer - B

Description: A correlation coefficient of 0.15 indicates a weak positive correlation.

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Question 5: In a scatter diagram, points clustered closely around a line indicate:

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Answer - A

Description: Points clustered closely around a line in a scatter diagram suggest a strong correlation between the variables.

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Question 6: What is the primary purpose of the scatter diagram method in correlation analysis?

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Answer - B

Description: The scatter diagram method is used to provide a visual representation of the relationship between two variables.

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Question 7: Which of the following is an example of a non-parametric correlation coefficient?

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Answer - B

Description: Spearmans rank correlation coefficient is a non-parametric measure of correlation.

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Question 8: When is the correlation considered statistically significant?

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Answer - C

Description: Correlation is considered statistically significant when the p-value is less than the chosen significance level.

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Question 9: Which type of correlation coefficient can be used when the variables are measured on an ordinal scale?

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Answer - B

Description: Spearmans rank correlation coefficient is suitable for variables measured on an ordinal scale.

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Question 10: What does a correlation coefficient of +1 indicate?

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Answer - A

Description: A correlation coefficient of +1 indicates a perfect positive correlation, meaning the variables move together in a straight line.

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Question 11: In regression analysis, what is the dependent variable?

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Answer - C

Description: The dependent variable is also known as the response variable, representing the outcome or variable being predicted.

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Question 12: What is the primary goal of regression analysis?

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Answer - B

Description: The primary goal of regression analysis is to predict the values of the dependent variable based on the values of one or more independent variables.

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Question 13: Which of the following is not a type of regression analysis?

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Answer - D

Description: Quadratic regression is not a type of regression analysis discussed in the context of linear relationships.

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Question 14: What does the slope of the regression line represent?

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Answer - B

Description: The slope of the regression line represents the change in the dependent variable for a one-unit change in the independent variable.

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Question 15: Which regression coefficient represents the point where the regression line intersects the y-axis?

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Answer - A

Description: The intercept is the regression coefficient that represents the point where the regression line intersects the y-axis.

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Question 16: What is the purpose of the residual in regression analysis?

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Answer - B

Description: The residual in regression analysis represents the difference between the observed and predicted values of the dependent variable.

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Question 17: In multiple regression, how many independent variables are considered simultaneously?

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Answer - C

Description: Multiple regression considers three or more independent variables simultaneously to predict the dependent variable.

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Question 18: What is the purpose of the coefficient of determination (R-squared) in regression analysis?

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Answer - C

Description: The coefficient of determination (R-squared) assesses how well the regression model fits the observed data.

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Question 19: Which of the following is a potential issue in regression analysis?

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Answer - D

Description: Multicollinearity, homoscedasticity, and normality of residuals are all potential issues in regression analysis that can affect the reliability of the results.

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