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Test: Correlation and Regression - SSC CGL MCQ


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15 Questions MCQ Test Statistics for SSC CGL - Test: Correlation and Regression

Test: Correlation and Regression for SSC CGL 2024 is part of Statistics for SSC CGL preparation. The Test: Correlation and Regression questions and answers have been prepared according to the SSC CGL exam syllabus.The Test: Correlation and Regression MCQs are made for SSC CGL 2024 Exam. Find important definitions, questions, notes, meanings, examples, exercises, MCQs and online tests for Test: Correlation and Regression below.
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Test: Correlation and Regression - Question 1

Which one of the following statements about the correlation coefficient is correct?

Detailed Solution for Test: Correlation and Regression - Question 1
The correlation coefficient is indeed unaffected by the change of origin (translation). It measures the linear relationship between two variables and is independent of the units or scales in which the variables are measured. However, it's important to note that it is affected by changes of scale (multiplication).
Test: Correlation and Regression - Question 2

Choose the correct option concerning the correlation analysis between 2 sets of data.

Detailed Solution for Test: Correlation and Regression - Question 2
A "simple correlation" is indeed a correlational analysis comparing two sets of data. It measures the degree of linear association between two variables.
Test: Correlation and Regression - Question 3

The slope of the regression line of Y on X is also referred to as the:

Detailed Solution for Test: Correlation and Regression - Question 3
The slope of the regression line of Y on X is often referred to as the "Regression coefficient of Y on X." It represents the change in the dependent variable Y for a one-unit change in the independent variable X.
Test: Correlation and Regression - Question 4
Which of the assertions below is the least accurate?
Detailed Solution for Test: Correlation and Regression - Question 4
Option A is the least accurate. When outliers are present in the data series, correlation can be less reliable as it can be strongly influenced by outliers, leading to misleading interpretations. Correlation measures linear relationships and is sensitive to extreme values.
Test: Correlation and Regression - Question 5
Choose the least likely assumption of a classic normal linear regression model?
Detailed Solution for Test: Correlation and Regression - Question 5
Option B is the least likely assumption. In a classic normal linear regression model, there is no requirement for the independent variable to be normally distributed. The normality assumption typically pertains to the residuals (errors) in the model.
Test: Correlation and Regression - Question 6
Which one of the below statements regarding the regression line is correct?
Detailed Solution for Test: Correlation and Regression - Question 6
Option D is correct. All of the statements are correct. A regression line is also known as the "line of the average relationship," and it is used for prediction and estimation.
Test: Correlation and Regression - Question 7
The correlation coefficient is?
Detailed Solution for Test: Correlation and Regression - Question 7
The correlation coefficient is the square root of the coefficient of determination (r-squared). It provides a measure of the strength and direction of the linear relationship between two variables.
Test: Correlation and Regression - Question 8
The correlation for the values of two variables moving in the same direction is:
Detailed Solution for Test: Correlation and Regression - Question 8
When the values of two variables move in the same direction, there is a positive correlation between them. This means that as one variable increases, the other also tends to increase, resulting in a positive relationship.
Test: Correlation and Regression - Question 9
Who suggested the mathematical approach for determining the magnitude of a linear relationship between two variables, such as X and Y?
Detailed Solution for Test: Correlation and Regression - Question 9
Karl Pearson is credited with suggesting the mathematical approach for determining the magnitude of a linear relationship between two variables, including the calculation of correlation coefficients.
Test: Correlation and Regression - Question 10
Who introduced the term ‘regression’?
Detailed Solution for Test: Correlation and Regression - Question 10
Francis Galton introduced the term 'regression' in the context of regression analysis and linear regression models.
Test: Correlation and Regression - Question 11
The correlation coefficient describes:
Detailed Solution for Test: Correlation and Regression - Question 11
The correlation coefficient describes both the magnitude and direction of the linear relationship between two variables. It provides information about the strength and direction of the association.
Test: Correlation and Regression - Question 12
Which of the given statements concerning type two errors is correct?
Detailed Solution for Test: Correlation and Regression - Question 12
Option B is correct. Accepting an incorrect (false) hypothesis when it should have been rejected is referred to as a type two error in hypothesis testing. It is also known as a "false negative" error.
Test: Correlation and Regression - Question 13
Which of the given plots is suitable for testing the linear relationship between a dependent and independent variable?
Detailed Solution for Test: Correlation and Regression - Question 13
A scatter plot is suitable for testing the linear relationship between a dependent and independent variable. It allows you to visually examine the relationship between two variables and identify patterns, including linearity.
Test: Correlation and Regression - Question 14
Choose the method(s) that doesn’t have a closed-form solution for its coefficient?
Detailed Solution for Test: Correlation and Regression - Question 14
Lasso regression does not have a closed-form solution for its coefficients. It uses a regularization technique that can lead to some coefficients being exactly zero, which is why it lacks a closed-form solution.
Test: Correlation and Regression - Question 15
The correlation for the values of two variables moving in the opposite direction is:
Detailed Solution for Test: Correlation and Regression - Question 15
When the values of two variables move in the opposite direction, there is a negative correlation between them. This means that as one variable increases, the other tends to decrease, resulting in a negative relationship.
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