Section B Quiz 1 Advance Machine Learning

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  • 1/10 Questions

    The straight line graph of the linear equation Y = a + bX, slope will be downward If:

    • B = 0 
    • B < 0 
    • B > 0 
    • B ≠ 0
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About This Quiz

This advanced quiz in Machine Learning covers key concepts of regression, including linear regression, regression coefficients, and their implications in predictive modeling.

Section B Quiz 1 Advance Machine Learning - Quiz

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  • 2. 

    If the value of any regression coefficient is zero, then two variables are:

    • Qualitative 

    • Correlation

    •  Dependent 

    • Independent 

    Correct Answer
    A. Independent 
    Explanation
    If the value of any regression coefficient is zero, it indicates that there is no relationship or association between the independent variable and the dependent variable. In other words, the independent variable does not have any effect on the dependent variable. Therefore, the two variables are considered independent of each other.

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  • 3. 

    In simple regression equation, the numbers of variables involved are:

    • 0

    • 1

    • 2

    • 3

    Correct Answer
    A. 2
    Explanation
    In a simple regression equation, there are two variables involved: one independent variable and one dependent variable. The independent variable is used to predict or explain the changes in the dependent variable. Therefore, the correct answer is 2.

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  • 4. 

    The straight line graph of the linear equation Y = a + bX, slope will be upward If:

    • B = 0 

    • B < 0 

    • B > 0 

    • B ≠ 0

    Correct Answer
    A. B > 0 
    Explanation
    The slope of a straight line graph represents the rate of change between the variables. In the equation Y = a + bX, the slope is represented by the coefficient b. If b > 0, it means that as X increases, Y also increases. This indicates a positive relationship between the variables, resulting in an upward slope on the graph.

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  • 5. 

    In simple linear regression, the numbers of unknown constants are:

    • One

    • Two

    • Three

    • Four 

    Correct Answer
    A. Two
    Explanation
    In simple linear regression, there are two unknown constants: the slope (represented by the letter "m") and the y-intercept (represented by the letter "b"). These constants are determined by fitting a straight line to a set of data points in order to model the relationship between a dependent variable (y) and an independent variable (x). The slope represents the rate of change of the dependent variable with respect to the independent variable, while the y-intercept represents the value of the dependent variable when the independent variable is zero.

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  • 6. 

    The slope of the regression line of Y on X is also called the:

    • Correlation coefficient of X on Y

    • Correlation coefficient of Y on X

    • Regression coefficient of X on Y 

    • Regression coefficient of Y on X

    Correct Answer
    A. Regression coefficient of Y on X
    Explanation
    The slope of the regression line of Y on X represents the change in the dependent variable Y for a unit change in the independent variable X. Therefore, it is the regression coefficient of Y on X.

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  • 7. 

    In simple linear regression model Y = α + βX + ε where α and β are called:

    • Estimates

    • Parameters

    • Random errors

    • Variables

    Correct Answer
    A. Parameters
    Explanation
    In a simple linear regression model, the variables Y and X represent the dependent and independent variables, respectively. The parameters α and β are the coefficients that determine the intercept and slope of the regression line, respectively. These parameters are estimated from the data and represent the true population values. Therefore, the correct answer is "Parameters".

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  • 8. 

    The purpose of simple linear regression analysis is to:

    • Predict one variable from another variable

    • Replace points on a scatter diagram by a straight-line

    • Measure the degree to which two variables are linearly associated

    • Obtain the expected value of the independent random variable for a given value of the dependent variable 

    Correct Answer
    A. Predict one variable from another variable
    Explanation
    Simple linear regression analysis is a statistical method used to predict or estimate the value of one variable based on the value of another variable. It involves fitting a straight line to a scatter diagram of the data points, with the goal of understanding the linear relationship between the two variables. By using this analysis, we can make predictions about the value of the dependent variable based on the known value of the independent variable. Therefore, the purpose of simple linear regression analysis is to predict one variable from another variable.

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  • 9. 

    Regression coefficient is independent of:

    •  Units of measurement 

    •  Scale and origin

    • Both (a) and (b) 

    • None of them

    Correct Answer
    A. Both (a) and (b) 
    Explanation
    The regression coefficient is a measure of the relationship between the independent variable and the dependent variable in a regression analysis. It represents the change in the dependent variable for a one-unit change in the independent variable. The coefficient is independent of the units of measurement because it is a standardized measure that takes into account the scale and origin of the variables. Therefore, the correct answer is both (a) and (b) - the regression coefficient is independent of both the units of measurement and the scale and origin of the variables.

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  • 10. 

    If the points on the scatter diagram indicate that as one variable increases the other variable tends to decrease the value of r will be:

    • Perfect positive

    • Perfect negative

    • Negative

    • Zero

    Correct Answer
    A. Negative
    Explanation
    If the points on the scatter diagram indicate that as one variable increases, the other variable tends to decrease, the value of r will be negative. This is because a negative correlation exists between the two variables, meaning that as one variable increases, the other variable decreases. The correlation coefficient, r, measures the strength and direction of the linear relationship between the variables. In this case, the negative correlation indicates that as one variable increases, the other variable tends to decrease, resulting in a negative value for r.

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  • Current Version
  • Mar 15, 2023
    Quiz Edited by
    ProProfs Editorial Team
  • Aug 27, 2018
    Quiz Created by
    Shivanig18
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