Statistique Et Méthodologie De La Recherche Test

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Statistique Et Méthodologie De La Recherche Test

 

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The measure of how well the regression line fits the data is the:

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If all the actual and estimated values of Y are same on the regression line, the sum of squares of error will be:

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A coefficient of correlation is computed to be -0.95 means that

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The signs of regression coefficients and correlation coefficient are always:

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1. The method of least squares dictates that we choose a regression line where the sum of the
square of deviations of the points from the lie is:

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The regression equation always passes through:

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To compare three independent means we use:

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When correlation coefficient is 1, all the points in a scatter diagram would lie?

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The degree of linear association between two metric scaled variables is measured by:

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

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In the regression equation y = bo + bx, bo is the

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The arithmetic mean of the two regression coefficients is greater than or equal to:

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R2 is used in regression analysis to:

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Two variables have a positive association when?

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The strength (degree) of the correlation between a set of independent variables X and a dependent variable Y is measured by

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The value we would predict for the dependent variable when the independent variables are all
equal to zero is called:

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Correlation analysis is used to:

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When regression line passes through the origin, then:

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When the p-value is greater than 0.05 we can conclude that:

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Let the coefficient of determination computed to be 0.39 in a problem involving one independent variable and one dependent variable. This result means that

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In scatter diagram, if most of the points lie in the first and third quadrants, then coefficient of correlation is:

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The correlation coefficient is used to determine:

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To investigate the association between two categorical variables we use:

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The coefficient of determination is the?

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2. A relationship where the flow of the data points is best represented by a curve is called:

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In regression analysis, the variable that is being predicted is the:

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Internal “validity” refers to:

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If the Pearson Correlation Coefficient shows zero value, it means that:

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51. What is the slope of the line y = -3.4x – 2.5?

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A scatterplot is a ?

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The term regression was used by:

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In regression analysis, the variable that is being predicted is

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

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Negative regression coefficient indicates that the movement of the variables are in:

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Correlation and regression are concerned with ?

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if the correlation coefficient r = 0.5 then the coefficient of determination is?

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In the regression equation Y = a + bX, b is called:

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When the two regression lines are parallel to each other, then their slopes are:

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Positive regression coefficient indicates that the movement of the variables are in:

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The null hypothesis states the means are:

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When there is no linear correlation between two variables, what will the value of r be?

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If both variables X and Y increase or decrease simultaneously, then the coefficient of correlation will be:

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When the p-value is less than 0.05 we can conclude that:

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In regression analysis, if the independent variable is measured in kilograms, the dependent
variable:

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A discrete variable is:

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If the coefficient of determination is 0.81, the correlation coefficient:

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An alternative to statistical techniques for analysis of data to find patterns and trends is?

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Which of the following statements is true?

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The predicted rate of response of the dependent variable to changes in the independent variable
is called:

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Computers are essential for quantitative data analysis because?

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

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If there is a very strong correlation between two variables then the correlation coefficient must
be:

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If two variables have a correlation coefficient of .30, what percentage of one variable is
accounted for by the other variable?

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A Type I error occurs when the null hypothesis is:

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What does it mean when you calculate a 95% confidence interval?

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In the regression equation Y = a+bX, the Y is called

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Inferential statistics enable you to (Except one):

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A perfect positive correlation is signified by:

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If the plotted points in a scatter diagram are evenly distributed, then the correlation is :

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The sum of the difference between the actual values of Y and its values obtained from the fitted regression line is always:

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