stat #2 multiple choice

one dependent and one or more independent variables are related

Regression analysis is a statistical procedure for developing a mathematical equation that describes how

a. $66,000

Regression analysis was applied between sales data (in $1000s) and advertising data (in $100s), and the following information was obtained.ŷ = 12 + 1.8x n = 17SSR = 225SSE = 75Sb1 = 0.2683Refer to Exhibit 14-3. Based on the above estimated regression equation, if advertising is $3,000, then the point estimate for sales (in dollars) is _____. a. $66,000 b. $5,412 c. $66 d. $17,400

a residual

The difference between the observed value of the dependent variable and the value predicted by using the estimated regression equation is called

the regression model

The equation that describes how the dependent variable (y) is related to the independent variable (x) is called

.625

The following information regarding a dependent variable (y) and an independent variable (x) is provided. xy2413443658 SSE = 6 SST = 16 Refer to Exhibit 14-4. The coefficient of determination is _____. a. .625 b. .7096 c. -.7906 d. .375

min Σ(yi - ŷi)2

The least squares criterion is

can be larger or smaller than the coefficient of correlation

The numerical value of the coefficient of determination

residual analysis

The primary tool or measure for determining whether the assumed regression model is appropriate is

coefficient of determination

The proportion of the variation in the dependent variable y that is explained by the estimated regression equation is measured by the

standard deviation

The standardized residual is provided by dividing each residual by its

influential observation

An observation that has a strong effect on the regression results is called a(n)

outlier

A data point (observation) that does not fit the trend shown by the remaining data is called a(n)

the least squares method

A procedure used for finding the equation of a straight line that provides the best approximation for the relationship between the independent and dependent variables is

influential

Data points having high leverage are often

is 16%

If the coefficient of correlation is .4, the percentage of variation in the dependent variable explained by the estimated regression equation

d. None of these answers are correct.

If there is a very strong correlation between two variables, then the coefficient of correlation must be a. much larger than 1, if the correlation is positive b. much smaller than 1, if the correlation is negative c. either much larger than 1 or much smaller than 1 d. None of these answers are correct.

.600

In a regression analysis, if SSE = 200 and SSR = 300, then the coefficient of determination is

is the independent variable

In a regression analysis, the variable that is used to predict the dependent variable

d. None of these answers are correct.

In a simple regression analysis (where y is a dependent and x an independent variable), if the y-intercept is positive, then it must be true that a. there is a positive correlation between x and y b. there is a negative correlation between x and y c. if x is increased, y must also increase d. None of these answers are correct.

x-axis of a scatter diagram

In regression analysis, the independent variable is typically plotted on the

coefficient of determination can be computed

In regression and correlation analysis, if SSE and SST are known, then with this information the

coefficient of determination

In simple linear regression, r2 is the

less than 1

It is possible for the coefficient of determination to be