Quiz 1
The strength of a linear relationship in simple linear regression does not change if the units of data are converted True or False
True
A certain point on a residual plot has been determined as a significant outlier and was found to have been incorrectly recorded. This incorrect recording cannot be rectified and, therefore, the outlier data point should be removed from the dataset. a. True b. False
a
Correlation is a measure of the degree of linear relationship between two variables. a. True b. False
a
For a given data sample, the difference between the actual y value and the y value predicted by the regression model (the error of the regression model in predicting each value of the dependent variable) is called: a. residual b. homoscedasticity c. scatter plot d. error term
a
A consultant develops a simple regression equation to predict sales (in millions of dollars) by year: y-hat = -4,865.81 + 3.07(Year), where Year is the x-variable. The model predicts that sales in 2010, as compared to sales in 2005, will be: a. 12.28 million lower b. 15.35 million higher c. 18.42 million higher d. 18.42 million lower
b
For the Pearson's product-moment correlation coefficient, a perfect negative relationship is denoted by a correlation of: a. -100.0 b. -1 c. -0.1 d. -0.01
b
Heteroscedasticity is the condition that occurs when the error variances produced by a regression model are constant. a. True b. False
b
Mathematical simple linear regression models that produce an "exact" output for a given input are called: a. probabilistic models b. deterministic models c. regression models d. correlation models
b
When carrying out a simple linear regression analysis, if the residuals from the regression equation are correlated with their preceding values then the independence assumption for simple linear regression has been met. a. True b. False
b
Which of the following is not an assumption for simple linear regression: a. X-variable values are random or pre-determined b. Y-variable values are random c. Residual values are random d. Error term values are random
b
Which of the following statements indicate a situation in which 2 variables may not be appropriate for simple linear regression? a) Their scatterplot shows a linear relationship b) Their scatterplot shows a curved relationship c) Their scatterplot shows that they have similar range d) Their scatterplot shows points tightly clustered on a line
b
Another name for bivariate, linear regression is: a. correlation b. multiple regression c. simple regression d. time series regression
c
Data points that lie apart from the rest of the points are called: a. residuals b. error terms c. outliers d. standard deviations
c
For the regression equation: y = 2.45 - 1.62(x), if x = 2, what is the value of y? a. 5.69 b. -3.24 c. -0.79 d. 0.83
c
In regression analysis, a residual is calculated as: a. 2(y - y-hat) b. 2(y-hat - y) c. y - y-hat d. y-hat - y
c
Which of the following statements is true concerning the y intercept in the equation of the regression line? a. The x indicates the y intercept b. The y indicates the y intercept c. b0 indicates the y intercept. d. b1 indicates the y intercept.
c
A computer analysis produces a correlation coefficient of 0.45 between 2 variables. This can be described as a: a. moderate negative relationship b. weak negative relationship c. strong positive relationship d. moderate positive relationship
d
A consultant develops a simple regression equation to predict sales (in millions of dollars) by year: y-hat = -4,865.81 + 3.07(Year), where Year is the x-variable. The expected sales for 2008 are: a. $9,770,546.48 million b. 11,030.37 million c. 6,164.56 million d. $1,298.75 million
d
A type of graph in which the residuals for a particular regression model are plotted along with their associated values of x. a. simple regression b. deterministic model c. probabilistic model d. residual plot
d
Which of the following is true of bivariate regression? a. An equation may include multiple dependent variables, but only one independent variable. b. An equation may include multiple independent variables, but only one dependent variable. c. The variable to be predicted is called the independent variable. d. The variable to be predicted is called the dependent variable.
d
