STATS 3331
The _____ is an indication of how frequently interval estimates based on samples of the same size taken from the same population using identical sampling techniques will contain the true value of the parameter we are estimating.
confidence level
The process of making estimates and drawing conclusions about one or more characteristics of a population through analysis of sample data drawn from the population is known as _____.
statistical inference
_____ refers to the use of sample data to calculate a range of values that is believed to include the value of the population parameter.
Interval estimation
_____ refers to the degree of correlation among independent variables in a regression model.
Multicollinearity
A _____ is used to visualize sample data graphically and to draw preliminary conclusions about the possible relationship between the variables.
scatter chart
A regression analysis involving one independent variable and one dependent variable is referred to as a _________.
simple linear regression
In the graph of the simple linear regression equation, the parameter ß1 is the __________ of the true regression line.
slope
In a simple linear regression analysis the quantity that gives the amount by which the dependent variable changes for a unit change in the independent variable is called the _____.
slope of the regression line
Prediction of the value of the dependent variable outside the experimental region is called _____.
extrapolation
A normally distributed error term with a mean of zero would _____.
allow more accurate modeling
In a linear regression model, the variable (or variables) used for predicting or explaining values of the response variable are known as the _____. It(they) is(are) denoted by x.
independent variable
A variable used to model the effect of categorical independent variables in a regression model is known as a _____.
dummy variable
_____ is used to test the hypothesis that the values of the regression parameters ß1, ß2, ... ßq are all zero.
An F test
The population parameters that describe the y-intercept and slope of the line relating y and x, respectively, are _____.
B0 and B1
Which of the following regression models is used to model a nonlinear relationship between the independent and dependent variables by including the independent variable and the square of the independent variable in the model?
Quadratic regression model
The scatter chart below displays the residuals versus the dependent variable, x. Which of the following conclusions can be drawn based upon this scatter chart? (diagram is a V)
The model fails to capture the relationship between the variables accurately.
The scatter chart below displays the residuals versus the dependent variable, x. Which of the following conclusions can be drawn from the scatter chart given below? (scatter diagram is a funnel with the wide end on the right)
The residuals have an increasing variance as the dependent variable increases.
_____ refers to the data set used to compare model forecasts and ultimately pick a model for predicting values of the dependent variable.
Validation set
A variable used to model the effect of categorical independent variables in a regression model which generally takes only the value zero or one is called _____.
a dummy variable
The _____ is a measure of the goodness of fit of the estimated regression equation. It can be interpreted as the proportion of the variability in the dependent variable y that is explained by the estimated regression equation.
coefficient of determination
Assessing the regression model on data other than the sample data that was used to generate the model is known as _____.
cross-validation
In the simple linear regression model, the _____ accounts for the variability in the dependent variable that cannot be explained by the linear relationship between the variables.
error term
The _____ is the range of values of the independent variables in the data used to estimate the regression model.
experimental region
The coefficient of determination _____.
is used to evaluate the goodness of fit
The degree of correlation among independent variables in a regression model is called _____.
multicollinearity