data analytics practice test 7/8
refers to the scenario in which the relationship
interaction
A time series that shows a recurring pattern over one year or less is said to follow a _____.
seasonal pattern
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
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
The graph of the simple linear regression equation is a(n) _____.
straight line
The _____ is a measure of the error that results from using the estimated regression equation to predict the values of the dependent variable in the sample
sum of squares due to error (SSE)
When the mean value of the dependent variable is independent of variation in the independent variable, the slope of the regression line is _____.
zero
A time series plot of a period of time (quarterly) versus quarterly sales (in $1,000s) is shown below. Which of the following data patterns best describes the scenario shown?
Seasonal pattern and linear trend
Which of the following states the objective of time series analysis?
To uncover a pattern in a time series and then extrapolate the pattern into the future
_____ is the data set used to build the candidate models.
Training set
______ refers to the data set used to compare model forecasts and ultimately pick a model for predicting values of the dependent
Validation set
Prediction of the mean value of the dependent variable y for values of the independent variables x1, x2, . . . , xq that are outside the experimental range is called _____.
extrapolation
Prediction of the value of the dependent variable outside the experimental region is called ___.
extrapolation
The process of making a conjecture about the value of a population parameter, collecting sample data that can be used to assess this conjecture, measuring the strength of the evidence against the conjecture that is provided by the sample, and using these results to draw a conclusion about the conjecture is known as _____.
hypothesis testing
The process of _____ might be used to determine the value of the smoothing constant that minimizes the mean squared error
nonlinear optimization
In the moving averages method, the order k determines the _____.
number of time series values under consideration
Fitting a model too closely to sample data, resulting in a model that does not accurately reflect the population is termed as _____.
overfitting
A _____ is used to visualize sample data graphically and to draw preliminary conclusions about the possible relationship between the variables.
scatter chart
For causal modeling, _____ are used to detect linear or nonlinear relationships between the independent and dependent variables
scatter charts
A regression analysis involving one independent variable and one dependent variable is referred to as a _____.
simple linear regression
In a simple linear regression model, y = ß0 + ß1x + ε the parameter ß1 represents the _____.
slope of the true regression line
The least squares regression line minimizes the sum of the _____
squared differences between actual and predicted y values
A procedure for using sample data to find the estimated regression equation is _____.
the least squares method
Trend refers to _____.
the long-run shift or movement in the time series observable over several periods of time
The exponential smoothing forecast for period t + 1 is a weighted average of the _____.
actual value in period t with weight α and the forecast for period t with weight 1 - α
In a linear regression model, the variable that is being predicted or explained is known as _____. It is denoted by y and is often referred to as the response variable.
dependent variable
The mean absolute error, mean squared error, and mean absolute percentage error are all methods to measure the accuracy of a forecast. These methods measure forecast accuracy by _____.
determining how well a particular forecasting method is able to reproduce the time series data that are already available
A time series with a seasonal pattern can be modeled by treating the season as a _____.
dummy variable
A variable used to model the effect of categorical independent variables in a regression model is known as a _____.
dummy variable
0In 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
. _____ 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
A time series plot of a period of time (in weeks) versus sales (in 1,000's of gallons) is shown below. Which of the following data patterns best describes the scenario shown?
Time series with a horizontal pattern
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 moving averages and exponential smoothing methods are appropriate for a time series exhibiting _____.
a horizontal pattern
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
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
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 prespecified value of the independent variable at which its relationship with the dependent variable changes in a piecewise linear regression model is referred to as the ______.
knot
A _____ is an interval estimate of an individual y value, given values of the independent variables
prediction interval
If a time series plot exhibits a horizontal pattern, then _____.
there is still not enough evidence to conclude that the time series is stationary
A positive forecast error indicates that the forecasting method _____ the dependent variable.
underestimated
_____ uses a weighted average of past time series values as the forecast.
Exponential smoothing
_____ is the amount by which the predicted value differs from the observed value of the time series variable
Forecast error
_____ refers to the use of sample data to calculate a range of values that is believed to include the value of the population
Interval estimation
_____ refers to the degree of correlation among independent variables in a regression model
Multicollinearity
A time series plot of a period of time (in years) versus revenue (in millions of dollars) is shown below. Which of the following data patterns best describes the scenario shown?
Nonlinear trend pattern
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
_____ is a statistical procedure used to develop an equation showing how two variables are related.
Regression analysis
A normally distributed error term with a mean of zero would _____.
allow more accurate modeling
A causal model provides evidence of _____between an independent variable and the variable to be forecast
an association
The difference between the observed value of the dependent variable and the value predicted using the estimated regression equation is known as the _____.
residual
The degree of correlation among independent variables in a regression model is called _____.
multicollinearity
Regression analysis involving one dependent variable and more than one independent variable is known as ____
multiple regression
A forecast is defined as a(n) ______.
prediction of future values of a time series
In the graph of the simple linear regression equation, the parameter ß0 represents the _____ of the true regression line
y-intercept