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Qualified Medicare Beneficiary (QMB) 3200 Final Exam A with All Questions and 100% Correct Answers
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Qualified Medicare Beneficiary (QMB) 3200 Final Exam with All Questions and 100% Correct Answers
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Name: Score:73 Multiple choice questions
Term 1 of 73
To test for the significance of a regression model involving 14 independent variables and 255
observations, the numerator and denominator degrees of freedom (respectively) for the
critical value of F are
14 and 240
14 and 241
14 and 255
255 and 14
Term 2 of 73
The following model y= Bo+ B1x1+e is referred to as a
simple first-order model with one predictor variable
complex second-order model with two predictor variables
time series model with autoregressive components
multiple regression model with interaction terms
Term 3 of 73
horizontal pattern
a pattern where data points are clustered together
exists when the data fluctuate randomly around a constant mean over time
a pattern that has a cyclical trend
a pattern that shows consistent increase over time
,Term 4 of 73
Mean Absolute Error (MAE)
the average of the forecasted values
a measure of the variability of the forecast errors
the difference between actual and forecasted values
the average of the absolute values of the forecast errors
Term 5 of 73
Excel's __________ function can be used to calculate a p-value for a hypothesis test.
NORM.S.DIST
T.test
Max
Average
Term 6 of 73
Mean Squared Error (MSE)
the average of squared forecast errors
the standard error of the mean
the average of the absolute values of the forecast errors
the standard error of the population
Term 7 of 73
correlation coefficient
estimates the median value of a dataset
determines the probability of an event occurring
measures the strength of linear relationship between variables
calculates the average of two variables
,Term 8 of 73
The value of the sample statistic is used to estimate
the average of squared forecast errors
the value of the population parameter
the standard error of the mean
coefficient of determination
Term 9 of 73
Standard error of the mean decreases
as sample size increases
as the population increases
as variability in x decreases.
decreases
Term 10 of 73
Common types of data patterns that can be identified when examining a time series plot
include all of the following EXCEPT
vertical
negative
horizontal
cyclical pattern
Term 11 of 73
The standard deviation of p̄ is referred to as
the standard error of the mean
the standard error of the population
the sample mean
the average of the absolute values of the forecast errors
, Term 12 of 73
Symbol representing the size of sample
x̄
standard deviation of the sampling distribution of x̄ 1 - x̄ 2
normal
n
Term 13 of 73
Seasonal pattern
refers to the overall magnitude of a time series
indicates randomness in time series data
describes the trend in a time series data
exists if the time series plot exhibits a repeating pattern over successive periods
Term 14 of 73
coefficient of determination
standard deviation of the population
measures the strength of linear relationship between variables
the average of the absolute values of the forecast errors
measures goodness of fit how much of y is explained by x
Term 15 of 73
As the goodness of fit for the estimated multiple regression equation increases
the number of predictors decreases
the residuals become larger
the value of the multiple coefficient of determination increases
the intercept term becomes insignificant
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