The general form of a probabilistic model is y = deterministic function + random
deviation
TRUE
The simple linear regression model is a deterministic model
FALSE
In the simple linear regression model, the randomness of e implies that y itself is
subject to uncertainty.
TRUE
In the simple linear regression model, (alpha) and (beta) are fixed numbers that are usually
unknown
TRUE
In the simple linear regression, the standard deviation of y is the same as the standard
deviation of the random deviation e.
TRUE
In the simple linear regression model, the point estimate and the point prediction are
identical for a particular value of x.
TRUE
. In the simple linear regression mode, e
depends on the value of x.
FALSE
The estimated standard deviation, se
, has n 1 degrees freedom
TRUE
The estimated standard deviation, se
, is roughly the magnitude of a typical deviation
from the least squares regression line.
TRUE
. The mean value of the statistic b is (beta)
TRUE
The expected change in the value of y for one unit change in x is
FALSE
The point estimate a + bx* is an unbiased statistic that can be used to estimate the
mean value of y when x = x*.
TRUE
The estimated mean value of y is a + bx
when x has the value x
.
TRUE
A standardized residual plot with spread increasing from left to right suggests that the
variance of y is not the same at each x value.
TRUE
A residual is a deviation from the population regression line.
FALSE
If on average y increases as x increases, the correlation coefficient is positive
TRUE
Pearson's correlation coefficient, r, does not depend on the units of measurement of
the two variables.
TRUE
The value of Pearson's r is always between 0 and 1.
FALSE
If r is close to 1, then the points lie close to a straight line with a positive slope.
TRUE
The slope of the least squares line is the average amount by which y increases as x
increases by one unit.
TRUE
The least squares line passes through the point (mean of x, mean of y)
TRUE
The slopes of the least squares lines for predicting y from x, and the least squares line
for predicting x from y, are equal.
FALSE
If the absolute value of r=1, the standard deviation of y is equal to the standard deviation of the residuals.
FALSE
The higher the value of the coefficient of determination, the greater the evidence for a
causal relationship between x and y.
FALSE
The standard deviation about the least squares line is roughly the typical amount by
which an observation deviates from the least squares line.
TRUE
The value of the residual plus (Y-hat) is equal to yi
.
TRUE
The coefficient of determination is equal to the positive square root of Pearson's r
FALSE
. A transformation, or reexpression, of a variable is accomplished by substituting a
function of the variable in place of the variable for further analysis.
TRUE
A randomized complete block design with 4 treatment levels and 2 blocks requires 6 subjects.
FALSE
When testing hypotheses concerning differences in treatment effects from an experiment, the test statistic used for comparing two treatments is the same as the test statistic used for comparing differences between two population means from a sample study.
TRUE
The chi-squared test statistic, X2, measures the extent to which the observed cell counts differ from those expected when H0 (null hypothesis) is true.
...
For a sample size n, there are n - 1 degrees of freedom associated with the goodness-of-fit test statistic, X2.
...
In order to decide whether the observed data is compatible with the null hypothesis, the observed cell counts are compared to the cell counts that would be expected when the alternative hypothesis is true.
...
The chi-squared test statistic for testing independence in a two-way tables has rc - 1 degrees of freedom.
...
The row and column marginal totals provide information on the distribution of the observed values for each of the two variables defining the contingency table.
...
For the chi-squared goodness-of-fit chi-squared test, the associated P-value is the area under the appropriate chi-squared curve to the left of the calculated value of X2.
...