Statistics Exam 2
leveneTest(write what goes in here)
(dependent variable, independent variable, center for Levene's test)
describeBY(write what goes in here)
(dependent variable, independent variable, fast = TRUE or FALSE)
Type II error
Beta
the power curve provides the probability of
correctly rejecting the null hypothesis
null hypothesis
no effect or difference between the two values
parameters
numerical characteristics of a population
if the null value falls outside of the interval, we
reject Ho
fast = TRUE
speed up
Bias
systematic (built-in) error that pushes an estimate away from its true value
The test statistic produced in an ANOVA is a ratio of two variances: ___.
the between group variance and the within group variance
type 1 error
the error of rejecting the true null hypothesis
In the analysis of variance procedure (ANOVA), "factor" refers to
the independent variable
the sample statistic s is the point estimator of
σ(standard deviation)
alternative hypothesis: true mean is not equal 70
2 tailed test
The ANOVA procedure is a statistical approach for determining whether or not the means of
3 or more populations are equal
What is the basic idea behind the null hypothesis for Levene's test?
At the population level, the variances for the groups are the same.
as n increases, what happens to the standard error of the mean
SE decreases
Suppose we follow up a statistically significant 5-group ANOVA with an Unadjusted Fisher's LSD test using an alpha of 0.05. We aren't interested in all possible pairwise comparisons; we are really only interested in 3 of them. How can we manipulate the output we generate to get p-values that only take 3 pairwise comparisons into account and get the most power out of the post-hoc analyses?
Take the p-values of the comparisons of interest and multiply them by 3 before comparing them to 0.05.
According to the structural model approach to ANOVA, what does αj represent?
The impact of the treatment factor, or how levels of the independent variable can contribute to measurement differences on observations.
If all else remains the same, what happens to a confidence interval if the sample standard deviation gets narrower?
The interval gets narrower.
as n increases, the sampling distribution of the sample mean approaches what distribution?
a normal distribution
Precision
an indicator of how similarly a quantity is measured over repeated instances
if the confidence interval goes from 95% to 90%, the confidence interval for mu
becomes narrower
in interval estimation, as the n becomes larger, the interval estimate
becomes narrower
as the df for a t distribution increases, the difference between the t distribution and the standard normal distribution
becomes smaller
Distribution of means
compilation of all sample means that come from a particular sample size
what is point estimation
data from the sample is used to estimate the population parameter
as n increases, the MOE
decreases
In the ANOVA, treatments refer to
different levels of a factor
hypothesis testing
evaluates the likelihood of obtaining a particular outcome in a statistical experiment when we have a prior idea about what should have happen
n increases, the CI
gets narrower
as the test statistic becomes larger, the p-value
gets smaller
describe()
gives us basic summary statistics about our variable of interest
if a hypothesis is rejected at the 5% level of significance, what will happen at the 1% level of significance?
it may be rejected or retained
the smaller the type I error, the _______ the type II error will be
larger
t.test(variable, alternative, null value, conf.level)
runs t test function
The required condition for using an ANOVA procedure on data from several populations is that the
sampled populations have equal variances
the probability of committing a type I error when the null hypothesis is true as an equality is
the level of significance
the p-value is a probability that measures the support for
the null hypothesis
the probability distribution of all possible values of the sample mean is
the sampling distribution of x bar
When s is used to estimate σ, the margin of error is computed by using
the t distribution
confidence intervals
they are built around point estimates to provides a suggested range of values that could represent the true population value of what has been measured
paired = TRUE
turns on dependent t-test
alternative = "two.sided"
two tailed t test with Ha
the level of significance is the maximum allowable probability of
type I error
var-equal = TRUE
use equal variances approach
if the level of significance of a hypothesis test is raised from .01 to .05, the probability of a type II error
will decrease
the sample mean is the point estimate of
μ
