Exam 1 Closed Book Flashcards
(30 cards)
A frequency distribution of several mean values is called
a sampling distribution
With inferential statistics we can use
𝑥̅ to estimate μ and sample statistics to estimate population parameters
A standard error
relates to how much uncertainty there is in an estimate of the population mean
Type II error is
accepting the H0 when it’s false
a frequency distribution of several mean values is
a sampling distribution
if a value is selected a priori, the value has been selected
based on already known, pre-determined info
In relation to variance, the standard deviation
returns the sample to its original units
An example of nominal scale data is
hair color
A measure of central tendency includes
the mean, mode, median
p-value is the probability
of obtaining sample statistic from a population in which null hypothesis is true.
Ordinal scales involve
ranks
In inferential statistics we use sample statistics to
estimate population parameters
An example of ordinal-scale data is
weight classes
An example of interval-scale data is
temperature
An example of ratio-scale data is
length or volume
population means are represented by
mu
sample means are represented by
x bar
A p-value is
the probability of obtaining your sample data and statistics from a population in which the null hypothesis is true
The test that deals with two nominal-scale variables
contingency table
Expected frequencies in contingency tables are
calculated ( a posteriori)
What two tests must be done before continuing with a contingency table?
R and B rule and category size
Measures of dispersion include
the range, sum of squares, variance, standard deviation and coefficient of variation
The standard deviation of the sampling distribution is
the standard error
According to central limit theorem
the means of samples from a normally distributed population will be normally distributed as well; and samples from any distribution will have means that approach normal distributions as the sample size increases.
