Psych 2220 Midterm 3
nominal variable
a variable used for observations that have categories, or names, as their values
ordinal variable
a variable whose categorical values possess some kind of order
ratio variable
A variable that meets the criteria for interval variables but also has a meaningful zero point
single sample t test
hypothesis test in which we collect data to a population for which we know the mean but not the standard deviation
single-sample t test
hypothesis test in which we compare a sample from which we collect data to a population for which we know the mean but not the standard deviation
as the sample size increases what happens to the corresponding t distribution?
it more closely approximates the z distribution
t-distributions
the t distributions help us specify how confident we can be about research findings, we want to know whether or not we can generalize what we have learned about one sample to a larger popuation
paired-samples t test
used to compare two means for a within groups design, a situation which every participant is in both samples, also called a dependent-samples t test
independent samples t-test
used to compare two means, for a between groups design, a situation in which each participant is assigned to only one condition
standard error
the standard deviation of a distribution of means
how to find scores that fall between 2 z scores
(% to mean + 50) + % in tail
how to find scores that are at least as extreme as 2 z scores
(50 - % to mean) + % in tail
six steps of hypothesis testing
1. Identify populations 2. state both hypothesis 3. critical values (p table)
paired samples t-test
1.difference between scores x2-x1 2.add up differences and divide by N 3.diff-mean differences 4.square the results 5.add sum of squared deviations that will be numerator 6.solve for standard deviation sqrt num/n-1 7.find standard error with previous result 8.mean difference - 1 / standard error
how to find scores above z score
100 - %in tail
how to find scores below zvscore
100 - %in tail
standard deviation
a computed measure of how much scores vary around the mean score
variances
changes that have occurred over time.
cohen's d
d=(M-u)/sd, measure of effect size that assesses the difference between 2 means in terms of standard devation
correlational studies
examine relationships between variables
type 2 error
failing to reject a false null hypothesis
What is an assumption of the independent-samples t test, but not an assumption of the one-sample t test?
homogeneity of variance
statistical power
measure of the likelihood that we will reject the null hypothesis, given that the null hypothesis is false
what does a z score of 0 represent
no standard deviations above or below the mean
central limit theorem
refers to how a distribution of means is a more normal distribution than a distribution of scores, even when the population distribution is not normal
type 1 error
rejecting a true null hypothesis
distribution of means
same mean as a distribution of scores from the same population , but a smaller standard deviation
point estimates
sample mean and sample proportion
Which of the following sampling distributions is used when conducting a paired-samples t test?
sampling distribution of mean differences
sample standard deviation
sqrt(x-M)squared/N
interval estimates
the extent to which point estimates are likely to be in error
degrees of freedom
the number of scores that are free to vary when we estimate a population parameter from a sample
interval variable
the order matters, and the distance between data points are all equal. ex: temperature
independent events
the outcome of one event does not affect the outcome of the second event
conditional probabilities
the probability of one event given the known outcome of a related event
experiments
the use of control and experimental groups and dependent and independent variables to test causation
95% confidence interval
upper/lower mean +/-1.96*SEM SEM = standard dev/root(n)
discrete variables
values that can be counted
continuous variables
variables that take on any value
when do we use a t distribution, instead of the z distribution, to conduct a hypothesis test comparing two means?
when we do not know the population standard deviation
