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39 Cards in this Set

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The probability that a sample was randomly drawn from population is measured by...
z test and T test. (diff with t test is that you know pop mean, but not pop strd dev)
Did incoming grad students score significantly better than the population who took the GRE?
This question is addressed by what type of test?
z test ( 1 tailed)
Do students in Lubbock score significantly beeter or worse than students in TX on statewide achievement tests?
Z test
The t distribution approaches the z distribution as...
sample size approaches infinity
In T Testing, for a value to be considered significant, what must be true of the critical and observed t values?
t(observed) must be creater than t(critical) in order for something to be significant.
In terms of p values, what must be true for siginifcance?
For something to be signficant, p must be less than .05
Is performance better than chance in a 5 alternative test where chance =.20? Are corrlations between predictions and performance that I find for each participant significantly greater than 0?
These questions can be adressed by using what type of test?
t test
What are the 3 types of t tests? Describe the differences between each type of test.
1.single sample t test
2. dependent (paired samples) t test
3. independent (2 sample) t test

1.determines the probability that the sample was drawn from the population (or not); want to decide how likely it is that your sample is a random sample from the population
info given: pop mean, but not pop strd dev
2.-Testing whether the avg difference between two scores is zero.
-compares knowledge at begining and end of course to see if knowledge incr

3.-compares two samples to determine whether they came from the same population or not
-determines wether a difference between groups is likely/unlikely to have occured by chance
info given: 2 means, but no info about pop mean or pop std dev
determines the probability that the sample was drawn from the population (or not); want to decide how likely it is that your sample is a random sample from the population
single sample t test
.-Testing whether the avg difference between two scores is zero.
-compares knowledge at begining and end of course to see if knowledge incr
dependent (paired samples) t test
compares two samples to determine whether they came from the same population or not
-determines wether a difference between groups is likely/unlikely to have occured by chance
independent samples t test
info given: 2 means, but no info about pop mean or pop std dev
independent samples t test
info given: pop mean, but not pop strd dev
single sample t test
This type of test could help you examine whether males or females do better in PSY 5380
independent samples t test
Was the sample selected by student 1 different from the sample selected by student 2?
independent t test
Is the control group mean different from the treatment group mean (is it likely that both means were drawn randomly from the same population)?
independent t test
Do males and females differ in their response to an advertisement?
independent t test
Distinguish between the 4 types of scales.
nominal
ordinal
interval
ratio
Classification in terns of mutually exlusive groups that do not have magnitude relationships.
nominal scale
breed of dog, gender
nominal scale
reflects differences in magnitude, but equal intervals cannot be assumed and their is no zero point
ordinal scale
national ranks of football teams, student's high school class rank
ordinal scale
reflects differences in magnitude and has equal intervals but no absolute zero point
interval scale
IQ scores, ACT/SAT scores, temperature scales
interval (be/c no true zero)
reflects magnitude, equal intervals, and has a zero point
ratio scale
dollars to euro conversion is reflective of which scale. Why?
ratio scale, because equal intervals with zero pt.
Parametric statistics are used with which scales?
interval and ratio scalses
nonparametric statistics are used with which scales?
nominal and ordinal
(we don't cover in this class)
What is the probability that a mean that large or larger would
come from a population with Mu =5.68?
single sample t test ( in this case, 1 tailed)
A person scored 600 on their GRE. The population mean for GRE is equal to 500, with a standard deviation of 100.
b) What percentage of the population had the same score or lower than this person?
z score
I have a sample with N=9 and Y bar =5.11. My population has a known mean (Mu=5.68) and a known standard deviation (sigma = 2.24).
a) What is the probability of getting a Z this low or lower?
b) What is the probability of getting a Z this high or higher?
c) What is the probability of getting a z= 0.76 or bigger and z= -0.76 or lower
Z test
A group of college students was randomly assigned to a lecture group or a World-Wide
Web (WWW) group. The lecture group heard a lecture on independent samples ttests.
The WWW studied the same material as presented on the Web. Then both groups were
given a test over the material. The results (percent correct on the test) were as follows:
Independent Samples t Test ( 2 sample t test)
. Pre- and Post-test scores for students are provided. Did the students’ performance increase significantly as a result of taking the course?
Dependent t test (Paired Samples t Test)
. PSY 1300 students answer questions from practice GRE at the beginning of semester.
They answer 20 questions. Each question has 5 alternatives.
a) Is the students’ performance significantly different from chance?
b) Construct a 95% confidence interval around the sample mean.
Single sample T test
I have a sample with a mean of 7.2 and N=9. The relevant population has a Mu = 5.68, Sj = 2.40.
a) Is my mean larger than would be expected if I had drawn my sample randomly?
b) Is my mean larger OR smaller than would be expected if I had drawn my sample randomly?
Single sample T test
Describe how Confidence intervals are calculated.
lower limit: sample mean - tcritical(standard error of mean)

Upper limit: sample mean + tcrit(standard error of mean)
Describe the central limit theorem
If a population has a finite variance sigma squared an a mean mu, then the distribution of sample means from samples of n independent observations approaches a normal distribution with variance sigma squared/n and a mean mu as sample n increases
Large sample sizes tell you what about the variance of the sampling distribution.
Larger sample sizes mean less variance in the sampling distribution
The CLT tells us what about the sampling distribution of means
-sampling distrbution of means = population mean ( if thousands of random samples are taken)
-the sampling distribution of means will approach normality with larger samples, even if the population is not normal.