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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 WorldWide
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 Posttest 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. 