mathhhhh

DF for independent sample t

(n1-1) + ( n2-1)

which Alpha value has a lower risk of making a type 1 error

.01

which Alpha value has a lower risk of making a type 2 error

.05

if the null hypothesis is true, the Z for a sample mean, sample T Test, related samples T Test, all expect an obtained value close to

0

in most research situations in which a related samples T test is used the mean difference expected if the null is true is

0

when Computing the numerator of the independent samples T Test the population mean difference ( i.e U1-U2)will always be

0

if the null hypothesis is true, the Anova F value is expected to be close to

1

the effect size in this study indicates that the anti-anxiety drug raised cholesterol levels of the participants by how many standard deviations and is the effect size small medium or large

1.15 standard deviations large effect size

the first step in Computing a related samples T is to compute different scores (D) by:

Computing the D for each set of paired scores

you use a one-way independent measures Anova when

The IV defines two or more independent samples and the DV is on a ratio interval scale

you use an independent samples T statistic when

The Ivy defines two independent samples and the DV is measured on an interval ratio scale

what symbol represents a null hypothesis when doing a one tailed independent test

U1 >_ U2

what is the symbol that represents the null hypothesis when doing a two tailed independent test

U1=U2

which of the following best represents the null hypothesis for a two-tailed related samples T Test

Ud=0

which significance test should you use to determine if the difference between two unrelated samples is likely due to sampling error

Z for sample mean

when entering the data for an independent t-test you should have

a column for the IV and a column for the DV

why is it better to conduct an anova than multiple T tests when you're comparing multiple conditions

a single Anova helps keep the probability of type 1 error lower than doing multiple T tests

the null hypothesis for the independent Anova is that

all the sample means are the same

the estimated standard error of the mean difference is

an estimate of how different the two sample means are expected to be due to sampling error

an independent T Test can be used to compare differences between people that

are created by the researcher by providing different IV levels already exist in different populations of people

the research hypothesis for the independent and Nova is

at least one of the sample means is different from at least one of the other sample means

if the computed F value is greater than the critical value of f the null hypothesis should

be rejected

A major advantage of the Anova is that it can

compare the data from more than two conditions with a single analysis

the related samples T Test analyzes blank rather than blank

difference scores, raw scores

you use an independent Anova when you want to determine if the mean differences among two or more sample means are likely to be due to sampling error and you have

different people in each condition

to get a one tailed P value, you must

divide the two tailed P value in half

as with all types of T Test single sample and others if the null hypothesis is false the related samples T Test expects and obtained T value that is

far from zero

when you enter data for a related samples T Test you should:

have the paired scores on the same row of the spreadsheet

which of the following common statistical assumptions is not an assumption of the related samples T Test

homogeneity of variance

the levene's test will help you determine

if the two conditions have similar variances or variances that are very different IE the homogeneity of variance assumption is not met or violated

when determining if an effect size is small medium or large you should

ignore the sign of the computed effect size use absolute value

which significance test should you use to determine if the difference between two unrelated samples is likely to be due to sampling error

independent T Test

which sources of score variance can contribute to between treatment variance IE the numerator of an F ratio

individual differences measurement error and treatment effects all three

effect size for independent sample t

m1-m2 / sd2p square rooted

of the three sources of variance that can be potentially influential scores only two of them always influence scores which two will always influence the variability of scores

measurement error individual differences

when the obtained T value is not further from zero than the critical value the null hypothesis should:

not be rejected

if the obtained t value (IE in this case 2.83) is farther from zero than the critical value, the difference between the two means is:

not likely due to sampling error

when Computing the degrees of freedom for a RELATED samples T Test, the n in the formula is the:

number of pairs of scores

MSbetween is divided by the MSerror to produce the

obtained f value

which of the following is the best example of variability due to a treatment effect

people getting treatment may have lower depression scores than those getting treatment be because treatment a is more effective at helping depressed people

post hoc tests are needed whenever you

reject a Nova's null hypothesis and there were more than two independent variable conditions

an important distinction between the single sample t-test and the related sample t-test is that the blank analyzes mean differences between two sample means

related samples T Test

the two names for t test

repeated measures t test related samples t test

when you are doing a one-tailed tea test, the critical region is always on the side of the T distribution that is predicted by the

research hypothesis

the denominator of the f-ratio estimates the amount of variability createdbye

sampling error

the independent t-test is a ratio of the difference between two sample means over an estimate of

sampling error

which of the following values is a measure of sampling error

sem

two tailed research and null hypothesis are described with the key word :

significantly different

which of the following is the best example of variability due to individual differences

some people are more resistant to treatment for depression than others

if the null hypothesis is false the Anova F value is expected to be

substantially greater than 1

critical value for t test:

take the df and go to table and look up number

when Computing a related samples T Test you must remember that all of the analysis are done on

the difference between the paired scores for each participant ie (D)

Ud is the symbolic notation for

the mean of the difference scores from the population

when riding the reporting statement of the results the p-value is written as less than .05 because:

the obtained t value was in the critical region

whenever you fail to reject the null hypothesis and yet the effect size is medium or large you should conclude:

the sample size was too small and you should return the study with a larger sample size

when Computing the standard error of the mean difference, the equation calls for using

the sample sizes from each group

to compute the effect size you divide the observed deviation between the means by

the standard deviation of the difference scores

which of the following values can never be negative

the standard error of the mean difference

how do you interpret the effect size for Anova ieN2P=.22

the type of treatment people received explain to 22% of the variability in anxiety scores

the denominators of the single sample t-test and the related sample t-test are both blank

the typical amount of sampling error expected in the study

in research studies, researchers are most interested in evaluating which of the following sources of score variance

treatment effect

which source of score variance will never contribute to within treatment variance

treatment effects

what is the best example of variability due to measurement error

two people with the same level of depression produce different scores on a depression inventory

researchers use the related samples T test to determine if blank differ more than would be expected by sampling error

two related sample means

the numerator of the independent samples t-test is the difference between

two sample means

levene's test is automatically run by SPSS to determine if the blank of the two groups is significantly

variances

what are two things to do when interpreting the statistical results of any study?

you should consider if a confounding variable might have affected the results you should recognize that the experimental design is just as important to the scientific conclusion as the statistical result