Statistics Module 7 (Questions and Answers A+ Graded 100% Verified)

Statistics Module 7 (Questions and Answers A+ Graded 100% Verified) Seven steps of hypothesis testing 1. state Ho and Ha hypothesis, and test statistic 2. state level of significance 3. state whether one tailed or two tailed test 4. compute test statistic 5. determine degrees of freedom 6. obtain critical value from the distribution table 7. compare and decide whether to accept/reject Ho hypothesis and significant/non significant when is t test appropriate? - when we want to make inferences about two populations - investigate differences between two samples or populations - to compare actual mean difference observed between two groups - is the difference more (in either direction) than would be expected by chance alone t-test strategy what is in the numerator of the t-test formula? the difference between two means: sample mean and population mean provides a measure of the variance and sample size what is in the denominator of the t-test formula? how to compute for the degrees of freedom of t-test? N - 1; where N is the number of groups degrees of freedom the extent be which scores can vary or be different 2 types of t-test 1. independent samples 2. two related samples a t-test that determine difference of means between two distinctly groups (e.g RNs and RPNs - not the same) independent samples a t-test that determine difference of means between same group on two different occasions (e.g same group of nurses pre and post intervention) -two related samples (within samples) level of measurement of independent variable when using t test for independent samples - nominal or ordinal level of measurement of dependent variable when using t test for independent samples - interval or ratio between subjects between or within: comparison between two different samples within subjects between or within: comparison between similar group of sample but on two different occasion - repeated measures false: no logical relationship; they are independent of each other true or false: in independent sample, there is a logical relationship that exist between persons in one group and persons in another group - all observations are dependent of each other 1. the independent variable is nominal/categorical with two levels (mutually exclusive and independent 2. dependent variable is continuous (interval or ratio), normally distributed 3. homogeneity of variance (similar variance of the dependent variable for the two groups 3 assumption for independent t test dependent sample t test paired t test, matched pair sample or correlated samples - used to compare means of two groups when the individual scores in one group are paired with particular scores in the other group 1. single group of persons measured twice (pre- and post-test scores) 2. match the 1st and 2nd group (matched on IQ scores) 3. splitting of biological twins into separate groups 3 ways to match samples 1. sample data consist of matched pairs 2. samples are simple random samples 3. sample size N>30 3 assumptions for t test of dependent samples false: before and after; using the same sample true or false: within subjects or repeated measure studies involve taking data after a treatment using a different sample true true or false: in t test for repeated measures, the two data sets are considered to be related or dependent because the same subjects are used, and the first measure on each individual will likely carry over similarities in the second measure increase control since the subjects are exactly the same individuals for each measure the main advantage of t test for dependent measures