One and Two Sample Interference Flashcards
this is the analysis and interpretation of data
inferential
parametric and non parametric test
inferential
are the test applied to data that are normally distributed
parametric test
parametric test is usually expressed in
interval and ratio
in parametric test, the skewness is equal to
zero
in parametric test, the kurtosis is equal to
0.265
True or False
parametric test is more powerful than non parametric test
true
what is the non parametric equivalent of paired t test
wilcoxon rank sum test
what is the non parametric equiavalent of unpaired t test
mann-whitney u test
its non parametric equivalent is spearman correlation
pearson correlation
what is the nonparametric equivalent of one way analysis of variance
kruskal wallis test
procedures in hypothesis testing
- formulate the null and alternative hypothesis
- choose a level of significance
- choose the appropriate test statistic
- establish critical region
- decision (accept null if outside the critical region)
- conclusion
if the computed t-statistics is less than the critical value, does it fall in the critical region?
it does not fall in the critical region
if the critical value falls in the critical value, should we reject or accept?
reject
this table is used to find the critical values based on 95% confidence level and alpha at 0.05
t table
this test involves the direction and the degrees of freedom in determining the probability or the critical value
t table
number of observations, and the data that are free to vary when estimating a statistical parameter
degrees of freedom
degrees of freedom used to calculate what kind of values?
t-values and p-values
it is used when you want to test if the sample’s mean from which the sample is drawn is at a hypothesized value
one sample interference
it is typically implemented on small samples
one sample interference
the purpose of this is to determine if the sample observation could have come from a process that followes a specific parameter like the mean
one sample interfence
it is used to determine whether the mean of a sample data set is different from a known value
one sample mean test
True or False
small sample size makes the test more conservative means that the small but important differences may be detected
False (small but important differences may NOT be detected)
True or False
increasing sample size makes the statistical test more powerful
true
