FINAL EXAMINATION FOR STAT 202 IN APPLIED
STATISTICAL METHODS
Comparing two Large Data Sets Using Z Scores - answers✔✔Compares two sample means to
determine whether or not to reject the null hypothesis
Alpha - answers✔✔Margin of error or rejection region determinant, also called the "Level of
Significance"
Critical Value - answers✔✔Using alpha to determine the Z score at which you reject the Null
Hypothesis
Comparing two Large Data Sets Using Z Scores: Reject the Null Hypothesis - answers✔✔There is
evidence of a difference in means
Comparing two Large Data Sets Using Z Scores: Accept the Null Hypothesis - answers✔✔There
is no evidence of a difference in means at significance level of alpha = x
Comparing two small Independent Data Sets Using t-Scores: Assumptions - answers✔✔1.
Independent Random Samples
2. Normally distributed Populations
3. Variances are unknown but assumed equal (Sigma 1 = Sigma 2)
n<30
Pooled Variance - answers✔✔The mean of each population may be different, but one may
assume that the variance of each population is the same. Written as Sp^2
, Degrees of Freedom for t-Scores - answers✔✔n1+n2-2 = DF
P-Value Test - answers✔✔If P-val > Alpha, we fail to reject the null hypothesis
If P-val < Alpha, we reject the fail hypothesis
Paired Sample t-Test - answers✔✔Difference between the means of two groups where the
variable of interest is the difference between observations over the observations themselves.
These are dependent samples as opposed to independent samples like a regular independent t-
Test. Repeated observations, before and afters, comparing two similar populations and the
difference between them. These pairings Eliminate variation among subjects.
Experimental Units - answers✔✔
Factors - answers✔✔Factors are those variables whose effect on the response is of interest to
the experimenter, they are quantitative and qualitative (ALSO CALLED INDEPENDENT
VARIABLES)
A factor of an experiment is a controlled independent variable; a variable whose levels are set
by the experimenter.
A factor is a general type or category of treatments. Different treatments constitute different
levels of a factor. For example, three different groups of runners are subjected to different
training methods. The runners are the experimental units, the training methods, the
treatments, where the three types of training methods constitute three levels of the factor 'type
of training'.
Treatment - answers✔✔In experiments, a treatment is something that researchers administer
to experimental units. For example, a corn field is divided into four, each part is 'treated' with a
different fertilizer to see which produces the most corn; a teacher practices different teaching
methods on different groups in her class to see which yields the best results; a doctor treats a
patient with a skin condition with different creams to see which is most effective. Treatments
STATISTICAL METHODS
Comparing two Large Data Sets Using Z Scores - answers✔✔Compares two sample means to
determine whether or not to reject the null hypothesis
Alpha - answers✔✔Margin of error or rejection region determinant, also called the "Level of
Significance"
Critical Value - answers✔✔Using alpha to determine the Z score at which you reject the Null
Hypothesis
Comparing two Large Data Sets Using Z Scores: Reject the Null Hypothesis - answers✔✔There is
evidence of a difference in means
Comparing two Large Data Sets Using Z Scores: Accept the Null Hypothesis - answers✔✔There
is no evidence of a difference in means at significance level of alpha = x
Comparing two small Independent Data Sets Using t-Scores: Assumptions - answers✔✔1.
Independent Random Samples
2. Normally distributed Populations
3. Variances are unknown but assumed equal (Sigma 1 = Sigma 2)
n<30
Pooled Variance - answers✔✔The mean of each population may be different, but one may
assume that the variance of each population is the same. Written as Sp^2
, Degrees of Freedom for t-Scores - answers✔✔n1+n2-2 = DF
P-Value Test - answers✔✔If P-val > Alpha, we fail to reject the null hypothesis
If P-val < Alpha, we reject the fail hypothesis
Paired Sample t-Test - answers✔✔Difference between the means of two groups where the
variable of interest is the difference between observations over the observations themselves.
These are dependent samples as opposed to independent samples like a regular independent t-
Test. Repeated observations, before and afters, comparing two similar populations and the
difference between them. These pairings Eliminate variation among subjects.
Experimental Units - answers✔✔
Factors - answers✔✔Factors are those variables whose effect on the response is of interest to
the experimenter, they are quantitative and qualitative (ALSO CALLED INDEPENDENT
VARIABLES)
A factor of an experiment is a controlled independent variable; a variable whose levels are set
by the experimenter.
A factor is a general type or category of treatments. Different treatments constitute different
levels of a factor. For example, three different groups of runners are subjected to different
training methods. The runners are the experimental units, the training methods, the
treatments, where the three types of training methods constitute three levels of the factor 'type
of training'.
Treatment - answers✔✔In experiments, a treatment is something that researchers administer
to experimental units. For example, a corn field is divided into four, each part is 'treated' with a
different fertilizer to see which produces the most corn; a teacher practices different teaching
methods on different groups in her class to see which yields the best results; a doctor treats a
patient with a skin condition with different creams to see which is most effective. Treatments
