# Quantitative Analysis

Quantitative Analysis
Part 1
Compare and contrast internal and external validity. Describe and give
examples of research questions for which external validity is a primary
concern. Describe and give examples of research questions in which
internal validity is a primary concern. Discuss strategies researchers
use in order to make strong claims about the applicability of their
findings to a target population.
Compare and contrast random selection and random assignment. Be sure to
include a discussion of when you would want to do one or the other and
the possible consequences of failing to do random selection or random
assignment in particular situations.
Explain the relationship between sample size and the likelihood of a
statistically significant difference between measured values of two
groups. In other words, explain why, all else being equal, as sample
size increases the likelihood of finding a statistically significant
relationship increases.
Compare and contrast probability and non-probability sampling. What are
Part 2
If you do a quantitative study for your dissertation, you must estimate
the sample size you will need in order to have a reasonable chance of
finding a relationship among the variables stated in your research
hypotheses (should one exist), given your statistical analysis(es) and
assumptions/calculations of factors 2-4 above. You must do this, even if
you plan to use a convenience sample (see below). There are a number of
sample size calculators available. Northcentral uses G*Power, which is
required in this Activity. You will use G*Power’s “a priori power
analysis” function to calculate a sample size. If it yields an
unrealistically large size sample, you will rethink your design and
assumptions and, perhaps, use G*Power’s “compromise power analysis” to
estimate a workable sample size that makes sense. If you plan on using a
convenience sample, you would use both analyses as part of your argument
that your convenience sample is large enough.
1.
Calculate the sample size needed given these factors:
one-tailed t-test with two independent groups of equal size
small effect size (see Piasta, S.B., & Justice, L.M., 2010)
alpha =.05
beta = .2
Assume that the result is a sample size beyond what you can obtain. Use
the compromise function to compute alpha and beta for a sample half the
size. Indicate the resulting alpha and beta. Present an argument that
your study is worth doing with the smaller sample.
2.
Calculate the sample size needed given these factors:
ANOVA (fixed effects, omnibus, one-way)
small effect size
alpha =.05
beta = .2
3 groups
Assume that the result is a sample size beyond what you can obtain. Use
the compromise function to compute alpha and beta for a sample
beta/alpha ratio. Indicate the resulting alpha and beta. Give an
argument that your study is worth doing with the smaller sample.
3. In a few sentences, describe two designs that can address your
research question. The designs must involve two different statistical
analyses. For each design, specify and justify each of the four factors
and calculate the estimated sample size you’ll need. Give reasons for
any parameters you need to specify for G*Power.
Include peer-reviewed journal articles as needed to support your
responses to Part I.
Support your paper with a minimum of 5 resources. In addition to these
specified resources, other appropriate scholarly resources, including
older articles, may be included.
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