Week 1 discussion
The Logic of Inference: The Science of Uncertainty
Describing and explaining social phenomena is a complex
task. Box’s quote speaks to the point that it is a near impossible undertaking
to fully explain such systems—physical or social—using a set of models. Yet
even though these models contain some error, the models nevertheless assist
with illuminating how the world works and advancing social change.
The competent quantitative researcher understands the
balance between making statements related to theoretical understanding of
relationships and recognizing that our social systems are of such complexity
that we will always have some error. The key, for the rigorous researcher, is
recognizing and mitigating the error as much as possible.
As a graduate student and consumer of research, you must
recognize the error that might be present within your research and the research
of others.
To prepare for this Discussion:
Use the Walden Library Course Guide and Assignment Help
found in this week’s Learning Resources to search for and select a quantitative
article that interests you and that has social change implications.
As you read the article, reflect on George Box’s quote in
the introduction for this Discussion.
For additional support, review the Skill Builder:
Independent and Dependent Variables, which you can find by navigating back to
your Blackboard Course Home Page. From there, locate the Skill Builder link in
the left navigation pane.
By Day 3
Post a very brief description (1–3 sentences) of the article
you found and address the following:
Describe how you think the research in the article is useful
(e.g., what population is it helping? What problem is it solving?).
Using Y=f(X) +E notation, identify the independent and
dependent variables.
How might the research models presented be wrong? What types
of error might be present in the reported research?
Be sure to support your Main Post and Response Post with
reference to the week’s Learning Resources and other scholarly evidence in APA
Style.
By Day 5
Remembering that all research has some error, respond to at
least one colleague’s post and comment on how we as social change agents and
critical consumers of research can balance the usefulness with the error in the
research. Do we throw the research out because of too much error, or is there
something useful that it can tell us?
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Week 2 discussion
Displaying Data
Visual displays of data provide you and anyone else with a
graphical display of what is often a complex array of quantitative data. A key
strength of visualization is the ability to quickly enlighten you with key
data. Rather than solely relying on your audience to interpret numerical values
and statistics explained in a narrative, a visual display can easily illustrate
descriptions, relationships, and trends. Although the focus is on simplicity,
the researcher has an obligation to present these graphical displays in a clear
and meaningful way.
For this Discussion, you will explore ways to appropriately
display data.
To prepare for this Discussion:
Review the Learning Resources for this week related to
frequency distributions and graphic displays of data.
Using the SPSS software, open the General Social Survey
dataset found in this week’s Learning Resources.
Next, create a figure or table from a few selected variables
within the dataset.
Finally, think about what is good about how the data are
displayed in the figure or table you created and what is not so good.
By Day 3
Post your display of the table or figure you created and
provide an explanation of why this would be the best way to display the data
provided.
Be sure to support your Main Post and Response Post with
reference to the week’s Learning Resources and other scholarly evidence in APA
Style.
By Day 5
Respond to at least one of your colleagues’ post and
determine whether you are able to understand the “whole picture” of the data or
understand the data in its entirety. What might you add to their display and
why? What might you change to their display and why?
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Week 3 discussion
Central Tendency and Variability
Understanding descriptive statistics and their variability
is a fundamental aspect of statistical analysis. On their own, descriptive
statistics tell us how frequently an observation occurs, what is considered
“average”, and how far data in our sample deviate from being “average.” With
descriptive statistics, we are able to provide a summary of characteristics
from both large and small datasets. In addition to the valuable information
they provide on their own, measures of central tendency and variability become
important components in many of the statistical tests that we will cover.
Therefore, we can think about central tendency and variability as the
cornerstone to the quantitative structure we are building.
For this Discussion, you will examine central tendency and
variability based on two separate variables. You will also explore the
implications for positive social change based on the results of the data.
To prepare for this Discussion:
Review this week’s Learning Resources and the Descriptive
Statistics media program.
For additional support, review the Skill Builder: Visual
Displays for Categorical Variables and the Skill Builder: Visual Displays for
Continuous Variables, which you can find by navigating back to your Blackboard
Course Home Page. From there, locate the Skill Builder link in the left
navigation pane.
Review the Chapter 4 of the Wagner text and the examples in
the SPSS software related to central tendency and variability.
From the General Social Survey dataset found in this week’s
Learning Resources, use the SPSS software and choose one continuous and one
categorical variable Note: this dataset will be different from your Assignment
dataset).
As you review, consider the implications for positive social
change based on the results of your data.
By Day 3
Post, present, and report a descriptive analysis for your
variables, specifically noting the following:
For your continuous variable:
Report the mean, median, and mode.
What might be the better measure for central tendency?
(i.e., mean, median, or mode) and why?
Report the standard deviation.
How variable are the data?
How would you describe this data?
What sort of research question would this variable help
answer that might inform social change?
Post the following information for your categorical
variable:
A frequency distribution.
An appropriate measure of variation.
How variable are the data?
How would you describe this data?
What sort of research question would this variable help
answer that might inform social change?
Be sure to support your Main Post and Response Post with
reference to the week’s Learning Resources and other scholarly evidence in APA
Style.
By Day 5
Respond to at least one colleagues’ post with a comment on
the presentation and interpretation of their analysis. In your response, address
the following questions:
Was the presentation of results clear? If so, provide some
specific comments on why. If not, provide constructive suggestions.
Are you able to understand how the results might relate back
to positive social change? Do you think there are other aspects of positive
social change related to the results?
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entering your message. Then click on the Submit button to post your message.
Week 4 discussion
The Importance of Relationships
As its name implies, confidence intervals provide a range of
values, along with a level of confidence, to serve as an estimate of some
unknown population value. Since it is rare to have access to the entire
population, you must frequently rely on the confidence interval of the sample
to make some inference about the population of interest. Before making accurate
inferences to the population, we need to fully understand how the three key
components of the interval—variability in the data, sample size, and confidence
level—impact the width of the interval.
For this Discussion, you will explore the relationship
between these components and understand the trade-off between reducing risk in
our confidence of estimates and increasing precision.
To prepare for this Discussion:
Review Chapters 7 and 8 of the Frankfort-Nachmias &
Leon-Guerrero text and in Chapter 8, p. 256, consider the 2012 Benghazi
Terrorist Attack Investigation and focus on how different levels of confidence
and sample size work together.
Review Magnusson’s web blog found in the Learning Resources
to further your visualization and understanding of confidence intervals.
Use the Course Guide and Assignment Help found in this
week’s Learning Resources to search for a quantitative article related to
confidence intervals.
Using the SPSS software, General Social Survey dataset and
choose a quantitative variable that interests you.
By Day 3
Using SPSS:
Take a random sample of 100.
Calculate the 95% confidence interval for the variable.
Calculate a 90% confidence interval.
Take another random sample of 400.
Calculate the 95% confidence interval for the variable.
Calculate a 90% confidence interval.
Post your results and an explanation of how different levels
of confidence and sample size affect the width of the confidence interval.
Next, consider the statement, “Confidence intervals are underutilized” and
explain what the implications might be of using or not using confidence
intervals. Provide examples based on the results of your data. Also, use your
research to support your findings.
Be sure to support your Main Post and Response Post with
reference to the week’s Learning Resources and other scholarly evidence in APA
Style.
By Day 5
Respond to one of your colleague’s posts and explain how you
might see the implications differently.
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entering your message. Then click on the Submit button to post your message.
Week 5 discussion
Statistical Significance and Meaningfulness
Once you start to understand how exciting the world of statistics
can be, it is tempting to fall into the trap of chasing statistical
significance. That is, you may be tempted always to look for relationships that
are statistically significant and believe they are valuable solely because of
their significance. Although statistical hypothesis testing does help you
evaluate claims, it is important to understand the limitations of statistical
significance and to interpret the results within the context of the research
and its pragmatic, “real world” application.
As a scholar-practitioner, it is important for you to
understand that just because a hypothesis test indicates a relationship exists
between an intervention and an outcome, there is a difference between groups,
or there is a correlation between two constructs, it does not always provide a
default measure for its importance. Although relationships are significant,
they can be very minute relationships, very small differences, or very weak
correlations. In the end, we need to ask whether the relationships or differences
observed are large enough that we should make some practical change in policy
or practice.
For this Discussion, you will explore statistical significance
and meaningfulness.
To prepare for this Discussion:
Review the Learning Resources related to hypothesis testing,
meaningfulness, and statistical significance.
Review Magnusson’s web blog found in the Learning Resources
to further your visualization and understanding of statistical power and
significance testing.
Review the American Statistical Association’s press release
and consider the misconceptions and misuse of p-values.
Consider the scenario:
A research paper claims a meaningful contribution to the
literature based on finding statistically significant relationships between
predictor and response variables. In the footnotes, you see the following
statement, “given this research was exploratory in nature, traditional levels
of significance to reject the null hypotheses were relaxed to the .10 level.”
By Day 3
Post your response to the scenario in which you critically
evaluate this footnote. As a reader/reviewer, what response would you provide
to the authors about this footnote?
Be sure to support your Main Post and Response Post with
reference to the week’s Learning Resources and other scholarly evidence in APA
Style.
By Day 5
Respond to at least one of your colleagues’ posts and
explain the benefits and consequences of the “relaxed” level of significance.
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entering your message. Then click on the Submit button to post your message.
Week 6 discussion
Research Design and t Tests: How Are They Connected?
The best way to solidify your understanding of statistical
testing is to actually engage in performing some data analysis. This week you
will work with a real, secondary dataset to construct a research question,
perform a t test, and interpret the results.
Whether in a scholarly or practitioner setting, good
research and data analysis should have the benefit of peer feedback. For this
Discussion, you will post your response to the hypothesis test, along with the
results. Be sure and remember that the goal is to obtain constructive feedback
to improve the research and its interpretation, so please view this as an opportunity
to learn from one another.
To prepare for this Discussion:
Review the Learning Resources and the media programs related
to t tests.
Using the SPSS software, open the High School Longitudinal
Study dataset found in this week’s Learning Resources and construct a research
question that involves a comparison of a means test.
By Day 3
Use SPSS to answer the research question you constructed and
post your response to the following:
What is your research question?
What is the null hypothesis for your question?
What research design would align with this question?
What comparison of means test was used to answer the
question (be sure to defend the use of the test using the article you found in
your search)?
What dependent variable was used and how is it measured?
What independent variable is used and how is it measured?
If you found significance, what is the strength of the
effect?
Identify your research question and explain your results for
a lay audience, what is the answer to your research question?
Be sure to support your Main Post and Response Post with
reference to the week’s Learning Resources and other scholarly evidence in APA
Style.
By Day 5
Respond to one of your colleagues’ posts and:
Make recommendations for the design choice.
Explain whether you think that this is the appropriate t
test to use for the question. Why or why not?
As a lay reader, were you able to understand the results and
their implications? Why or why not?
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entering your message. Then click on the Submit button to post your message.
Week 7 discussion
Research Design for One-Way ANOVA
Similar to the previous week’s Discussion, this Discussion
assists in solidifying your understanding of statistical testing by engaging in
some data analysis. This week, you will once again work with a real, secondary
dataset to construct a research question, perform a one-way ANOVA, and
interpret the results.
Whether in a scholarly or practitioner setting, good
research and data analysis should have the benefit of peer feedback. For this
Discussion, you will post your response to the hypothesis test, along with the
results. Be sure and remember that the goal is to obtain constructive feedback
to improve the research and its interpretation, so please view this as an
opportunity to learn from one another.
To prepare for this Discussion:
Review this week’s Learning Resources and media program
related to one-way ANOVA testing.
Using the SPSS software, open the General Social Survey
dataset found in this week’s Learning Resources.
Using the General Social Survey dataset, construct a
research question that can be answered by a one-way ANOVA.
By Day 3
Use SPSS to answer the research question. Post your response
to the following:
What is your research question?
What is the null hypothesis for your question?
What research design would align with this question?
What dependent variable was used and how is it measured?
What independent variable is used and how is it measured?
If you found significance, what is the strength of the
effect?
Explain your results for a lay audience and further explain
what the answer is to your research question.
Be sure to support your Main Post and Response Post with
reference to the week’s Learning Resources and other scholarly evidence in APA
Style.
By Day 5
Respond to at least one of your colleagues’ posts and
respond based the following:
Do you think the variables are appropriately used? Why or
why not?
Does the analysis answer the research question? Be sure to
provide constructive and helpful comments for possible improvement.
If there was a significant effect, comment on the strength
and its meaningfulness.
As a lay reader, were you able to understand the results and
their implications? Why or why not?
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entering your message. Then click on the Submit button to post your message.
Week 8 discussion
Correlation and Bivariate Regression
Similar to the previous week’s Discussion, this Discussion
assists in solidifying your understanding of statistical testing by engaging in
some data analysis. This week you will once again work with a real, secondary
dataset to construct a research question, perform a correlation and bivariate
regression model, and interpret the results.
Whether in a scholarly or practitioner setting, good
research and data analysis should have the benefit of peer feedback. For this
Discussion, you will post your response to the hypothesis test, along with the
results. Be sure and remember that the goal is to obtain constructive feedback
to improve the research and its interpretation, so please view this as an
opportunity to learn from one another.
To prepare for this Discussion:
Review this week’s Learning Resources and media program
related to regression and correlation.
Review Magnusson’s web blog found in the Learning Resources
to further your visualization and understanding of correlations between two
variables.
Construct a research question using the General Social
Survey dataset, which can be answered by a Pearson correlation and bivariate
regression.
By Day 3
Use SPSS to answer the research question. Post your response
to the following:
What is your research question?
What is the null hypothesis for your question?
What research design would align with this question?
What dependent variable was used and how is it measured?
What independent variable is used and how is it measured?
If you found significance, what is the strength of the
effect?
Explain your results for a lay audience; explain the answer
to your research question.
Be sure to support your Main Post and Response Post with
reference to the week’s Learning Resources and other scholarly evidence in APA
Style.
By Day 5
Respond to at least one of your colleagues’ posts and
comment on the following:
Do you think the variables are appropriately used? Why or
why not?
Does the analysis answer the research question? Be sure and
provide constructive and helpful comments for possible improvement.
If there was a significant effect, comment on the strength
and its meaningfulness.
As a lay reader, were you able to understand the results and
their implications? Why or why not?
Click on the Reply button below to reveal the textbox for
entering your message. Then click on the Submit button to post your message.
Week 9 discussion
Multiple Regression
As with the previous week’s Discussion, this Discussion
assists in solidifying your understanding of statistical testing by engaging in
some data analysis. This week you will once again work with a real, secondary
dataset to construct a research question, estimate a multiple regression model,
and interpret the results.
Whether in a scholarly or practitioner setting, good
research and data analysis should have the benefit of peer feedback. For this
Discussion, you will post your response to the hypothesis test, along with the
results. Be sure and remember that the goal is to obtain constructive feedback
to improve the research and its interpretation, so please view this as an
opportunity to learn from one another.
To prepare for this Discussion:
Review this week’s Learning Resources and media program related
to multiple regression.
Create a research question using the General Social Survey
that can be answered by multiple regression.
By Day 3
Use SPSS to answer the research question. Post your response
to the following:
What is your research question?
What is the null hypothesis for your question?
What research design would align with this question?
What dependent variable was used and how is it measured?
What independent variable is used and how is it measured?
What other variables were added to the multiple regression
models as controls?
What is the justification for adding the variables?
If you found significance, what is the strength of the
effect?
Explain your results for a lay audience, explain what the
answer to your research question.
Be sure to support your Main Post and Response Post with
reference to the week’s Learning Resources and other scholarly evidence in APA
Style.
By Day 5
Respond to at least one of your colleagues’ posts and
comment on the following:
Do you think the variables are appropriately used? Why or
why not?
Does the addition of the control variables make sense to
you? Why or why not?
Does the analysis answer the research question? Be sure and
provide constructive and helpful comments for possible improvement.
If there was a significant effect, comments on the strength
and its meaningfulness.
As a lay reader, were you able to understand the results and
their implications? Why or why not?
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entering your message. Then click on the Submit button to post your message.
Week 10 discussion
Estimating Models Using Dummy Variables
You have had plenty of opportunity to interpret coefficients
for metric variables in regression models. Using and interpreting categorical
variables takes just a little bit of extra practice. In this Discussion, you
will have the opportunity to practice how to recode categorical variables so
they can be used in a regression model and how to properly interpret the
coefficients. Additionally, you will gain some practice in running diagnostics
and identifying any potential problems with the model.
To prepare for this Discussion:
Review Warner’s Chapter 12 and Chapter 2 of the Wagner
course text and the media program found in this week’s Learning Resources and
consider the use of dummy variables.
Create a research question using the General Social Survey
dataset that can be answered by multiple regression. Using the SPSS software,
choose a categorical variable to dummy code as one of your predictor variables.
By Day 3
Estimate a multiple regression model that answers your
research question. Post your response to the following:
What is your research question?
Interpret the coefficients for the model, specifically
commenting on the dummy variable.
Run diagnostics for the regression model. Does the model
meet all of the assumptions? Be sure and comment on what assumptions were not
met and the possible implications. Is there any possible remedy for one the
assumption violations?
Be sure to support your Main Post and Response Post with
reference to the week’s Learning Resources and other scholarly evidence in APA
Style.
By Day 5
Respond to at least one of your colleagues’ posts and
provide a constructive comment on their assessment of diagnostics.
Were all assumptions tested for?
Are there some violations that the model might be robust
against? Why or why not?
Explain and provide any additional resources (i.e., web
links, articles, etc.) to provide your colleague with addressing diagnostic
issues.
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entering your message. Then click on the Submit button to post your message.
Week 11 discussion
Categorical Data Analysis
As with the previous week’s Discussion, this Discussion
assists in solidifying your understanding of statistical testing by engaging in
some data analysis. This week you will once again work with a real, secondary
dataset to construct a research question, perform categorical data analysis
that answers the question, and interpret the results.
Whether in a scholarly or practitioner setting, good
research and data analysis should have the benefit of peer feedback. For this
Discussion, you will post your response to the hypothesis test, along with the
results. Be sure and remember that the goal is to obtain constructive feedback
to improve the research and its interpretation, so please view this as an
opportunity to learn from one another.
To prepare for this Discussion:
Review Chapters 10 and 11 of the Frankfort-Nachmias &
Leon-Guerrero course text and the media program found in this week’s Learning
Resources related to bivariate categorical tests.
Create a research question using the General Social Survey
dataset that can be answered using categorical analysis.
By Day 3
Use SPSS to answer the research question. Post your response
to the following:
What is your research question?
What is the null hypothesis for your question?
What research design would align with this question?
What dependent variable was used and how is it measured?
What independent variable is used and how is it measured?
If you found significance, what is the strength of the
effect?
Explain your results for a lay audience and further explain
what the answer is to your research question.
Be sure to support your Main Post and Response Post with
reference to the week’s Learning Resources and other scholarly evidence in APA
Style.
By Day 5
Respond to at least one of your colleagues’ posts and
comment on the following:
Do you think the variables are appropriately used? Why or
why not?
Does the analysis answer the research question? Be sure and
provide constructive and helpful comments for possible improvement.
As a lay reader, were you able to understand the results and
their implications? Why or why not?
Click on the Reply button below to reveal the textbox for
entering your message. Then click on the Submit button to post your message.
