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Boston University Time Series in R Composition
This assignment provides practice in decomposing the seasonal time series data and then subtract that effect from the data ...
Boston University Time Series in R Composition
This assignment provides practice in decomposing the seasonal time series data and then subtract that effect from the data and then to show how to address issues of correlations between successive values of the time series. Before beginning this assignment, review the learning resources for this module, especially focus on Decomposing Time Series, Forecasting using Exponential Smoothing and ARIMA Models sections of A Little of R for Time Series by Avril Coghlan. Complete the following steps and write a report to record your work, results and analysis. You may use the attached data sets (average price data and NY benchmarked employment data) or one of time series data from data( ). Please note that some time series are more amenable to time series analysis than others.It is important that you understand data structure and be able to appropriately transform/clean raw data prior to analysis. "Average price data.xlsx" is in the long format. The data series are stacked on top of each other. That is how the data is provided the Bureau of Labor Statistics. The names of variables are provided in the "series" worksheet. You need to pick one series name and use it to filter or subset the data prior to analysis. Some series are better than others. You may want to use only the portions of the series after 2009, since the Great Recession was an one-time event that cannot be modeled.A. Decompose seasonal time series data and subtract that effect from the data:
Identify an appropriate time series data set, this can be a data set in R or a data set you find.
Then, use R to display decompose the seasonal time series and seasonally adjust to subtract the seasonal components from the time series.
In your report, provide insights to the results.
B. Address issues of correlations between successive values of the time series:
Identify an appropriate data set, this can be this can be a data set in R or a data set you find.
Then use R time series functions to address autocorrelation issues in data sets. In many cases you can make a better predictive model by taking correlations in the data into account. Address autocorrelation issues (irregular components of the time series) using a technique called ARIMA (Autoregressive Integrated Moving Average) models for irregular components of time series.
In your report, provide insights to the results.
Report Your assignment/project should have a good cover/title page, introduction of what the goals of the project and the methods you use. It also should follow APA format with at least 1000 words (excluding title page and references page) and references page. In the body of your project you should incorporate the R codes and R outputs with interpretation of your results. Finally, you need to make sense of your results to make good points with proper conclusions, to show your understanding of the course material and its application to the dataset. Graphs, figures, charts, tables are very useful to increase visual effects to impress your readers. You also should do your best to give insight and understanding to the project with a good conclusion. Please use subtitles to make your assignment more reader friendly as well.
Testing for Bivariate Categorical Analysis, statistics assignment help
Assignment: Testing for Bivariate Categorical AnalysisYou have had plenty of practice with data analysis in the Discussion ...
Testing for Bivariate Categorical Analysis, statistics assignment help
Assignment: Testing for Bivariate Categorical AnalysisYou have had plenty of practice with data analysis in the Discussions and hopefully you have received helpful and encouraging feedback from your colleagues. Now, for the last time in the course, it is time once again to put all of that good practice to use and answer a social research question using categorical statistical tools. As you begin the Assignment, be sure and pay close attention to the assumptions of the test. Specifically, make sure the variables are categorical level variables.For this Assignment, you will consider three different scenarios. Each of these scenarios include a research question. You will examine each scenario, choose a categorical data analysis and run a sample test.To prepare for this Assignment: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.Using the SPSS software, open the Afrobarometer dataset found in this week’s Learning Resources.Next, review the Chi Square Scenarios found in this week’s Learning Resources and consider each research scenario for this Assignment.Based on the dataset you chose and for each research scenario provided, using the SPSS software, choose a categorical data analysis and run a sample test.Once you perform your categorical data analysis, review Chapter 11 of the Wagner text to understand how to copy and paste your output into your Word document.For this Assignment:Write a 1- to 2-paragraph analysis of your categorical data results for each research scenario. In your analysis, display the data for the output. Based on your results, provide an explanation of what the implications of social change might be.Use proper APA format, citations, and referencing for your analysis, research question, and display of output.
Abcott Institute Module 8 Treating Depression Lab Part
Module 8 -
Treating Depression Lab Part 1 (discussion 1) - mod 8 group 1
From 2020SU-MATH-160-1774
11 unread reply. ...
Abcott Institute Module 8 Treating Depression Lab Part
Module 8 -
Treating Depression Lab Part 1 (discussion 1) - mod 8 group 1
From 2020SU-MATH-160-1774
11 unread reply.55 replies.
Learn by Doing
In this activity, you will investigate the first question
related to the study described below.
Some features of this activity may not work well on a cell phone
or tablet. We highly recommend that you complete this activity on a computer.
Here are the directions and grading rubric for
the Learn by Doing discussion board exercises.
A list of StatCrunch directions is
provided at the bottom of this page.
Context
Clinical depression is a recurrent illness
requiring treatment and often hospitalization. Nearly 50% of people who have an
episode of major depression will have a recurrence within 2-3 years. Being able
to prevent the recurrence of depression in people who are at risk for the
disease would go a long way to alleviate the pain and suffering of patients.
During the 1980's the federal government, through the National Institutes of
Health (NIH), sponsored a large clinical trial to evaluate two drugs for
depression. There were 3 treatment groups. Patients received either Imipramine
(Imip), Lithium (Li), or a Placebo (Pl). Researchers randomly assigned patients
to one of the 3 treatment groups and followed them for 2-4 years to track any
recurrences of depression.
(Prien et al., Archives of General Psychiatry, 1984).
Variables
·
Hospt: Which hospital the patient was from: Labeled
1, 2, 3, 5 or 6
·
Treat: 0=Lithium; 1=Imipramine; 2=Placebo
·
Outcome: 0=Success 1=Failure (recurrence of
depression)
·
Time: Number of weeks until a recurrence (if
outcome=1) or until study ended (if outcome=0)
·
AcuteT: How long the patient was depressed before
the start of the current study, measured in days
·
Age: Age in years
·
Gender: 1=Female 2=Male
Data
If you have not done so already, download
the depression datafile (as always, if a login box
opens, just close it and then download the file). Then upload the file in
StatCrunch.
Prompt
We will analyze the data to answer the 1st
research question: Which of the drugs (if either) was more successful
in preventing the recurrence of depression relative to the placebo?
In the previous lab-preparation activity, we determined that we
will analyze the data using a two-way table and conditional percentages.
1. Use StatCrunch to produce a two-way
contingency table. (directions)
Copy the table in your StatCrunch output window and paste it in your initial
discussion post. (directions)
After you paste the content of the your StatCrunch output window into your
discussion post, keep the table titled Contingency table results: and
delete the Chi-Square results: table.
2. Analyze the data in your two-way table by
finding appropriate conditional percentages. Write each
conditional percentage as a ratio (e.g. 25 out of 40) and as a percentage (e.g.
25/40 = 62.5%). Then write a sentence that explains the meaning of the
percentage in the context of the research question.
3. Draw a conclusion. Based on this study, which
drug was the most effective in preventing the recurrence of depression? Support
your conclusion using conditional percentages.
Top-Three Concepts or Skills
Top-Three Concepts or Skills" Please respond to the following:Note: Online students, please select one of the two subjects ...
Top-Three Concepts or Skills
Top-Three Concepts or Skills" Please respond to the following:Note: Online students, please select one of the two subjects to discuss.Determine the top-three (3) concepts or skills you learned in this course that you believe will be the most useful to you in your present or future professional career or education. Provide at least one (1) specific example to support your response. Provide a rationale as to why the three (3) aforementioned concepts or skills are important to someone in the field of business statistics.
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Most Popular Content
Boston University Time Series in R Composition
This assignment provides practice in decomposing the seasonal time series data and then subtract that effect from the data ...
Boston University Time Series in R Composition
This assignment provides practice in decomposing the seasonal time series data and then subtract that effect from the data and then to show how to address issues of correlations between successive values of the time series. Before beginning this assignment, review the learning resources for this module, especially focus on Decomposing Time Series, Forecasting using Exponential Smoothing and ARIMA Models sections of A Little of R for Time Series by Avril Coghlan. Complete the following steps and write a report to record your work, results and analysis. You may use the attached data sets (average price data and NY benchmarked employment data) or one of time series data from data( ). Please note that some time series are more amenable to time series analysis than others.It is important that you understand data structure and be able to appropriately transform/clean raw data prior to analysis. "Average price data.xlsx" is in the long format. The data series are stacked on top of each other. That is how the data is provided the Bureau of Labor Statistics. The names of variables are provided in the "series" worksheet. You need to pick one series name and use it to filter or subset the data prior to analysis. Some series are better than others. You may want to use only the portions of the series after 2009, since the Great Recession was an one-time event that cannot be modeled.A. Decompose seasonal time series data and subtract that effect from the data:
Identify an appropriate time series data set, this can be a data set in R or a data set you find.
Then, use R to display decompose the seasonal time series and seasonally adjust to subtract the seasonal components from the time series.
In your report, provide insights to the results.
B. Address issues of correlations between successive values of the time series:
Identify an appropriate data set, this can be this can be a data set in R or a data set you find.
Then use R time series functions to address autocorrelation issues in data sets. In many cases you can make a better predictive model by taking correlations in the data into account. Address autocorrelation issues (irregular components of the time series) using a technique called ARIMA (Autoregressive Integrated Moving Average) models for irregular components of time series.
In your report, provide insights to the results.
Report Your assignment/project should have a good cover/title page, introduction of what the goals of the project and the methods you use. It also should follow APA format with at least 1000 words (excluding title page and references page) and references page. In the body of your project you should incorporate the R codes and R outputs with interpretation of your results. Finally, you need to make sense of your results to make good points with proper conclusions, to show your understanding of the course material and its application to the dataset. Graphs, figures, charts, tables are very useful to increase visual effects to impress your readers. You also should do your best to give insight and understanding to the project with a good conclusion. Please use subtitles to make your assignment more reader friendly as well.
Testing for Bivariate Categorical Analysis, statistics assignment help
Assignment: Testing for Bivariate Categorical AnalysisYou have had plenty of practice with data analysis in the Discussion ...
Testing for Bivariate Categorical Analysis, statistics assignment help
Assignment: Testing for Bivariate Categorical AnalysisYou have had plenty of practice with data analysis in the Discussions and hopefully you have received helpful and encouraging feedback from your colleagues. Now, for the last time in the course, it is time once again to put all of that good practice to use and answer a social research question using categorical statistical tools. As you begin the Assignment, be sure and pay close attention to the assumptions of the test. Specifically, make sure the variables are categorical level variables.For this Assignment, you will consider three different scenarios. Each of these scenarios include a research question. You will examine each scenario, choose a categorical data analysis and run a sample test.To prepare for this Assignment: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.Using the SPSS software, open the Afrobarometer dataset found in this week’s Learning Resources.Next, review the Chi Square Scenarios found in this week’s Learning Resources and consider each research scenario for this Assignment.Based on the dataset you chose and for each research scenario provided, using the SPSS software, choose a categorical data analysis and run a sample test.Once you perform your categorical data analysis, review Chapter 11 of the Wagner text to understand how to copy and paste your output into your Word document.For this Assignment:Write a 1- to 2-paragraph analysis of your categorical data results for each research scenario. In your analysis, display the data for the output. Based on your results, provide an explanation of what the implications of social change might be.Use proper APA format, citations, and referencing for your analysis, research question, and display of output.
Abcott Institute Module 8 Treating Depression Lab Part
Module 8 -
Treating Depression Lab Part 1 (discussion 1) - mod 8 group 1
From 2020SU-MATH-160-1774
11 unread reply. ...
Abcott Institute Module 8 Treating Depression Lab Part
Module 8 -
Treating Depression Lab Part 1 (discussion 1) - mod 8 group 1
From 2020SU-MATH-160-1774
11 unread reply.55 replies.
Learn by Doing
In this activity, you will investigate the first question
related to the study described below.
Some features of this activity may not work well on a cell phone
or tablet. We highly recommend that you complete this activity on a computer.
Here are the directions and grading rubric for
the Learn by Doing discussion board exercises.
A list of StatCrunch directions is
provided at the bottom of this page.
Context
Clinical depression is a recurrent illness
requiring treatment and often hospitalization. Nearly 50% of people who have an
episode of major depression will have a recurrence within 2-3 years. Being able
to prevent the recurrence of depression in people who are at risk for the
disease would go a long way to alleviate the pain and suffering of patients.
During the 1980's the federal government, through the National Institutes of
Health (NIH), sponsored a large clinical trial to evaluate two drugs for
depression. There were 3 treatment groups. Patients received either Imipramine
(Imip), Lithium (Li), or a Placebo (Pl). Researchers randomly assigned patients
to one of the 3 treatment groups and followed them for 2-4 years to track any
recurrences of depression.
(Prien et al., Archives of General Psychiatry, 1984).
Variables
·
Hospt: Which hospital the patient was from: Labeled
1, 2, 3, 5 or 6
·
Treat: 0=Lithium; 1=Imipramine; 2=Placebo
·
Outcome: 0=Success 1=Failure (recurrence of
depression)
·
Time: Number of weeks until a recurrence (if
outcome=1) or until study ended (if outcome=0)
·
AcuteT: How long the patient was depressed before
the start of the current study, measured in days
·
Age: Age in years
·
Gender: 1=Female 2=Male
Data
If you have not done so already, download
the depression datafile (as always, if a login box
opens, just close it and then download the file). Then upload the file in
StatCrunch.
Prompt
We will analyze the data to answer the 1st
research question: Which of the drugs (if either) was more successful
in preventing the recurrence of depression relative to the placebo?
In the previous lab-preparation activity, we determined that we
will analyze the data using a two-way table and conditional percentages.
1. Use StatCrunch to produce a two-way
contingency table. (directions)
Copy the table in your StatCrunch output window and paste it in your initial
discussion post. (directions)
After you paste the content of the your StatCrunch output window into your
discussion post, keep the table titled Contingency table results: and
delete the Chi-Square results: table.
2. Analyze the data in your two-way table by
finding appropriate conditional percentages. Write each
conditional percentage as a ratio (e.g. 25 out of 40) and as a percentage (e.g.
25/40 = 62.5%). Then write a sentence that explains the meaning of the
percentage in the context of the research question.
3. Draw a conclusion. Based on this study, which
drug was the most effective in preventing the recurrence of depression? Support
your conclusion using conditional percentages.
Top-Three Concepts or Skills
Top-Three Concepts or Skills" Please respond to the following:Note: Online students, please select one of the two subjects ...
Top-Three Concepts or Skills
Top-Three Concepts or Skills" Please respond to the following:Note: Online students, please select one of the two subjects to discuss.Determine the top-three (3) concepts or skills you learned in this course that you believe will be the most useful to you in your present or future professional career or education. Provide at least one (1) specific example to support your response. Provide a rationale as to why the three (3) aforementioned concepts or skills are important to someone in the field of business statistics.
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