Working With Inferential Statistics
DNP 830 Topic 6 Working With Inferential Statistics GCU
DNP 830 Topic 6 Working With Inferential Statistics GCU
General Requirements:
This course helps you develop a basic understanding of statistics. Two distinct types of statistics are addressed: descriptive and inferential. In this assignment, you will have the opportunity to use the SPSS program. SPSS makes it easy to analyze data using specific tests. This assignment will give you practice with t-tests and ANOVA. Be sure to review the videos before undertaking this practice.
Use the following information to ensure successful completion of the assignment:
- For assistance with accessing SPSS, refer to the resources “How to Use SPSS From the GCU Server” and “How to Install SPSS on Your Computer.”
- Before beginning this assignment, be sure to view the tutorial videos provided as Topic Materials: (1) SPSS for Beginners 6a: One-Sample T-Tests and Confidence Intervals; (2) SPSS for Beginners 6c: Independent-Samples T-Tests and Confidence Intervals; (3) Oneway ANOVA – SPSS (Part 1); (4) ANOVA 1: Calculating SST (Total Sum of Squares); and (5) Introduction to Statistics: Inferential Statistics.
- Doctoral learners are required to use APA style for their writing assignments. The APA Style Guide is located in the Student Success Center.
- You are not required to submit this assignment to LopesWrite.
Directions:
Open SPSS and complete the following:
SPSS Output
Open SPSS and obtain an output (as in the tutorial videos) with the following results highlighted.
Have children exposed to movies created before 1980 caused more injuries than children exposed to movies after 1980?
Which group has caused more injuries: children exposed to movies created between 1937-1960, children exposed to movies created between 1961-1989, or children exposed to movies created between 1990-1999?
Determine the statistics using a one-tailed t-test (for question 1) and ANOVA (for question 2). Be sure to describe how you ensured that the assumptions for each test were met prior to doing the one-tailed t-test and ANOVA. Justify your choice with references.
Data Set:
“Data Set: Violence, Children, and Movies” is provided as a Topic Material.
Summary:
Write a 250-500 word summary of your results and how this statistical analysis may be applied to your prospectus. Use the “Working With Inferential Statistics Template” to present your data and embed the table in your paper. Include your SPSS output as an appendix in the paper.
DNP 830 Topic 7 Case Report What Does the Research Say? GCU
DNP 830 Topic 7 Case Report What Does the Research Say? GCU
General Requirements:
In this assignment, learners are required to write a case report. The report should demonstrate a depth and breadth of the knowledge and skills gained in the current course and potentially solve an identified real-world practice problem.
Use the following information to ensure successful completion of the assignment:
- Use at least two additional scholarly research sources published within the last 5 years. Provide citations and references for all sources used.
- Doctoral learners are required to use APA style for their writing assignments. The APA Style Guide is located in the Student Success Center.
- This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.
- You are required to submit this assignment to LopesWrite. Please refer to the directions in the Student Success Center.
Directions for Case Report What Does the Research Say? :
Identify a particular real-world problem using a PICOT template that you have used in previous courses. Include the particular clinical setting and potential health/disease issue you will examine. Identify and fully describe the research that has taken place within the last 5 years.
Your case report must include the following:
- Introduction with a problem statement.
- Brief synthesized review.
- Description of the case/situation/conditions.
- Proposed solutions describing the validity and reliability of the research you have read.
Portfolio Practice Hours:
Practice immersion assignments are based on your current course objectives and is application based learning using your real-world practice setting. These assignments earn practice immersion hours and are indicated in the syllabus by a Portfolio Practice Hours statement which reminds you, the learner, to enter in a corresponding case log in Typhon. Actual clock hours are entered, but the average hours associated with each practice immersion assignment is 10.
You are required to complete your assignment using real-world application. Real-world application requires the use of evidence-based data, contemporary theories, and concepts presented in the course. The culmination of your assignment must present a viable application in a current practice setting. For more information on parameters for practice immersion hours, please refer to DNP resources in the DC Network.
To earn portfolio practice hours, enter the following after the references section of your paper:
Practice Hours Completion Statement DNP-830
I, (INSERT NAME), verify that I have completed (NUMBER OF) clock hours in association with the goals and objectives for this assignment. I have also tracked said practice hours in the Typhon Student Tracking System for verification purposes and will be sure that all approvals are in place from my faculty and practice mentor.
Working With Inferential Statistics
In this blog post, we’ll be discussing inferential statistics and how you can use it to make better business decisions. Inferential statistics is a branch of statistics that deals with making predictions based on data. It’s often used in fields such as marketing and product development, where companies need to make decisions based on limited data sets. While inferential statistics can be complex, understanding the basics can help you make better-informed decisions in your business. In this post, we’ll cover the basics of inferential statistics and how you can use it in your business.
What is inferential statistics?
Inferential statistics are used to make predictions or conclusions about a population based on a sample. They allow us to test hypotheses and make estimations.
There are two main types of inferential statistics: parametric and nonparametric. Parametric methods assume that the data follows a certain type of distribution, such as a normal distribution. Nonparametric methods do not make any assumptions about the distribution of the data.
Some common parametric tests include t-tests, ANOVA, and regression analysis. Some common nonparametric tests include chi-squared tests and rank-order tests.
The different types of data
There are two types of data: quantitative and qualitative. Quantitative data is numerical and can be graphed and analyzed mathematically. Qualitative data is non-numerical and cannot be graphed or analyzed mathematically.
How to collect data
There are many ways to collect data, but some methods are more effective than others. Here are a few tips on how to collect data:
1. Use multiple methods of data collection. This will help you to get a more complete picture of the phenomenon you’re studying.
2. Make sure your data is representative of the population you’re interested in. This is especially important if you’re using inferential statistics, as you want your results to be generalizable to the population at large.
3. Pay attention to detail and accuracy. This is critical for all statistical analyses, but especially when you’re working with inferential statistics, as small errors can lead to big problems down the line.
4. Keep good records of your data collection process. This will help you (or someone else) to replicate your study, and it will also be helpful if you need to go back and check your work later on.
How to analyze data
When working with inferential statistics, it is important to first understand the data that you are working with. This means knowing what the data represents and how it was collected. Once you have a good understanding of the data, you can begin to analyze it.
There are many different ways to analyze data, but some of the most common methods include looking at descriptive statistics, performing tests of hypothesis, and creating models. Descriptive statistics can give you a basic overview of the data, while tests of hypothesis can help you test specific hypotheses about the data. Models can be used to predict future events or outcomes based on the data.
No matter which method you use to analyze your data, it is important to interpretation the results correctly. This means understanding what the results mean and how they can be applied to your research question or problem.
What are the results of inferential statistics?
The results of inferential statistics can be used to make predictions or estimates about a population based on a sample. This is done by using a variety of statistical techniques, such as estimation and hypothesis testing. The results of inferential statistics can be used to help make decisions about business, policy, and other areas where knowing the characteristics of a population is important.
How to use inferential statistics
In order to use inferential statistics, you will need to first collect data. This data can be collected through surveys, experiments, or observational studies. Once you have collected your data, you will need to clean it and organize it in a way that makes sense. After your data is organized, you will need to choose a statistical test to run on your data. The type of statistical test you choose will depend on the type of data you have collected and the question you are trying to answer. After you have chosen a statistical test, you will need to interpret the results of your test.
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