This document provides instruction on using the Mann-Whitney test to compare the medians of two independent samples. It discusses when to use the Mann-Whitney test, how to run it in Minitab, and provides an example comparing the medians of two columns of sample data labeled MetricC1 and MetricC2. The results of running the Mann-Whitney test on this example are interpreted to determine if the medians are statistically different between the two samples. The document encourages applying the test to factors identified in a previous lesson and discussing how the results could impact an organization.
Hypothesis Testing: Central Tendency – Normal (Compare 1:1)Matt Hansen
An extension on a series about hypothesis testing, this lesson reviews the 2 Sample T & Paired T tests as central tendency measurements for normal distributions.
Hypothesis Testing: Central Tendency – Non-Normal (Compare 1:Standard)Matt Hansen
An extension on hypothesis testing, this lesson reviews the 1 Sample Sign & Wilcoxon tests as central tendency measurements for non-normal distributions.
Hypothesis Testing: Central Tendency – Non-Normal (Compare 2+ Factors)Matt Hansen
An extension on hypothesis testing, this lesson reviews the Mood’s Median & Kruskal-Wallis tests as central tendency measurements for non-normal distributions.
Hypothesis Testing: Central Tendency – Normal (Compare 1:1)Matt Hansen
An extension on a series about hypothesis testing, this lesson reviews the 2 Sample T & Paired T tests as central tendency measurements for normal distributions.
Hypothesis Testing: Central Tendency – Non-Normal (Compare 1:Standard)Matt Hansen
An extension on hypothesis testing, this lesson reviews the 1 Sample Sign & Wilcoxon tests as central tendency measurements for non-normal distributions.
Hypothesis Testing: Central Tendency – Non-Normal (Compare 2+ Factors)Matt Hansen
An extension on hypothesis testing, this lesson reviews the Mood’s Median & Kruskal-Wallis tests as central tendency measurements for non-normal distributions.
Hypothesis Testing: Central Tendency – Normal (Compare 2+ Factors)Matt Hansen
An extension on a series about hypothesis testing, this lesson reviews the ANOVA test as a central tendency measurement for normal distributions. It also explains what residuals and boxplots are and how to use them with the ANOVA test.
An extension on hypothesis testing, this lesson introduces the concepts of a correlation and regression as part of measuring statistical relationships.
Dowhy: An end-to-end library for causal inferenceAmit Sharma
In addition to efficient statistical estimators of a treatment's effect, successful application of causal inference requires specifying assumptions about the mechanisms underlying observed data and testing whether they are valid, and to what extent. However, most libraries for causal inference focus only on the task of providing powerful statistical estimators. We describe DoWhy, an open-source Python library that is built with causal assumptions as its first-class citizens, based on the formal framework of causal graphs to specify and test causal assumptions. DoWhy presents an API for the four steps common to any causal analysis---1) modeling the data using a causal graph and structural assumptions, 2) identifying whether the desired effect is estimable under the causal model, 3) estimating the effect using statistical estimators, and finally 4) refuting the obtained estimate through robustness checks and sensitivity analyses. In particular, DoWhy implements a number of robustness checks including placebo tests, bootstrap tests, and tests for unoberved confounding. DoWhy is an extensible library that supports interoperability with other implementations, such as EconML and CausalML for the the estimation step.
Causal Inference in Data Science and Machine LearningBill Liu
Event: https://learn.xnextcon.com/event/eventdetails/W20042010
Video: https://www.youtube.com/channel/UCj09XsAWj-RF9kY4UvBJh_A
Modern machine learning techniques are able to learn highly complex associations from data, which has led to amazing progress in computer vision, NLP, and other predictive tasks. However, there are limitations to inference from purely probabilistic or associational information. Without understanding causal relationships, ML models are unable to provide actionable recommendations, perform poorly in new, but related environments, and suffer from a lack of interpretability.
In this talk, I provide an introduction to the field of causal inference, discuss its importance in addressing some of the current limitations in machine learning, and provide some real-world examples from my experience as a data scientist at Brex.
Assignment 2 Tests of SignificanceThroughout this assignment yo.docxrock73
Assignment 2: Tests of Significance
Throughout this assignment you will review mock studies. You will needs to follow the directions outlined in the section using SPSS and decide whether there is significance between the variables. You will need to list the five steps of hypothesis testing (as covered in the lesson for Week 6) to see how every question should be formatted. You will complete all of the problems. Be sure to cut and past the appropriate test result boxes from SPSS under each problem and explain what you will do with your research hypotheses. All calculations should be coming from your SPSS. You will need to submit the SPSS output file to get credit for this assignment. This file will save as a .spv file and will need to be in a single file. In other words, you are not allowed to submit more than one output file for this assignment.
The five steps of hypothesis testing when using SPSS are as follows:
1. State your research hypothesis (H1) and null hypothesis (H0).
2. Identify your confidence interval (.05 or .01)
3. Conduct your analysis using SPSS.
4. Look for the valid score for comparison. This score is usually under ‘Sig 2-tail’ or ‘Sig. 2’. We will call this “p”.
5. Compare the two and apply the following rule:
a. If “p” is < or = confidence interval, than you reject the null.
Be sure to explain to the reader what this means in regards to your study. (Ex: will you recommend counseling services?)
* Be sure that your answers are clearly distinguishable. Perhaps you bold your font or use a different color.
ASSIGNMENT 2(200) WORD MINIUM
1. They allow us to see if our relationship is "statistically significant". (Remember that this only shows us that there is or is not a relationship but does NOT show us if it is big, small, or in-between.)
2. It let's us know if our findings can be generalized to the population which our sample was selected from and represents.
This week you will decide which test of significance you will use for your project. For this class your choices for tests will include one of the following:
· Chi-square
· t Test
· ANOVA
We will be using a process for hypothesis testing which outlines five steps researchers can follow to complete this process:
1. Write your research hypothesis (H1) and your null hypothesis (H0).
2. Identify and record your confidence interval. These are usually .05 (95%) or .01 (99%).
3. Complete the test using SPSS.
4. Identify the number under Sig. (2-tail). This will be represented by "p".
5. Compare the numbers in steps 2 and 4 and apply the following rule:
1. If p < or = confidence interval, than you reject the null hypothesis
Determine what to do with your null and explain this to your reader. Be sure to go beyond the phrase "reject or fail to reject the null" and explain how that impacts your research and best describes the relationship between variables.
TEST QUESTIONS-NEED FULL ANSWERS
Q1
Make up and discuss research examples corresponding to the various ...
Hypothesis Testing: Central Tendency – Normal (Compare 2+ Factors)Matt Hansen
An extension on a series about hypothesis testing, this lesson reviews the ANOVA test as a central tendency measurement for normal distributions. It also explains what residuals and boxplots are and how to use them with the ANOVA test.
An extension on hypothesis testing, this lesson introduces the concepts of a correlation and regression as part of measuring statistical relationships.
Dowhy: An end-to-end library for causal inferenceAmit Sharma
In addition to efficient statistical estimators of a treatment's effect, successful application of causal inference requires specifying assumptions about the mechanisms underlying observed data and testing whether they are valid, and to what extent. However, most libraries for causal inference focus only on the task of providing powerful statistical estimators. We describe DoWhy, an open-source Python library that is built with causal assumptions as its first-class citizens, based on the formal framework of causal graphs to specify and test causal assumptions. DoWhy presents an API for the four steps common to any causal analysis---1) modeling the data using a causal graph and structural assumptions, 2) identifying whether the desired effect is estimable under the causal model, 3) estimating the effect using statistical estimators, and finally 4) refuting the obtained estimate through robustness checks and sensitivity analyses. In particular, DoWhy implements a number of robustness checks including placebo tests, bootstrap tests, and tests for unoberved confounding. DoWhy is an extensible library that supports interoperability with other implementations, such as EconML and CausalML for the the estimation step.
Causal Inference in Data Science and Machine LearningBill Liu
Event: https://learn.xnextcon.com/event/eventdetails/W20042010
Video: https://www.youtube.com/channel/UCj09XsAWj-RF9kY4UvBJh_A
Modern machine learning techniques are able to learn highly complex associations from data, which has led to amazing progress in computer vision, NLP, and other predictive tasks. However, there are limitations to inference from purely probabilistic or associational information. Without understanding causal relationships, ML models are unable to provide actionable recommendations, perform poorly in new, but related environments, and suffer from a lack of interpretability.
In this talk, I provide an introduction to the field of causal inference, discuss its importance in addressing some of the current limitations in machine learning, and provide some real-world examples from my experience as a data scientist at Brex.
Assignment 2 Tests of SignificanceThroughout this assignment yo.docxrock73
Assignment 2: Tests of Significance
Throughout this assignment you will review mock studies. You will needs to follow the directions outlined in the section using SPSS and decide whether there is significance between the variables. You will need to list the five steps of hypothesis testing (as covered in the lesson for Week 6) to see how every question should be formatted. You will complete all of the problems. Be sure to cut and past the appropriate test result boxes from SPSS under each problem and explain what you will do with your research hypotheses. All calculations should be coming from your SPSS. You will need to submit the SPSS output file to get credit for this assignment. This file will save as a .spv file and will need to be in a single file. In other words, you are not allowed to submit more than one output file for this assignment.
The five steps of hypothesis testing when using SPSS are as follows:
1. State your research hypothesis (H1) and null hypothesis (H0).
2. Identify your confidence interval (.05 or .01)
3. Conduct your analysis using SPSS.
4. Look for the valid score for comparison. This score is usually under ‘Sig 2-tail’ or ‘Sig. 2’. We will call this “p”.
5. Compare the two and apply the following rule:
a. If “p” is < or = confidence interval, than you reject the null.
Be sure to explain to the reader what this means in regards to your study. (Ex: will you recommend counseling services?)
* Be sure that your answers are clearly distinguishable. Perhaps you bold your font or use a different color.
ASSIGNMENT 2(200) WORD MINIUM
1. They allow us to see if our relationship is "statistically significant". (Remember that this only shows us that there is or is not a relationship but does NOT show us if it is big, small, or in-between.)
2. It let's us know if our findings can be generalized to the population which our sample was selected from and represents.
This week you will decide which test of significance you will use for your project. For this class your choices for tests will include one of the following:
· Chi-square
· t Test
· ANOVA
We will be using a process for hypothesis testing which outlines five steps researchers can follow to complete this process:
1. Write your research hypothesis (H1) and your null hypothesis (H0).
2. Identify and record your confidence interval. These are usually .05 (95%) or .01 (99%).
3. Complete the test using SPSS.
4. Identify the number under Sig. (2-tail). This will be represented by "p".
5. Compare the numbers in steps 2 and 4 and apply the following rule:
1. If p < or = confidence interval, than you reject the null hypothesis
Determine what to do with your null and explain this to your reader. Be sure to go beyond the phrase "reject or fail to reject the null" and explain how that impacts your research and best describes the relationship between variables.
TEST QUESTIONS-NEED FULL ANSWERS
Q1
Make up and discuss research examples corresponding to the various ...
Hypothesis Testing Definitions A statistical hypothesi.docxwilcockiris
Hypothesis Testing
Definitions:
A statistical hypothesis is a guess about a population parameter. The guess may or not be
true.
The null hypothesis, written H0, is a statistical hypothesis that states that there is no
difference between a parameter and a specific value, or that there is no difference between
two parameters.
The alternative hypothesis, written H1 or HA, is a statistical hypothesis that specifies a
specific difference between a parameter and a specific value, or that there is a difference
between two parameters.
Example 1:
A medical researcher is interested in finding out whether a new medication will have
undesirable side effects. She is particularly concerned with the pulse rate of patients who
take the medication. The research question is, will the pulse rate increase, decrease, or
remain the same after a patient takes the medication?
Since the researcher knows that the mean pulse rate for the population under study is 82
beats per minute, the hypotheses for this study are:
H0: µ = 82
HA: µ ≠ 82
The null hypothesis specifies that the mean will remain unchanged and the alternative
hypothesis states that it will be different. This test is called a two-tailed test since the
possible side effects could be to raise or lower the pulse rate. Notice that this is a non
directional hypothesis. The rejection region lies in both tails. We divide the alpha in two
and place half in each tail.
Example 2:
An entrepreneur invents an additive to increase the life of an automobile battery. If the
mean lifetime of the automobile battery is 36 months, then his hypotheses are:
H0: µ ≤ 36
HA: µ > 36
Here, the entrepreneur is only interested in increasing the lifetime of the batteries, so his
alternative hypothesis is that the mean is greater than 36 months. The null hypothesis is
that the mean is less than or equal to 36 months. This test is one-tailed since the interest
is only in an increased lifetime. Notice that the direction of the inequality in the alternate
hypothesis points to the right, same as the area of the curve that forms the rejection
region.
Example 3:
A landlord who wants to lower heating bills in a large apartment complex is considering
using a new type of insulation. If the current average of the monthly heating bills is $78,
his hypotheses about heating costs with the new insulation are:
H0: µ ≥ 78
HA: µ < 78
This test is also a one-tailed test since the landlord is interested only in lowering heating
costs. Notice that the direction of the inequality in the alternate hypothesis points to the
left, same as the area of the curve that forms the rejection region.
Study Design:
After stating the hypotheses, the researcher’s next step is to design the study. In designing
the study, the researcher selects an appropriate statistical test, chooses a level of
significance, and formulates a plan for conducting the study..
About CORE:
The Culture of Research and Education (C.O.R.E.) webinar series is spearheaded by Dr. Bernice B. Rumala, CORE Chair & Program Director of the Ph.D. in Health Sciences program in collaboration with leaders and faculty across all academic programs.
This innovative and wide-ranging series is designed to provide continuing education, skills-building techniques, and tools for academic and professional development. These sessions will provide a unique chance to build your professional development toolkit through presentations, discussions, and workshops with Trident’s world-class faculty.
For further information about CORE or to present, you may contact Dr. Bernice B. Rumala at Bernice.rumala@trident.edu
A detailed roadmap through the Control phase of the DMAIC methodology that navigates the user through the various tools and concepts for leading a Six Sigma project.
A detailed roadmap through the Improve phase of the DMAIC methodology that navigates the user through the various tools and concepts for leading a Six Sigma project.
Kseniya Leshchenko: Shared development support service model as the way to ma...Lviv Startup Club
Kseniya Leshchenko: Shared development support service model as the way to make small projects with small budgets profitable for the company (UA)
Kyiv PMDay 2024 Summer
Website – www.pmday.org
Youtube – https://www.youtube.com/startuplviv
FB – https://www.facebook.com/pmdayconference
Personal Brand Statement:
As an Army veteran dedicated to lifelong learning, I bring a disciplined, strategic mindset to my pursuits. I am constantly expanding my knowledge to innovate and lead effectively. My journey is driven by a commitment to excellence, and to make a meaningful impact in the world.
Putting the SPARK into Virtual Training.pptxCynthia Clay
This 60-minute webinar, sponsored by Adobe, was delivered for the Training Mag Network. It explored the five elements of SPARK: Storytelling, Purpose, Action, Relationships, and Kudos. Knowing how to tell a well-structured story is key to building long-term memory. Stating a clear purpose that doesn't take away from the discovery learning process is critical. Ensuring that people move from theory to practical application is imperative. Creating strong social learning is the key to commitment and engagement. Validating and affirming participants' comments is the way to create a positive learning environment.
VAT Registration Outlined In UAE: Benefits and Requirementsuae taxgpt
Vat Registration is a legal obligation for businesses meeting the threshold requirement, helping companies avoid fines and ramifications. Contact now!
https://viralsocialtrends.com/vat-registration-outlined-in-uae/
Affordable Stationery Printing Services in Jaipur | Navpack n PrintNavpack & Print
Looking for professional printing services in Jaipur? Navpack n Print offers high-quality and affordable stationery printing for all your business needs. Stand out with custom stationery designs and fast turnaround times. Contact us today for a quote!
Memorandum Of Association Constitution of Company.pptseri bangash
www.seribangash.com
A Memorandum of Association (MOA) is a legal document that outlines the fundamental principles and objectives upon which a company operates. It serves as the company's charter or constitution and defines the scope of its activities. Here's a detailed note on the MOA:
Contents of Memorandum of Association:
Name Clause: This clause states the name of the company, which should end with words like "Limited" or "Ltd." for a public limited company and "Private Limited" or "Pvt. Ltd." for a private limited company.
https://seribangash.com/article-of-association-is-legal-doc-of-company/
Registered Office Clause: It specifies the location where the company's registered office is situated. This office is where all official communications and notices are sent.
Objective Clause: This clause delineates the main objectives for which the company is formed. It's important to define these objectives clearly, as the company cannot undertake activities beyond those mentioned in this clause.
www.seribangash.com
Liability Clause: It outlines the extent of liability of the company's members. In the case of companies limited by shares, the liability of members is limited to the amount unpaid on their shares. For companies limited by guarantee, members' liability is limited to the amount they undertake to contribute if the company is wound up.
https://seribangash.com/promotors-is-person-conceived-formation-company/
Capital Clause: This clause specifies the authorized capital of the company, i.e., the maximum amount of share capital the company is authorized to issue. It also mentions the division of this capital into shares and their respective nominal value.
Association Clause: It simply states that the subscribers wish to form a company and agree to become members of it, in accordance with the terms of the MOA.
Importance of Memorandum of Association:
Legal Requirement: The MOA is a legal requirement for the formation of a company. It must be filed with the Registrar of Companies during the incorporation process.
Constitutional Document: It serves as the company's constitutional document, defining its scope, powers, and limitations.
Protection of Members: It protects the interests of the company's members by clearly defining the objectives and limiting their liability.
External Communication: It provides clarity to external parties, such as investors, creditors, and regulatory authorities, regarding the company's objectives and powers.
https://seribangash.com/difference-public-and-private-company-law/
Binding Authority: The company and its members are bound by the provisions of the MOA. Any action taken beyond its scope may be considered ultra vires (beyond the powers) of the company and therefore void.
Amendment of MOA:
While the MOA lays down the company's fundamental principles, it is not entirely immutable. It can be amended, but only under specific circumstances and in compliance with legal procedures. Amendments typically require shareholder
Unveiling the Secrets How Does Generative AI Work.pdfSam H
At its core, generative artificial intelligence relies on the concept of generative models, which serve as engines that churn out entirely new data resembling their training data. It is like a sculptor who has studied so many forms found in nature and then uses this knowledge to create sculptures from his imagination that have never been seen before anywhere else. If taken to cyberspace, gans work almost the same way.
Cracking the Workplace Discipline Code Main.pptxWorkforce Group
Cultivating and maintaining discipline within teams is a critical differentiator for successful organisations.
Forward-thinking leaders and business managers understand the impact that discipline has on organisational success. A disciplined workforce operates with clarity, focus, and a shared understanding of expectations, ultimately driving better results, optimising productivity, and facilitating seamless collaboration.
Although discipline is not a one-size-fits-all approach, it can help create a work environment that encourages personal growth and accountability rather than solely relying on punitive measures.
In this deck, you will learn the significance of workplace discipline for organisational success. You’ll also learn
• Four (4) workplace discipline methods you should consider
• The best and most practical approach to implementing workplace discipline.
• Three (3) key tips to maintain a disciplined workplace.
Discover the innovative and creative projects that highlight my journey throu...dylandmeas
Discover the innovative and creative projects that highlight my journey through Full Sail University. Below, you’ll find a collection of my work showcasing my skills and expertise in digital marketing, event planning, and media production.