A campus physician surveyed 200 students (half male, half female) about their awareness of wellness workshops offered by the health center. More female students (80) reported being aware of the workshops compared to male students (30). A chi-square test can determine if this observed difference is statistically significant or likely due to chance. Chi-square is a nonparametric test that compares observed frequencies to expected frequencies without assumptions about the population distribution. It can be used to analyze categorical and ordinal data when parametric test assumptions are violated.
How to Know if a Quantitative Research Design Is Appropriate for Your StudyMaria Sanchez
Are you wondering what quantitative research design is best for your thesis/dissertation? This webinar will present several options and criteria to choose the most appropriate one.
The topics are:
* Characteristics of Quantitative Research
* When to Choose Quantitative Research
* Types of Quantitative Research Designs
* Description, Basic Diagram, and Threats to Validity of Each Type of Design
The Development of the Biostatistics & Clinical Epideimiolgy Skills (BACES) A...Pat Barlow
A poster based on my dissertation work developing a new biostatistics and clinical epidemiology skills self-assessment for medical residents. I used an Item Response Theory (IRT) approach to gather preliminary data on 30 multiple choice items that will eventually turn into an online self-assessment module for residents looking to hone their skills in these critical areas. The article is currently under review in Medical Teach, and I am looking for more sites / collaborators for expanding the instrument. Email if you're interested!
This is a lecture on "Hypothesis Testing, Research Questions and Choosing a Statistical Test". It was presented at the Colombo Institute for Research and Psychology. The lecture covers key topics including the different types of data, the process of testing a hypothesis, key forms of inferential statistical tests and how to chose a test based on your research question and sample.
This was a presentation that was carried out in our research method class by our group. It will be useful for PHD and master students quantitative and qualitative method. It consist sample definition, purpose of sampling, stages in the selection of a sample, types of sampling in quantitative researches, types of sampling in qualitative researches, and ethical Considerations in Data Collection.
How to Know if a Quantitative Research Design Is Appropriate for Your StudyMaria Sanchez
Are you wondering what quantitative research design is best for your thesis/dissertation? This webinar will present several options and criteria to choose the most appropriate one.
The topics are:
* Characteristics of Quantitative Research
* When to Choose Quantitative Research
* Types of Quantitative Research Designs
* Description, Basic Diagram, and Threats to Validity of Each Type of Design
The Development of the Biostatistics & Clinical Epideimiolgy Skills (BACES) A...Pat Barlow
A poster based on my dissertation work developing a new biostatistics and clinical epidemiology skills self-assessment for medical residents. I used an Item Response Theory (IRT) approach to gather preliminary data on 30 multiple choice items that will eventually turn into an online self-assessment module for residents looking to hone their skills in these critical areas. The article is currently under review in Medical Teach, and I am looking for more sites / collaborators for expanding the instrument. Email if you're interested!
This is a lecture on "Hypothesis Testing, Research Questions and Choosing a Statistical Test". It was presented at the Colombo Institute for Research and Psychology. The lecture covers key topics including the different types of data, the process of testing a hypothesis, key forms of inferential statistical tests and how to chose a test based on your research question and sample.
This was a presentation that was carried out in our research method class by our group. It will be useful for PHD and master students quantitative and qualitative method. It consist sample definition, purpose of sampling, stages in the selection of a sample, types of sampling in quantitative researches, types of sampling in qualitative researches, and ethical Considerations in Data Collection.
Experimental method of Educational Research.Neha Deo
experimental method is the most challenging method of the Educational research. In the experimental method different functional & factorial designs can be used. One has to think over the internal & external validity of the experiment also.In this presentation all these things are discussed in details.
Experimental Research Design - Meaning, Characteristics and ClassificationSundar B N
This ppt contains Experimental Research Design Which covers Meaning, Characteristics and Classification of Experimental Research Design.
Subscribe to Vision Academy
https://www.youtube.com/channel/UCjzpit_cXjdnzER_165mIiw
Comparing research designs fw 2013 handout versionPat Barlow
This is an updated version of my Comparing Research Designs lecture, which now includes discussions on: (1) common considerations with research design such as bias, reliability, validity, and confounding; and (2) expanded discussion of RCT designs including factorial and cross-over designs.
This presentation is related to tools of Educational Research. This presentation slides deals various tools of educational research likes rating scale, opionnaire, checklist, aptitude test, inventory, observation, interview, schedule etc. This presentation slides also describe the item analysis, steps for item analysis and online survey tools.
Experimental method of Educational Research.Neha Deo
experimental method is the most challenging method of the Educational research. In the experimental method different functional & factorial designs can be used. One has to think over the internal & external validity of the experiment also.In this presentation all these things are discussed in details.
Experimental Research Design - Meaning, Characteristics and ClassificationSundar B N
This ppt contains Experimental Research Design Which covers Meaning, Characteristics and Classification of Experimental Research Design.
Subscribe to Vision Academy
https://www.youtube.com/channel/UCjzpit_cXjdnzER_165mIiw
Comparing research designs fw 2013 handout versionPat Barlow
This is an updated version of my Comparing Research Designs lecture, which now includes discussions on: (1) common considerations with research design such as bias, reliability, validity, and confounding; and (2) expanded discussion of RCT designs including factorial and cross-over designs.
This presentation is related to tools of Educational Research. This presentation slides deals various tools of educational research likes rating scale, opionnaire, checklist, aptitude test, inventory, observation, interview, schedule etc. This presentation slides also describe the item analysis, steps for item analysis and online survey tools.
tests of significance in periodontics aspect, tests of significance with common examples, tests in brief, null hypothesis, parametric vs non parametric tests, seminar by sai lakshmi
Hypothesis testing and estimation are used to reach conclusions about a population by examining a sample of that population.
Hypothesis testing is widely used in medicine, dentistry, health care, biology and other fields as a means to draw conclusions about the nature of populations
Similar to Some nonparametric statistic for categorical & ordinal data (20)
Delivering Micro-Credentials in Technical and Vocational Education and TrainingAG2 Design
Explore how micro-credentials are transforming Technical and Vocational Education and Training (TVET) with this comprehensive slide deck. Discover what micro-credentials are, their importance in TVET, the advantages they offer, and the insights from industry experts. Additionally, learn about the top software applications available for creating and managing micro-credentials. This presentation also includes valuable resources and a discussion on the future of these specialised certifications.
For more detailed information on delivering micro-credentials in TVET, visit this https://tvettrainer.com/delivering-micro-credentials-in-tvet/
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
This slide is special for master students (MIBS & MIFB) in UUM. Also useful for readers who are interested in the topic of contemporary Islamic banking.
MATATAG CURRICULUM: ASSESSING THE READINESS OF ELEM. PUBLIC SCHOOL TEACHERS I...NelTorrente
In this research, it concludes that while the readiness of teachers in Caloocan City to implement the MATATAG Curriculum is generally positive, targeted efforts in professional development, resource distribution, support networks, and comprehensive preparation can address the existing gaps and ensure successful curriculum implementation.
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
Executive Directors Chat Leveraging AI for Diversity, Equity, and InclusionTechSoup
Let’s explore the intersection of technology and equity in the final session of our DEI series. Discover how AI tools, like ChatGPT, can be used to support and enhance your nonprofit's DEI initiatives. Participants will gain insights into practical AI applications and get tips for leveraging technology to advance their DEI goals.
Safalta Digital marketing institute in Noida, provide complete applications that encompass a huge range of virtual advertising and marketing additives, which includes search engine optimization, virtual communication advertising, pay-per-click on marketing, content material advertising, internet analytics, and greater. These university courses are designed for students who possess a comprehensive understanding of virtual marketing strategies and attributes.Safalta Digital Marketing Institute in Noida is a first choice for young individuals or students who are looking to start their careers in the field of digital advertising. The institute gives specialized courses designed and certification.
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2. Preliminary Information
• Chi-square test and others to be studied here
are much less complex than the inferential
tests treated already by us.
• Hypothesis testing but with different sorts of
data
• Nonparametric tests – questions that do not
lend themselves to analysis by the usual
inferential statistics
3. A Campus Physician
• A campus physician is interested in
determining whether male or female students
are equally aware that regular workshops on
wellness, fitness, and diet are offered by the
health center. She randomly samples 200
students (half male, half female) and asks
whether they are aware of these programs,
subsequently comparing the frequencies of
their responses. The data follows:
5. Frequencies
• Responses are readily categorized as raw
frequencies:
• “Yes, I know about the workshops“ or
• “No, I did not know about the workshops"
6. Observation
• A nonparametric test performed on such data
enables us to take any speculation a step
further, to consider whether the observed
pattern of responses is statistically valid (i.e.,
women are more aware of available campus
health initiatives than men).
8. Parametric Tests
• A parametric statistic is an inferential test that, prior to
its use, assumes that certain specific characteristics are
true of a population – particularly the shape of its
distribution – from which data are drawn for analysis.
• Parametric tests concern Population parameters such
as 𝜇, 𝜎 and making inferences about those parameters,
requiring that certain assumptions be met before they
can properly be used for data analysis.
• Bell-shape or normal distributions
• When a set of data are not normal in shape ( i.e., a
distribution is said to be skewed).
9. Nonparametric Tests
• A nonparametric statistic is an inferential test, one that
makes few or sometimes no assumptions regarding any
numerical data or the shape of the population from
which the observations were drawn.
• Known as “distribution-free tests of significance“
• Normality need not be met.
• Too few observation exist, a distribution is skewed.
• Parametric tests assumptions are violated
10. Advantages of Using Nonparametric
Tests
• 1. Nonparametric statistical tests are usually
“distribution free“
• 2. Nonparametric statistical tests can be used to
analyze data that are not precisely numerical.[
parametric use only interval and ratio scales
while nonparametric nominally scaled or rank,
that is, ordinally scaled ]
• 3. Nonparametric statistical tests are ideal for
analyzing data from small samples.
• Nonparametric statistical tests are generally easy
to calculate.
11. Disadvantages of Nonparametric Tests
• 1. Nonparametric tests are less statistically
powerful than parametric tests.
• 2. The scales of measurement analyzed by
nonparametric tests (i.e., chiefly nominal or
ordinal data) are less sensitive than those
analyzed by parametric tests (i.e., chiefly
interval and ratio data)
12. Research design Nominal data Ordinal data Parametric Tests
One sample X² goodness-of-fit --- One sample t or z test
Two independent samples X² test of Independ. Mann-Whitney U test Independent groups t test
Two dependent samples --- WilcoXon matched-pairs Dependent groups t test
signed-rank test
More than three Independ X² test of Indep. --- One-way ANOVA
samples
Correlation ----- Spearman rs Pearson r
Nonparametric Tests for
Research Designs and the Nonparametric and Parametric Tests Available to Analyze Their Data
13. Nonparametric Tests
• Nonparametric test used to analyze nominal
data basically infer whether the pattern
discerned across some number of categories is
anticipated by chance or not.
• When nonparametric tests are applied to
ordinal data, they are often used to discern
whether one sample of observations has
higher rankings than another sample.
14. The Chi-Square (X²) Test for Categorical
Data
• Categorical data – keeping track of
frequencies
• Frequencies refer to the number of
observations or items than can be
meaningfully grouped under some heading or
label.
• For example, “Are there more women over 6
feet than under that height in a sample"
15. Chi-Square (X² )
• Chi-Square (X²) compares observed
frequencies against expected frequencies.
• It also makes inference about the presence or
absence of some pattern. , “Are there more
women over 6 feet than under that height in a
sample"
16. Chi-Square (X² ) Statistical
Assumptions
• 1 Chi-Square (X² ) is not a single distribution but rather a collection
of similar curves, each of which is based on some number of
degrees of freedom.
• 2. Chi-Square (X² ) is similar to the t distribution in that it is based
on one degree of freedom value ( in contrast the F statistic is always
based on two separate degrees of freedom values.)
• 3. Chi-Square (X² ) need not be applied to data that conform to any
particular shape (i.e., normal distribution), though the observations
must be nominal.
• 4. Chi-Square (X² ) observations are randomly selected from some
larger population.
• 5. Chi-Square (X² ) number of expected observations within a given
category should be reasonably large. A good rule of thumb is to
have few (preferably no) categories with less than an expected
frequency of 5 observations in any given analysis.
17. The Chi-square Test for One-variable:
Goodness-of-Fit
• We work with Nominal data and therefore concentrate
on categories in order to explore the relative
frequencies or proportions present in some
distributions.
• Examples:
• A. How many experimental psychologists are males
rather than females?
• B. Of the four most popular majors at the college,
which one do sophomores choose most often?
• Here FREQUENCIES and COMPARISONS are made
based on how the observations are categorized.
• Statistical test is called Goodness of Fit
18. Goodness-of-Fit
• Using sample data, the Chi-square test for goodness-of-fit tests
whether obtained observations conform to or "fit" or diverge from
the population proportions specified by a null hypothesis.
• Goodness-of-fit points to the comparison of what pattern or
distribution of frequencies would be anticipated due to chance
versus the one that is actually obtained.
• When the fit between “observed“ and “expected“ observations is
good, then we know that the distribution of observation across the
available categories is more or less equal.
• When the discrepancy between observed and expected
observations is sufficiently large, however, then a significant
difference is likely to be found between or among the categories.
• The departure of observed from expected results means that the fit
is not " good,“ that some influential factors or factor is presumably
causing it.
19. Example to Illustrate
• A statistics instructor asks the 35 students in
her class to complete a standard course
evaluation. One of the key questions of
interest to this instructor was:
• "Statistic was my favorite class this semester.“
20. OBSERVED DATA
Strongly agree Agree Undecided Disagree Strongly disagree
17 8 3 2 5
"Statistic was my favorite class this semester.“ (N = 35)
Chi-square test statistic X² indicates whether there is a
difference between some observed set of frequencies – the
data drawn from a piece of research– and a set of expected
frequencies. These expected frequencies constitute the
predictions made under the null hypothesis.
21. Steps for Testing a Hypothesis Using a Nonparametric Test
1. Verify that the data are based on a Nominal or an ordinal
scale, not on an interval or a ratio scale
2. State the null (H0) and the alternative (H1) hypothesis
3. Select a significance level (p value or 𝛼 level) for the
nonparametric test.
4. Perform the analyses using the statistic, determining
whether to accept or reject (H0). Interpret and evaluate the
results in light of the hypothesis, and if necessary, go to
step 5.
5. Compute any supporting statistics
22. Chi-Square test for Goodness-of-Fit
• It involves: 2 forms
• No frequency difference among a set of
different categories
• No frequency difference from a comparison
population.
23. Chi-Square test for Goodness-of-Fit
• Ho: No difference in course ratings across the five rating categories ( i.e.,
strongly agree to strongly disagree )
• Because there are 35 students, the EXPECTED FREQUENCY for each
category when no difference exists would 7 (35 ÷
5 possible categories equals/ = 7 students in each one)
24. EXPECTED DATA UNDER H0
Strongly agree Agree Undecided Disagree Strongly Disagree
7 7 7 7 7
The general rule of thumb for determining the expected frequencies for the chi-
square test for goodness-of-fit test is simply dividing N by the number of
available categories.
The alternative hypothesis, then, is
H1: There is statistically reliable difference between the observed and
expected frequencies.
25. COMPARISON DATA UNDER H0
STRONGLY AGREE AGREE UNDECIDED DISAGREE STRONGLY DISAGREE
4 10 11 5 5
H0: No difference in course ratings from prior semester across
the five rating categories (i.e., strongly agree to strongly disagree)
H1: There is a statistically reliable difference between the
observed and the comparison frequencies.
27. Calculating X² Test Statistic Using a Tabular Format
fo fE (fo-fE) (fo-fE) ² (fo-fE)²/fE
Strongly agree 17 7
Agree 8 7
Uncertain 3 7
Disagree 2 7
Strongly disagree 5 7
Σfo = 35 ΣfE 35
Note: N = 35 (i.e., Σfo) respondents. These data are based on
hypothetical responses to the statement “Statistics was my
favorite class this semester.“
28. Chi-square (X²) = 20.86
Dfx = K-1 ( The original rating scale is based
on 5 categories, so the degree of freedom for
this X² test statistic are):
Dfx = 5-1
Dfx = 4.
X² (4, N = 35) = 20.86, p < .05 [APA Style]