This document discusses what constitutes a good hypothesis and research problem. It defines a hypothesis as a tentative statement about solving a problem. There are two types of hypotheses: the null hypothesis and alternative hypothesis. A good hypothesis has properties such as predictability, accuracy, simplicity, clarity, testability, relevance, specificity, consistency, and uses relevant techniques. It also defines a good research problem as one that is feasible, interesting, novel, ethical, and relevant. The document provides guidance on formulating strong hypotheses and defining worthwhile research problems to investigate.
Intuition. It's a crucial ability that often helps guide us when we make design choices. But what if our intuition — the gut feeling we have when it comes to deciding whether a choice is the right one or not — can be improved by using data and research? This talk cover how using tools like analytics and usability testing can help us to more accurately identify user problems and create proven designs that keep real people at the centre of the experience.
Intuition. It's a crucial ability that often helps guide us when we make design choices. But what if our intuition — the gut feeling we have when it comes to deciding whether a choice is the right one or not — can be improved by using data and research? This talk cover how using tools like analytics and usability testing can help us to more accurately identify user problems and create proven designs that keep real people at the centre of the experience.
Causal inference for complex exposures: asking questions that matter, getting...Ellie Murray
Slides from Dec 3, 2021 talk at University of Minnesota School of Public Health, Epidemiology department.
Lecture topic: how do we ask good causal questions & once we've got our questions framed, how do we answer them?
Lecture recording will be posted to YouTube - date tbd.
This PPT slide presentation deals with the Meaning of hypothesis, Types of hypothesis, Parameters of a good hypothesis, Importance of hypothesis, Source of hypothesis, Format of hypotheis & Formulation of testable hypothesis.
UNIT II - Identification of Problem & Review of Literature
Problems in research – identification of research problem,
Research objectives and Research Hypothesis,
Research question
Questionnaire and Interview Schedule.
Types of Research Application Exploratory Research Conclusive Research Correlation Research Explanatory (Causal / experimental) Research Comparison between exploratory, descriptive and causal Experimentation and Market Testing
Type of Information Sought Qualitative and Quantitative research Other types of Research Design Data: Primary and Secondary Data Data Collection and Method of study in research Content analysis Game or role-playing Primary Market Research Method Quantitative Experiments Quasi Experiment and Field Trials Sociogram Variable and their Types Sampling Methods a. Probability Sampling . Simple Random Sampling . Systematic Sampling:. Stratified random sampling . Cluster Sampling b. Non Probability Sampling . Convenience sampling . Purposive /Judgment Sampling . Snowball Sample Types of Errors: Measurement
Data Exploration Univariate vs. Bivariate Data Analysis of Variance (ANOVA) Problem Solving Central Tendency and Normal Distribution Normal Distribution Variance Effect Size Frequency distribution: Skewed, Mesokurtic, Leptokurtic, Platykurtic
Hypothesis Testing "True" Mean and Confidence Interval Margin of Error (Confidence Interval) Type I errors and type II errors One-Tailed and Two-Tailed Tests Parametric and Non-parametric Tests Bi- and Multivariate Inferential Statistical Tests (Parametric) Chi Square Degrees of freedom T-test Z-test and t-test Analysis of Variance (ANOVA) Correlation (measures relationships between two variables) Factor analysis Sign test Run Test Other data display methods
Experimental Design Pre-Experimental Designs Quasi experiment Design True Experimental Design Reliability and Validity Validity Research Requirements Steps of Research The Preliminary Section Research Ethics Seminar, Workshop, Conference, Symposium Paper, Article Quality of a research journal Style Rules Appendix : Research Methodology Diagram APA Format
Causal inference for complex exposures: asking questions that matter, getting...Ellie Murray
Slides from Dec 3, 2021 talk at University of Minnesota School of Public Health, Epidemiology department.
Lecture topic: how do we ask good causal questions & once we've got our questions framed, how do we answer them?
Lecture recording will be posted to YouTube - date tbd.
This PPT slide presentation deals with the Meaning of hypothesis, Types of hypothesis, Parameters of a good hypothesis, Importance of hypothesis, Source of hypothesis, Format of hypotheis & Formulation of testable hypothesis.
UNIT II - Identification of Problem & Review of Literature
Problems in research – identification of research problem,
Research objectives and Research Hypothesis,
Research question
Questionnaire and Interview Schedule.
Types of Research Application Exploratory Research Conclusive Research Correlation Research Explanatory (Causal / experimental) Research Comparison between exploratory, descriptive and causal Experimentation and Market Testing
Type of Information Sought Qualitative and Quantitative research Other types of Research Design Data: Primary and Secondary Data Data Collection and Method of study in research Content analysis Game or role-playing Primary Market Research Method Quantitative Experiments Quasi Experiment and Field Trials Sociogram Variable and their Types Sampling Methods a. Probability Sampling . Simple Random Sampling . Systematic Sampling:. Stratified random sampling . Cluster Sampling b. Non Probability Sampling . Convenience sampling . Purposive /Judgment Sampling . Snowball Sample Types of Errors: Measurement
Data Exploration Univariate vs. Bivariate Data Analysis of Variance (ANOVA) Problem Solving Central Tendency and Normal Distribution Normal Distribution Variance Effect Size Frequency distribution: Skewed, Mesokurtic, Leptokurtic, Platykurtic
Hypothesis Testing "True" Mean and Confidence Interval Margin of Error (Confidence Interval) Type I errors and type II errors One-Tailed and Two-Tailed Tests Parametric and Non-parametric Tests Bi- and Multivariate Inferential Statistical Tests (Parametric) Chi Square Degrees of freedom T-test Z-test and t-test Analysis of Variance (ANOVA) Correlation (measures relationships between two variables) Factor analysis Sign test Run Test Other data display methods
Experimental Design Pre-Experimental Designs Quasi experiment Design True Experimental Design Reliability and Validity Validity Research Requirements Steps of Research The Preliminary Section Research Ethics Seminar, Workshop, Conference, Symposium Paper, Article Quality of a research journal Style Rules Appendix : Research Methodology Diagram APA Format
hematic appreciation test is a psychological assessment tool used to measure an individual's appreciation and understanding of specific themes or topics. This test helps to evaluate an individual's ability to connect different ideas and concepts within a given theme, as well as their overall comprehension and interpretation skills. The results of the test can provide valuable insights into an individual's cognitive abilities, creativity, and critical thinking skills
Remote Sensing and Computational, Evolutionary, Supercomputing, and Intellige...University of Maribor
Slides from talk:
Aleš Zamuda: Remote Sensing and Computational, Evolutionary, Supercomputing, and Intelligent Systems.
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Inter-Society Networking Panel GRSS/MTT-S/CIS Panel Session: Promoting Connection and Cooperation
https://www.etran.rs/2024/en/home-english/
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana Luísa Pinho
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
DERIVATION OF MODIFIED BERNOULLI EQUATION WITH VISCOUS EFFECTS AND TERMINAL V...Wasswaderrick3
In this book, we use conservation of energy techniques on a fluid element to derive the Modified Bernoulli equation of flow with viscous or friction effects. We derive the general equation of flow/ velocity and then from this we derive the Pouiselle flow equation, the transition flow equation and the turbulent flow equation. In the situations where there are no viscous effects , the equation reduces to the Bernoulli equation. From experimental results, we are able to include other terms in the Bernoulli equation. We also look at cases where pressure gradients exist. We use the Modified Bernoulli equation to derive equations of flow rate for pipes of different cross sectional areas connected together. We also extend our techniques of energy conservation to a sphere falling in a viscous medium under the effect of gravity. We demonstrate Stokes equation of terminal velocity and turbulent flow equation. We look at a way of calculating the time taken for a body to fall in a viscous medium. We also look at the general equation of terminal velocity.
ESR spectroscopy in liquid food and beverages.pptxPRIYANKA PATEL
With increasing population, people need to rely on packaged food stuffs. Packaging of food materials requires the preservation of food. There are various methods for the treatment of food to preserve them and irradiation treatment of food is one of them. It is the most common and the most harmless method for the food preservation as it does not alter the necessary micronutrients of food materials. Although irradiated food doesn’t cause any harm to the human health but still the quality assessment of food is required to provide consumers with necessary information about the food. ESR spectroscopy is the most sophisticated way to investigate the quality of the food and the free radicals induced during the processing of the food. ESR spin trapping technique is useful for the detection of highly unstable radicals in the food. The antioxidant capability of liquid food and beverages in mainly performed by spin trapping technique.
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Sérgio Sacani
Since volcanic activity was first discovered on Io from Voyager images in 1979, changes
on Io’s surface have been monitored from both spacecraft and ground-based telescopes.
Here, we present the highest spatial resolution images of Io ever obtained from a groundbased telescope. These images, acquired by the SHARK-VIS instrument on the Large
Binocular Telescope, show evidence of a major resurfacing event on Io’s trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images
show that a plume deposit from a powerful eruption at Pillan Patera has covered part
of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io’s surface using adaptive
optics at visible wavelengths.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
Toxic effects of heavy metals : Lead and Arsenicsanjana502982
Heavy metals are naturally occuring metallic chemical elements that have relatively high density, and are toxic at even low concentrations. All toxic metals are termed as heavy metals irrespective of their atomic mass and density, eg. arsenic, lead, mercury, cadmium, thallium, chromium, etc.
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
The ability to recreate computational results with minimal effort and actionable metrics provides a solid foundation for scientific research and software development. When people can replicate an analysis at the touch of a button using open-source software, open data, and methods to assess and compare proposals, it significantly eases verification of results, engagement with a diverse range of contributors, and progress. However, we have yet to fully achieve this; there are still many sociotechnical frictions.
Inspired by David Donoho's vision, this talk aims to revisit the three crucial pillars of frictionless reproducibility (data sharing, code sharing, and competitive challenges) with the perspective of deep software variability.
Our observation is that multiple layers — hardware, operating systems, third-party libraries, software versions, input data, compile-time options, and parameters — are subject to variability that exacerbates frictions but is also essential for achieving robust, generalizable results and fostering innovation. I will first review the literature, providing evidence of how the complex variability interactions across these layers affect qualitative and quantitative software properties, thereby complicating the reproduction and replication of scientific studies in various fields.
I will then present some software engineering and AI techniques that can support the strategic exploration of variability spaces. These include the use of abstractions and models (e.g., feature models), sampling strategies (e.g., uniform, random), cost-effective measurements (e.g., incremental build of software configurations), and dimensionality reduction methods (e.g., transfer learning, feature selection, software debloating).
I will finally argue that deep variability is both the problem and solution of frictionless reproducibility, calling the software science community to develop new methods and tools to manage variability and foster reproducibility in software systems.
Exposé invité Journées Nationales du GDR GPL 2024
ANAMOLOUS SECONDARY GROWTH IN DICOT ROOTS.pptxRASHMI M G
Abnormal or anomalous secondary growth in plants. It defines secondary growth as an increase in plant girth due to vascular cambium or cork cambium. Anomalous secondary growth does not follow the normal pattern of a single vascular cambium producing xylem internally and phloem externally.
4. Origin of the word “Hypothesis”
◎ “Hypo” - tentative or subject for
verification.
◎ “Thesis” – solution of the problems.
◎ Tentative statement about the solution
of the problem.
5
5. Two types of Hypothesis:
◎ Hₒ - null hypothesis
◎ Ha
– Alternative hypothesis
6
vs
7. A Good Hypothesis
✔ Power of
prediction
✔ Accuracy to
observable
things
✔ Simplicity
✔ Clearness/
Clarity
✔ Testability
✔ Relevant
✔ Specific
✔ Use of relevant
techniques
✔ Consistency
8
8. What is the difference between power of prediction and
testability?
