Papers by Devendra pathak pathak
Statistical methods shows entire procedure by which entire behavior of a population are observed ... more Statistical methods shows entire procedure by which entire behavior of a population are observed in a representing sample from particular population. In wide and singular sense statistics refer to statistical methods. Generally scientists are not following Abstract censuses of populations, they preferred it as sampling. Increased demand in statistics and decreasing cost of statistics are main responsible factors for development of statistics .statistical methods are grouped under two heads statistics as a data, statistics as a Methods. Main originating source of statistics are Government records and Mathematic Therefore sampling and statistical inference are considered essential for required achievement. Making mistake in analytical works used in statistical methods is unavoidable. a important aspect of quality control is detection of random and systematic error . Care should be taken for ERROR,
ACCURACY, PRECISION and BIAS in statistical results
General principles for the planning of experiments and data visualization. Choice of standard statistical models and methods of statistical inference. (Binomial, Poisson, normal).Application of these models to confidence interval, estimation and parametric hypothesis testing including two-sample situations, the purpose is to compare two (or more) populations with methods using many randomly computer-generated samples are finally introduced for estimating characteristics of a distribution and for statistical respect to their means or variances. (2) Non-parametric inference tests are also described in cases where the data sample distribution is not compatible with standard parametric distributions. (3) Re sampling inference. The following section deals with methods for processing multivariate data. Methods for Dealing with clinical trials are also briefly reviewed.
What do you mean by Stock: A stock is a value on the company assets and earning profit and value,... more What do you mean by Stock: A stock is a value on the company assets and earning profit and value,. more stocks, earn by individual ownership stake in company becomes greater.
Drafts by Devendra pathak pathak
A pattern of learning by which the learners elicit the change, renewal, reorganization, and a ser... more A pattern of learning by which the learners elicit the change, renewal, reorganization, and a series of new questions This is the Learning in which the primary focus is on how information is structured and delivered outside the traditional role relationships seen in academic and experiential models of learning. NEED OF INNOVATIVE LEARNING Following points will describe the need for innovative learning 1 INDIVIDUAL GROWTH OF LEARNER: The learner needs to become self-regulated learners who are able to control their emotions and motivations during the study process, set goals, and monitor their own learning process. 2. LEARNING BY INTERACTION: we are social beings and we learn by interacting, collaborative group work can be good for all learners; it pushes people in different ways. 3 LEARNER EMOTIONS: Students understand ideas better when there's interplay between emotions, motivation and cognition, keeping students motivated should be the starting point of learning. Students should understand why it matters, learning becomes more important to them. 4 LEVEL OF LEARNER: every learner has a different level and innovative learning environments reflect the various experiences and prior knowledge that each student brings to class. 5 OVERLOADING OF LEARNER: Educators should try to prevent both coasting and overloading to the learner. Learners need to experience both academic success and the challenge of discovery. In a diverse classroom group work can help achieve this as a learner at different levels help one another. 6. LEARNER ASSESSMENT: Assessments of learner are important, but only to gauge how to structure the next lesson for maximum effectiveness. It should be meaningful, substantial, and shape the learning environment itself. Therefore we can say that assessment of learner is wide tools for innovation learning .different technology used to assess and evaluate the learner, which serves all three PURPOSE FORMATIVE, SUMMATIVE, ACCOUNTABILITY of assessment 7 REAL WORLD LEARNING: learner should be connected to reach out with real-world Learning can't be meaningful if students don't understand why the knowledge will be useful to them, how it can be applied in life. We should understand the connections between subjects and ideas. which is essential for the ability to transfer skills to learner. TECHNOLOGY for LEARNING ENVIRONMENTS: Educational institute is inherently bounded by management policies and structures to meet this challenge and opportunity for current operating in existing systems—can be quite difficult. For these educational institutions that wish to make advances in practice, new technologies and innovations can be critical levers for small changes that can ultimately lead to bigger change. Number web-based innovations that have become quite useful in the larger digital culture of our world fit into current curricular structures and programs, and are often free and easily accessible. Many technology-rich learning environments can be implemented. Leveraging many of these tools together produces a dramatically different educational climate. These technologies are blogs, wikis, digital portfolios, e-learning,
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Papers by Devendra pathak pathak
ACCURACY, PRECISION and BIAS in statistical results
General principles for the planning of experiments and data visualization. Choice of standard statistical models and methods of statistical inference. (Binomial, Poisson, normal).Application of these models to confidence interval, estimation and parametric hypothesis testing including two-sample situations, the purpose is to compare two (or more) populations with methods using many randomly computer-generated samples are finally introduced for estimating characteristics of a distribution and for statistical respect to their means or variances. (2) Non-parametric inference tests are also described in cases where the data sample distribution is not compatible with standard parametric distributions. (3) Re sampling inference. The following section deals with methods for processing multivariate data. Methods for Dealing with clinical trials are also briefly reviewed.
Drafts by Devendra pathak pathak
ACCURACY, PRECISION and BIAS in statistical results
General principles for the planning of experiments and data visualization. Choice of standard statistical models and methods of statistical inference. (Binomial, Poisson, normal).Application of these models to confidence interval, estimation and parametric hypothesis testing including two-sample situations, the purpose is to compare two (or more) populations with methods using many randomly computer-generated samples are finally introduced for estimating characteristics of a distribution and for statistical respect to their means or variances. (2) Non-parametric inference tests are also described in cases where the data sample distribution is not compatible with standard parametric distributions. (3) Re sampling inference. The following section deals with methods for processing multivariate data. Methods for Dealing with clinical trials are also briefly reviewed.