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Alok Shukla Wins Prestigious Goldman Environmental Prize 2024

why in the news? Chhattisgarh Bachao Andolan (CBA) chairman and environmentalist Alok Shukla has been chosen for the coveted Goldman Environmental Prize 2024, also referred to as the Green Nobel.  Highlights <ol style="text-align: left;"><li>Hasdeo Arand, one of the most thick forests in central India covering up to 170,000 hectares and includes 23 coal blocks, is one of the reasons he was chosen for his environmental protection efforts. He will be honored in the US.</li><li>In the tribal-dominated state of Chhattisgarh, he effectively fought against Adani mining to safeguard 445,000 acres of biodiversity-rich forests from 21 proposed coal mines.</li><li> Owing to its high forest cover, the environment ministry declared Hasdeo Arand to be a "No-Go" area for mining in 2009, however it was later allowed to resume mining. The CBA never stopped fighting to end Hasdeo Arand mining.</li></ol><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgYZxZGswj9hDNiJ6Wc5dp7FqSv3Fja-5E1RUvzdmwt8tYJDWUg7Wat1B257xZSnBM0kBC1Ij_RlLA_0jTaxzk7bRsNdzZ6Fv_BRQEcprQ7ky9SAaIyb1kkeBqzQOnXr7qyg6oWgzYVtV4maZQMQPewNRDfnmxZlvaAeJfsHdfkNqcX4Mf6J_JR_hcgHVA/s1116/Screenshot%202024-04-30%20at%2021-51-26%20The%20Goldman%20Environmental%20Prize.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="754" data-original-width="1116" height="432" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgYZxZGswj9hDNiJ6Wc5dp7FqSv3Fja-5E1RUvzdmwt8tYJDWUg7Wat1B257xZSnBM0kBC1Ij_RlLA_0jTaxzk7bRsNdzZ6Fv_BRQEcprQ7ky9SAaIyb1kkeBqzQOnXr7qyg6oWgzYVtV4maZQMQPewNRDfnmxZlvaAeJfsHdfkNqcX4Mf6J_JR_hcgHVA/w640-h432/Screenshot%202024-04-30%20at%2021-51-26%20The%20Goldman%20Environmental%20Prize.png" width="640" /></a></div><h3>Hasdeo Arand Forest</h3>
<ul style="list-style-type: square;"><li>Hasdeo Arand, a sprawling forest in the northern part of Chhattisgarh is known for its biodiversity and its coal deposits.</li><li>The forest falls under Korba, Sujapur and Surguja districts with significant tribal population.</li><li>The Hasdeo river, a tributary of Mahanadi, flows through it.</li><li>Hasdeo Arand is the largest un-fragmented forest in Central India consisting of pristine Sal (Shorea robusta) and teak forests.</li><li>It is a noted migratory corridor and has a significant presence of elephants.</li></ul>
<a href="http://drishtiias.com/images/uploads/1714471928_image1.png" rel="noopener" target="_blank"></a><h3 style="text-align: center;"> <a href="#"><img border="0" height="343" src="http://drishtiias.com/images/uploads/1714471928_image1.png" width="400" /></a></h3><h3>Green Nobel Prize</h3>
<ul style="list-style-type: square;"><li>The Goldman Environmental Prize (also known as Green Nobel Prize) recognizes individuals for sustained and significant efforts to protect and enhance the natural environment, often at great personal risk.</li><li>It has been awarded annually by the Goldman Environmental Foundation since 1990.</li><li>It honours people from the world’s six continental regions: Africa, Asia, Europe, Islands & Island Nations, North America, and South & Central America.</li><li>The Goldman Prize views “grassroots” leaders as 
those involved in local efforts, where positive change is created 
through community or citizen participation in the issues that affect 
them.</li><li>Goldman Prize recipients are usually people from isolated villages 
or inner cities who choose to take great personal risks to safeguard the
 environment.</li><li>The winners are announced on Earth Day which is observed on 22nd April every year.</li></ul> Official Website: https://www.goldmanprize.org/

current affairs environment Alok Shukla Wins Prestigious Goldman Environmental Prize 2024

why in the news? Chhattisgarh Bachao Andolan (CBA) chairman and environmentalist Alok Shukla has been chosen for the coveted Goldman Enviro...

Data Preparation – tools and graphs

28.4.24 dodda venkatareddy 0

Data preparation is the crucial first step before any analysis can occur. It involves cleaning, transforming, and organizing your data to ensure its accuracy and usability. Researchers use a variety of tools to tackle this task, depending on the complexity and size of their data. Here are some popular options: Spreadsheets: For smaller datasets, familiar programs like Microsoft Excel or Google Sheets can be sufficient for basic cleaning and organization. Self-service data preparation tools: These user-friendly tools offer a visual interface for data wrangling tasks like filtering, sorting, and merging data sets. Examples include Alteryx, Trifacta Wrangler, and Microsoft Power BI Prep. Programming languages: For complex datasets or when automation is desired, researchers might utilize Python with libraries like Pandas or R with packages like tidyverse for data manipulation. Graphs for Exploratory Data Analysis Once your data is prepared, creating graphs is a great way to explore it and identify patterns or trends. Here are some common graphs used in research: Histograms: Used to visualize the distribution of a continuous variable. They show the frequency of data points falling within specific ranges. Scatter plots: Used to explore the relationship between two continuous variables. Each point on the graph represents a single data point. Box and whisker plots: Useful for comparing distributions of a variable across different groups. They show the median, quartiles, and outliers of the data.Line plots: Used to show trends over time or depict changes in a variable across different categories.Bar charts: Effective for comparing categorical variables. The length or height of each bar represents the frequency of a particular category. These graphs are just a starting point, and researchers may use more specialized visualizations depending on their field and research question. By using a combination of data preparation tools and exploratory data analysis graphs, researchers can effectively transform raw data into a format that is ready for meaningful analysis and the generation of reliable research findings.

Research Methodology Data Preparation – tools and graphs

Data preparation is the crucial first step before any analysis can occur. It involves cleaning, transforming, and organizing your data to en...

Data Analysis and its role in research

28.4.24 dodda venkatareddy 0

<div style="text-align: justify;">Data analysis is the process of inspecting, cleaning, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. In research, data analysis plays a critical role in every step of the research process, from formulating a research question to drawing conclusions.</div><div style="text-align: justify;"> </div><div style="text-align: justify;">Here are some of the key ways that data analysis is used in research:  </div>Uncovering patterns and trends:Data analysis allows researchers to identify patterns and trends within their data. These patterns can help researchers to better understand the phenomenon they are investigating and to develop new hypotheses. Testing hypotheses: Research often begins with a hypothesis, which is a tentative explanation for a phenomenon. Data analysis is used to test these hypotheses and to determine whether they are supported by the evidence. Making informed conclusions: Data analysis helps researchers to draw meaningful conclusions from their research findings. These conclusions can be used to advance knowledge in a particular field of study and to inform practice. Enhancing data quality: Data analysis includes data cleaning and validation processes that improve the quality and reliability of the dataset. This is important because the quality of the data will ultimately affect the quality of the research findings. There are many different data analysis techniques that can be used in research, depending on the type of data being collected and the research question being asked. Some common data analysis techniques include: Statistical analysis: Statistical analysis is a branch of mathematics that is used to summarize, describe, and interpret data. Statistical techniques can be used to test hypotheses, identify relationships between variables, and make predictions. Content analysis: Content analysis is a technique used to analyze textual data. It can be used to identify patterns in the use of language, to understand the attitudes and beliefs of a group of people, or to track changes in public opinion over time. Qualitative data analysis: Qualitative data analysis is a broad term that refers to a variety of techniques used to analyze non-numerical data. This type of data can include interview transcripts, observations, and documents. The importance of data analysis in research cannot be overstated. By using data analysis techniques, researchers are able to extract meaningful information from their data and to use this information to answer important questions and advance knowledge.

Research Methodology Data Analysis and its role in research

Data analysis is the process of inspecting, cleaning, transforming, and modeling data with the goal of discovering useful information, infor...

Determining size of the sample- Factors to be consider

28.4.24 dodda venkatareddy 0

Students frequently ask about sample size in research methods, but the decision depends on various factors and there is no definitive answer. Decisions are often influenced by time and cost constraints, making them a compromise between precision, precision, and other considerations.<h4 style="text-align: left;">1.Absolute and Relative Sample Size in Research</h4><ul style="text-align: left;"><li>Absolute sample size is more important than relative size.</li><li>A national probability sample of 1,000 individuals in the UK has the same validity as a sample of 1,000 individuals in the USA, despite a larger population.</li><li>As sample size increases, the precision of a sample decreases, reducing the 95% confidence interval.</li><li>The less sampling error one is prepared to tolerate, the larger a sample will need to be.</li><li>Fowler (1993) warns against relying on a single estimate of a variable in decision-making about sample size.</li><li>Most survey research generates multiple estimates, not a single 'desired level of precision'.</li><li>The notion of using a desired level of precision as a factor in a decision about sample size is not realistic.</li></ul><h4 style="text-align: left;"> 2.Time and Cost in Sampling Size </h4><ul style="text-align: left;"><li>Larger sample sizes lead to greater precision due to less sampling error.</li><li>Gains in precision are noticeable up to a sample size of around 1,000.</li><li>Sharp increases in precision become less announced after a certain point, often in the region of 1,000.</li><li>A slowing-down in the extent to which precision increases and the extent to which the mean sample error of the mean declines.</li><li>Considerations of sampling size are profoundly affected by matters of time and cost, as striving for smaller increments of precision becomes increasingly uneconomical.</li></ul><h4 style="text-align: left;">3. Non-Response in Survey Research </h4><ul style="text-align: left;"><li>Non-response in survey surveys is a significant issue, with a 20% rate of non-response.</li><li>To ensure 450 employees are interviewed, it may be advisable to sample 540–550 individuals, with approximately 90 being non-respondents.</li><li>Non-response rates are declining in many countries, indicating a growing tendency towards people refusing to participate in survey research.</li><li>Business Week and a report from the Market Research Society’s Research and Development Committee in Britain have reported concerns about declining response rates.</li><li>T. W. Smith (1995) suggests no consistent evidence of such a decline, and it's difficult to separate general trends from variables like research subject matter, respondent type, and effort level.</li><li>Strategies to improve responses to survey instruments like structured interviews and postal questionnaire. </li></ul><h4 style="text-align: left;">4. Population Heterogeneity and Sample Size </h4><ul style="text-align: left;"><li>Heterogeneity of population affects sample size.</li><li>Highly heterogeneous samples, like entire countries or cities, show high variation.</li><li>Relatively homogeneous samples, like company members or occupations, show less variation.</li><li>Greater population heterogeneity necessitates larger sample sizes.</li></ul><h4 style="text-align: left;">5. Understanding the Type of Analysis</h4><ul style="text-align: left;"><li>Researchers should consider the type of analysis they plan to undertake.</li><li>A contingency table is a useful tool for illustrating the relationship between two variables.</li><li>For instance, a contingency table could show the variation in employee skill development and learning among the 100 largest UK companies.</li><li>The table would also reflect differences between companies representing the seventeen main SIC code sections.</li><li>However, the initial criterion of selecting the 100 largest companies may not represent all SIC sections, leading to empty cells.</li><li>To overcome this, the sample would need to reflect a wider range of public and private organizational activity.</li></ul>Some principles that influence sample size include: <ul style="text-align: left;"><li>The greater the dispersion or variance within the population, the larger the sample must be to provide estimation precision.</li><li>The greater the desired precision of the estimate, the larger the sample must be.</li><li>The narrower or smaller the error range, the larger the sample must be.</li><li> The higher the confidence level in the estimate, the larger the sample must be. </li><li>The greater the number of subgroups of interest within a sample, the greater the sample size must be,  as each subgroup must meet minimum sample size requirements.</li></ul><ul><li>Population: Population refers to a collection of 
items that share similar traits. It consists of a number of observations
 from which we hope to draw conclusions. A sample is the subset of the 
population.</li><li>Margin of Error: The margin of error is a statistic
 that describes how much random sampling error there is in experiment 
results. It establishes how far your sample mean can deviate from the 
population mean, either higher or lower. The margin of error is 
frequently stated as a percentage.</li><li>Confidence Level: The projected likelihood that a 
population estimate falls within a certain margin of error is known as 
the confidence level. In other words, it expresses your level of 
confidence that the real mean is within your margin of error. The three 
most popular levels of confidence are 90%, 95%, and 99%.</li><li>Degree of Variability: The degree of variability 
refers to how much the sample measurements vary from the population 
measure. The sample size should be increased as variation increases.</li><li>Sampling Method: The sample size depends on the 
sampling method used. For example, in simple random sampling, the sample
 size is typically determined by the desired level of precision and the 
size of the population. In stratified sampling, the sample size may be 
determined by the desired level of precision within each stratum, and 
the proportion of the population in each stratum. In cluster sampling, 
the sample size may be determined by the desired level of precision 
within each cluster, and the number of clusters selected. In general, 
larger sample sizes are needed for more precise estimates and for 
populations with greater variability</li></ul><h2>Sample Size Calculation Formula</h2>
The size of the sample is very important for getting accurate, 
statistically significant results and running your study successfully.
<ul style="margin-left: 40px;"><li>If your sample is too small, you risk including an excessive number 
(within the sample size) of people who are anomalies and outliers. You 
don't get a true representation of the entire population because these 
influence the results.</li><li>The study becomes complicated, expensive, and time-consuming to 
conduct if the sample is too large, and even though the results are more
 accurate, the advantages do not exceed the disadvantages.</li></ul>
In order to find the optimal sample size, we use two types of standard formulas:
<h3>For Small Sample Size</h3>
The T distribution notion is utilized in place of the normal 
distribution when there is a lower sample size. This distribution is 
specifically used when the sample size is less than 30. In this test, if
 the population variance is unknown and the sample size is small, we use
 the t statistic to test the null hypothesis using both one-tailed and 
two-tailed tests. Another name for it is an adjusted sample size.
<mi>A</mi><mo>=</mo><mfrac><mi>n</mi><mrow><mo stretchy="false">(</mo><mn>1</mn><mo>+</mo><mfrac><mrow><mo stretchy="false">(</mo><mi>n</mi><mo>&#x2013;</mo><mn>1</mn><mo stretchy="false">)</mo></mrow><mi>P</mi></mfrac><mo stretchy="false">)</mo></mrow></mfrac></math>" id="MathJax-Element-1-Frame" role="presentation" style="position: relative;" tabindex="0">A=n(1+(n–1)P)
where,
A is the adjusted sample size,
n is the sample size,
P is the population size.
<h3>For Large Sample Size</h3>
For infinite population size, the formula is expressed in terms of z-value and error margin.
Sample Size (n) = <mfrac><mrow><msup><mi>Z</mi><mn>2</mn></msup><mi>p</mi><mo stretchy="false">(</mo><mn>1</mn><mo>&#x2013;</mo><mi>p</mi><mo stretchy="false">)</mo></mrow><msup><mi>m</mi><mn>2</mn></msup></mfrac></math>" id="MathJax-Element-2-Frame" role="presentation" style="position: relative;" tabindex="0">Z2p(1–p)m2
Where,
n is the sample size,
Z is the z-value,
p is the proportion of population (generally taken as 0.5),
m is the margin of error.<h2>Solved Examples of Sample Size</h2>
Here are some solved examples on sample size for you to practice.
Solved Example 1: Calculate the sample if the z value is 3.2 and the margin of error is 3.2%.
Solution: We have,
z = 3.2
m = 3.2% = 0.032
p = 0.5
Using the formula we have,
<mi>N</mi><mo>=</mo><mfrac><mrow><msup><mi>Z</mi><mn>2</mn></msup><mi>p</mi><mo stretchy="false">(</mo><mn>1</mn><mo>&#x2013;</mo><mi>p</mi><mo stretchy="false">)</mo></mrow><msup><mi>m</mi><mn>2</mn></msup></mfrac></math>" id="MathJax-Element-4-Frame" role="presentation" style="position: relative;" tabindex="0">N=Z2p(1–p)m2
<mi>N</mi><mo>=</mo><mfrac><mrow><mo stretchy="false">(</mo><mn>3.2</mn><msup><mo stretchy="false">)</mo><mn>2</mn></msup><mo stretchy="false">(</mo><mn>0.5</mn><mo stretchy="false">)</mo><mo stretchy="false">(</mo><mn>1</mn><mo>&#x2013;</mo><mo stretchy="false">(</mo><mn>0.5</mn><mo stretchy="false">)</mo></mrow><mrow><mo stretchy="false">(</mo><mn>0.032</mn><msup><mo stretchy="false">)</mo><mn>2</mn></msup></mrow></mfrac></math>" id="MathJax-Element-5-Frame" role="presentation" style="position: relative;" tabindex="0">N=(3.2)2(0.5)(1–(0.5)(0.032)2
N = 2500
Solved Example 2: Calculate the z-value if the sample size is 3000 and the margin of error is 2.5%.
Solution: We have,
N = 295
m = 2.5% = 0.025
p = 0.5
Using the formula we have,
<mi>N</mi><mo>=</mo><mfrac><mrow><msup><mi>Z</mi><mn>2</mn></msup><mi>p</mi><mo stretchy="false">(</mo><mn>1</mn><mo>&#x2013;</mo><mi>p</mi><mo stretchy="false">)</mo></mrow><msup><mi>m</mi><mn>2</mn></msup></mfrac></math>" id="MathJax-Element-6-Frame" role="presentation" style="position: relative;" tabindex="0">N=Z2p(1–p)m2
Thus,
<msup><mi>Z</mi><mn>2</mn></msup><mo>=</mo><mfrac><mrow><mi>N</mi><mrow class="MJX-TeXAtom-ORD"><mo>&#x00D7;</mo></mrow><msup><mi>m</mi><mn>2</mn></msup></mrow><mrow><mo stretchy="false">(</mo><mi>p</mi><mo stretchy="false">(</mo><mn>1</mn><mo>&#x2013;</mo><mi>p</mi><mo stretchy="false">)</mo></mrow></mfrac></math>" id="MathJax-Element-7-Frame" role="presentation" style="position: relative;" tabindex="0">Z2=N×m2(p(1–p)
<msup><mi>Z</mi><mn>2</mn></msup><mo>=</mo><mfrac><mrow><mn>3000</mn><mrow class="MJX-TeXAtom-ORD"><mo>&#x00D7;</mo></mrow><mo stretchy="false">(</mo><mn>0.025</mn><msup><mo stretchy="false">)</mo><mn>2</mn></msup></mrow><mrow><mo stretchy="false">(</mo><mn>0.5</mn><mo stretchy="false">(</mo><mn>1</mn><mo>&#x2013;</mo><mn>0.5</mn><mo stretchy="false">)</mo></mrow></mfrac></math>" id="MathJax-Element-8-Frame" role="presentation" style="position: relative;" tabindex="0">Z2=3000×(0.025)2(0.5(1–0.5)
N = 7.5
Solved Example 3: Calculate the adjusted sample size for a sample size of 400 and a population of 60000.
Solution: We have,
n = 400
P = 60000
Using the formula we have,
<mi>A</mi><mo>=</mo><mfrac><mi>n</mi><mrow><mo stretchy="false">(</mo><mn>1</mn><mo>+</mo><mfrac><mrow><mo stretchy="false">(</mo><mi>n</mi><mo>&#x2013;</mo><mn>1</mn><mo stretchy="false">)</mo></mrow><mi>P</mi></mfrac><mo stretchy="false">)</mo></mrow></mfrac></math>" id="MathJax-Element-9-Frame" role="presentation" style="position: relative;" tabindex="0">A=n(1+(n–1)P)
<mi>A</mi><mo>=</mo><mfrac><mn>400</mn><mrow><mo stretchy="false">(</mo><mn>1</mn><mo>+</mo><mfrac><mrow><mo stretchy="false">(</mo><mn>400</mn><mo>&#x2013;</mo><mn>1</mn><mo stretchy="false">)</mo></mrow><mn>60000</mn></mfrac><mo stretchy="false">)</mo></mrow></mfrac></math>" id="MathJax-Element-10-Frame" role="presentation" style="position: relative;" tabindex="0">A=400(1+(400–1)60000)
A = 397.42

Research Methodology Determining size of the sample- Factors to be consider

Students frequently ask about sample size in research methods, but the decision depends on various factors and there is no definitive answe...

UGC NET June 2024 Online Application Started || Exam in Offline Mode

20.4.24 dodda venkatareddy 0

The National Testing Agency (NTA) on behalf of the University Grants Commission (UGC) is going to conduct the UGC NET June 2024 cycle exam scheduled on 16th June 2024. NTA released the tentative date for UGC NET 2024 through the NTA Provisional Exam Calendar 2024-25 and it will soon upload the UGC NET Notification 2024 at its official website for the candidates. This article provides the latest information on UGC NET Notification 2024 eligibility, exam patterns, and other details regarding the UGC NET Notification 2024.NTA UGC NET is a national-level exam conducted to apply for both 
Assistant Professor or Junior Research Fellowship (JRF) and Assistant 
Professor placements in Indian universities and colleges. UGC NET 2024 
will cover a total of 83 topics. Candidates must fill out the UGC NET 2024 application form to apply online for UGC NET 2024 exam.
 Only candidates who fill out the UGC NET 2024 application form 
successfully will be eligible to receive their UGC NET Admit Card 2024 
to the respective official website.Eligibility Criteria for UGC NET June 2024 Exam 
 
According to the announcements made by the UGC chief, candidates 
pursuing a Four Year/8 Semester Bachelor’s Degree Programme, including 
those in their final semester/year, are eligible to apply for the 
UGC-NET. Moreover, candidates with a Four-Year Bachelor’s Degree 
Programme can appear in a subject of their choice for Ph.D. regardless 
of the discipline of their bachelor’s degree.Mode of Examination for UGC NET June 2024 
 
The UGC NET June 2024 examination will be exclusively conducted in Offline OMR(Pen & Paper) mode across multiple shifts. It will comprise 
two papers, both featuring objective-type, multiple-choice questions. 
Candidates will be allotted a total duration of three hours for both 
papers, encompassing 150 questions in total. UGC NET June 2024 Important Dates<div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhNJTi3PSIhCuG3aG3B8yJHaUOtVirm0VbXWguSXI9Xy4NDPvFWFg1VbbVaj26UK1E19U69dP8E-281B3I3Vn3byCVl2xeECumLIpNFQJSgX8hzxdjHervThrTQM7ThZPyfCFSWCJB7FdtbzM2fEqkq6WX9KKtX2wtnsnHsFO_13Jk2-Oik0KH2bACykkw/s1002/Screenshot%202024-04-21%20074304.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="423" data-original-width="1002" height="270" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhNJTi3PSIhCuG3aG3B8yJHaUOtVirm0VbXWguSXI9Xy4NDPvFWFg1VbbVaj26UK1E19U69dP8E-281B3I3Vn3byCVl2xeECumLIpNFQJSgX8hzxdjHervThrTQM7ThZPyfCFSWCJB7FdtbzM2fEqkq6WX9KKtX2wtnsnHsFO_13Jk2-Oik0KH2bACykkw/w640-h270/Screenshot%202024-04-21%20074304.png" width="640" /></a></div>  Step-by-Step Guide to Applying for UGC NET June 2024 
<ol> <li>Visit the official website: ugcnet.nta.nic.in</li> <li>Click on the 'New Registration' button on the homepage to initiate the registration process.</li> <li>Log in using the provided registration credentials.</li> <li>A new window will appear, prompting you to fill out the application form.</li> <li>Upload the necessary documents as per the guidelines.</li> <li>Complete the payment of the application fee.</li> <li>Click on the Submit button to finalize your application.</li> <li>Remember to take a printout of the confirmation page for future reference.</li></ol><h2 style="text-align: left;"> UGC NET June 2024 Official Notification </h2><iframe height="650" src="https://drive.google.com/file/d/1xF4WRP4y5nBA1Lecc4eKsTq8FMqisrM7/preview" width="650"></iframe>

notifications UGC NET June 2024 Online Application Started || Exam in Offline Mode

The National Testing Agency (NTA) on behalf of the University Grants Commission (UGC) is going to conduct the UGC NET June 2024 cycle exam ...

APRCET-UGC-Net/JRF: Paper I Portal

Alok Shukla Wins Prestigious Goldman Environmental Prize 2024

Data Preparation – tools and graphs

Data Analysis and its role in research

Determining size of the sample- Factors to be consider

UGC NET June 2024 Online Application Started || Exam in Offline Mode

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