The observation method is the most commonly used method for behavioral science studies. It involves direct observation by the investigator without asking questions of respondents. Some key advantages are that it obtains current information and is less demanding of respondent cooperation than interview methods. Common observation techniques include warranty card collection, pantry audits to understand consumer purchases, and distributor audits. Hypothesis testing is a key part of research and involves formally stating null and alternative hypotheses, selecting a significance level, choosing a statistical test, collecting a sample, calculating probabilities, and comparing to reject or fail to reject the null hypothesis.
Types of measurement scales in research methodologyManisha Mani
This document defines and describes the four main types of scales used in research methodology: nominal, ordinal, interval, and ratio scales. Nominal scales classify variables without numerical values. Ordinal scales arrange values in ascending or descending order. Interval scales assign unique values to each observation and measure equal intervals between values. Ratio scales have a true zero point below which no values exist, allowing the use of all mathematical operations. Each higher scale incorporates the properties of the lower scales but not vice versa. The scales are important for properly measuring and analyzing data in research.
The document outlines the typical structure of a research report, which consists of 7 components: 1) Abstract, 2) Introduction, 3) Literature Review, 4) Methods, 5) Results, 6) Conclusions, and 7) References. Each section serves a specific purpose, such as the abstract summarizing the main points, the introduction providing context and importance, the literature review summarizing prior research, and the methods, results, and conclusions sections describing the study. Proper formatting and inclusion of all relevant components is important for a high-quality research report.
The document defines inventory as assets held for sale, in production, or as supplies. It discusses two classes of inventory for manufacturers and traders. Inventory management aims to control ordering, storage, and stock levels. The economic order quantity model calculates the optimal order size to minimize total inventory costs, which are ordering costs and carrying costs. The formula, variables, and an example calculation are provided. Assumptions of the model and reorder point, which triggers reordering, are also explained.
This document outlines the objectives, methodology, and contents of a research project. The objectives are to learn literature survey skills, improve research presentation abilities, and understand research publication ethics. Key topics that will be covered include plagiarism, LaTeX, indexing databases, and evaluating publications. Students will gain experience conducting a literature review, selecting a project area, preparing reports and presentations, and attending special lectures. The overall goals are to enhance research skills and awareness of publishing standards.
This presentation discusses primary and secondary data collection methods. It begins by defining primary data as original data collected specifically for the research purpose, such as through surveys and interviews. Secondary data refers to data previously collected by others, such as published sources. Both data types are useful but have tradeoffs - primary data directly addresses the research question while secondary data is easier to obtain but may not be specific. The presentation provides examples of primary and secondary data collection techniques and their respective advantages and disadvantages.
The document outlines the key steps and concepts in research methodology. It discusses the meaning of research, objectives of research, different types of research approaches including quantitative and qualitative, the difference between basic and applied research, and the scientific method. The scientific method is described as having 7 steps: formulating a question, researching the question, forming a hypothesis, conducting an experiment, analyzing data, drawing conclusions, and communicating results.
Research meaning, Definition, Purpose, Objectives and Process.RajaKrishnan M
This document defines research and outlines the research methodology process. It states that research involves defining problems, formulating hypotheses, collecting and analyzing data, making deductions, reaching conclusions, and testing conclusions. Research is described as a systematic, formal, and rigorous process used to discover facts, relationships, and solutions to problems. The purpose of research is to gain solutions to problems through organized investigation with clearly defined objectives in order to obtain the right solution.
Criteria of selecting a sampling procedureDr.Sangeetha R
This document discusses the criteria for selecting a sampling procedure. There are two costs involved in sampling: the cost of data collection and the cost of incorrect inference from the data. Incorrect inferences can arise from either systematic bias or sampling error. Systematic bias results from errors in the sampling procedure and cannot be reduced by increasing sample size, while sampling error can be reduced by a larger sample. Sources of systematic bias include an inappropriate sampling frame, defective measuring devices, non-response bias, the indeterminacy principle, and natural bias in self-reported data.
Types of measurement scales in research methodologyManisha Mani
This document defines and describes the four main types of scales used in research methodology: nominal, ordinal, interval, and ratio scales. Nominal scales classify variables without numerical values. Ordinal scales arrange values in ascending or descending order. Interval scales assign unique values to each observation and measure equal intervals between values. Ratio scales have a true zero point below which no values exist, allowing the use of all mathematical operations. Each higher scale incorporates the properties of the lower scales but not vice versa. The scales are important for properly measuring and analyzing data in research.
The document outlines the typical structure of a research report, which consists of 7 components: 1) Abstract, 2) Introduction, 3) Literature Review, 4) Methods, 5) Results, 6) Conclusions, and 7) References. Each section serves a specific purpose, such as the abstract summarizing the main points, the introduction providing context and importance, the literature review summarizing prior research, and the methods, results, and conclusions sections describing the study. Proper formatting and inclusion of all relevant components is important for a high-quality research report.
The document defines inventory as assets held for sale, in production, or as supplies. It discusses two classes of inventory for manufacturers and traders. Inventory management aims to control ordering, storage, and stock levels. The economic order quantity model calculates the optimal order size to minimize total inventory costs, which are ordering costs and carrying costs. The formula, variables, and an example calculation are provided. Assumptions of the model and reorder point, which triggers reordering, are also explained.
This document outlines the objectives, methodology, and contents of a research project. The objectives are to learn literature survey skills, improve research presentation abilities, and understand research publication ethics. Key topics that will be covered include plagiarism, LaTeX, indexing databases, and evaluating publications. Students will gain experience conducting a literature review, selecting a project area, preparing reports and presentations, and attending special lectures. The overall goals are to enhance research skills and awareness of publishing standards.
This presentation discusses primary and secondary data collection methods. It begins by defining primary data as original data collected specifically for the research purpose, such as through surveys and interviews. Secondary data refers to data previously collected by others, such as published sources. Both data types are useful but have tradeoffs - primary data directly addresses the research question while secondary data is easier to obtain but may not be specific. The presentation provides examples of primary and secondary data collection techniques and their respective advantages and disadvantages.
The document outlines the key steps and concepts in research methodology. It discusses the meaning of research, objectives of research, different types of research approaches including quantitative and qualitative, the difference between basic and applied research, and the scientific method. The scientific method is described as having 7 steps: formulating a question, researching the question, forming a hypothesis, conducting an experiment, analyzing data, drawing conclusions, and communicating results.
Research meaning, Definition, Purpose, Objectives and Process.RajaKrishnan M
This document defines research and outlines the research methodology process. It states that research involves defining problems, formulating hypotheses, collecting and analyzing data, making deductions, reaching conclusions, and testing conclusions. Research is described as a systematic, formal, and rigorous process used to discover facts, relationships, and solutions to problems. The purpose of research is to gain solutions to problems through organized investigation with clearly defined objectives in order to obtain the right solution.
Criteria of selecting a sampling procedureDr.Sangeetha R
This document discusses the criteria for selecting a sampling procedure. There are two costs involved in sampling: the cost of data collection and the cost of incorrect inference from the data. Incorrect inferences can arise from either systematic bias or sampling error. Systematic bias results from errors in the sampling procedure and cannot be reduced by increasing sample size, while sampling error can be reduced by a larger sample. Sources of systematic bias include an inappropriate sampling frame, defective measuring devices, non-response bias, the indeterminacy principle, and natural bias in self-reported data.
This document outlines the contents and structure of a research report. It discusses that a research report is a detailed account of a disciplined study conducted to solve problems or reveal new knowledge. The key sections of a research report include an introduction stating the purpose and significance of the study, a literature review, methodology, data interpretation, conclusions and suggestions, bibliography, and appendices. Characteristics of a good report are that it is attractive, has a clear topic, uses balanced language, avoids repetition, and describes difficulties and shortcomings. The methodology section explains how primary and secondary data was collected and analyzed.
There are many different types of reports used across various fields. Technical reports provide detailed methods, assumptions, findings and supporting data. They are used when a full written report is required for record keeping or public dissemination. Popular reports emphasize simplicity, attractiveness, and policy implications over technical details. They use charts, diagrams and clear writing. Oral presentations can supplement written reports and allow for discussion, but lack a permanent record. Technical and popular reports vary in their structure, level of technical detail, and intended audience.
This document discusses primary and secondary data collection. It defines primary data as original data collected specifically for the current study, such as through surveys, experiments, or observations. Secondary data is data previously collected by someone else for another purpose, such as published reports or census data. Both primary and secondary data have advantages and disadvantages for research. Primary data allows targeted questions but is more expensive and time-consuming to collect, while secondary data is easier to obtain but may not be specific to the current study. Qualitative and quantitative research methods are discussed for primary data collection.
Plant layout refers to the arrangement of machines, materials, personnel and supporting services within a manufacturing facility. The objectives of plant layout include streamlining material flow, minimizing handling, maintaining process balance, and maximizing space and employee efficiency. There are four main types of layouts: product layout arranges machines in linear sequence to produce a single product; process layout groups similar machines together; combination layout blends aspects of product and process; and fixed position layout keeps large products stationary while bringing materials and machines to them. The document discusses the characteristics and suitability of each layout type.
Interpretation - Meaning, Techniques and PrecautionsSundar B N
This document provides a reference for a research methodology book titled "Research methodology: Methods and techniques" written by C. R. Kothari and published by New Age International in 2004. The book covers topics related to research methodology including methods and techniques used for conducting research.
The document outlines the key criteria for good research including:
1) Clearly stating the research aim and using common concepts
2) Adequately describing the research procedures to allow for replication
3) Carefully planning the research design to obtain objective results
It also describes the key qualities of good research as being systematic, following a specified sequence of steps; logical, guided by rules of reasoning; and empirical, dealing with concrete data to allow external validation of results.
The document outlines the 5 main steps in the sampling process:
1. Identify the target population that researchers want to generalize findings to.
2. Select a sampling frame which is a list of the population units to sample from.
3. Specify the sampling technique as either probability/random or non-probability/non-random.
4. Determine an appropriate sample size based on factors like time, cost and desired accuracy.
5. Execute the sampling plan by implementing the selection of the specific sample units.
The document outlines the steps and format for preparing a research report. It discusses that a research report involves several steps like logical analysis of the subject matter, preparing outlines and drafts, and rewriting. The main sections of a research report include an introduction, literature review, methodology, results, discussion, and conclusion. A research report should be objective, concise, and written in simple language. It should disseminate findings, examine the validity of conclusions, and inspire further research. The goal is to effectively communicate the research work to others.
This document outlines the steps for preparing a research report. It discusses including an introduction, objective methodology, summary of findings, main report with conclusions, and end matter with appendices, bibliography and index. The main text should present information in a logical sequence with sections. Charts and illustrations should only be used if they clearly present information. Calculated confidence limits and constraints must be stated. The purpose of the research report is to effectively communicate findings to others, as the research is not fully completed until the report is presented.
tribhuvan University
M.A population Studies
Research methods for population analysis
Data Processing, editing and coding
if any mistakes, suggest me to improve it.
thank you
hope its useful for all :)
The 7 step research process includes: 1) defining the research problem, 2) reviewing relevant literature, 3) formulating testable hypotheses, 4) designing the research methodology, 5) collecting primary data through methods like surveys and interviews, 6) analyzing the collected data, and 7) interpreting the findings and reporting the results. The overall goal is to gather information to initiate, modify, or terminate investments or projects through a systematic process of exploring an issue, collecting evidence, and drawing conclusions.
This document provides an overview of inventory management techniques. It begins with defining inventory and its objectives. It then covers various inventory analysis methods like ABC analysis, which categorizes inventory items into A, B and C based on their value and demand. Other techniques discussed include FSN analysis to classify items based on consumption pattern, and make or buy decision analysis to determine whether to manufacture or outsource items. The document aims to explain key inventory management strategies and analysis methods used by companies.
This document discusses various sampling designs and their characteristics. It describes probability sampling designs like simple random sampling which gives every unit an equal chance of selection. It also describes non-probability sampling designs like purposive sampling which involves deliberately choosing units. Specific probability designs discussed include systematic sampling, stratified sampling, cluster sampling, area sampling, and multi-stage sampling.
Characteristics of a good sample design & types of sample designDr.Sangeetha R
The document discusses different types of sample designs, including their key characteristics and differences. It covers non-probability sampling designs like purposive sampling which rely on researcher judgement, and probability sampling designs like simple random sampling where every item has an equal chance of selection. Probability sampling is preferred because it allows estimating sampling errors and significance of results.
Methods of data collection (research methodology)Muhammed Konari
Included all types of data collection.Includes primary data collection and secondary data collection. Described each and every classification of Data collections which are included in KTU Kerala.
A research report is a condensed form of a brief description of research work done by the researcher. It involves several steps to present the report in the form of a thesis or dissertation. The purpose of a research report is to present at conferences, publish in journals or articles, and obtain grants or financial aid. It can also have implications or recommendations for clinical practice, education, and administration. A research report should be concise, clear, honest, and complete while maintaining accuracy. It must also show originality and provide ready availability of findings.
The document outlines 7 criteria for good scientific research:
1. The purpose and concepts should be clearly defined.
2. The research procedures should be described in detail so others can repeat the work.
3. The design should plan for objective results.
4. Any flaws in the design or their effects should be reported honestly.
It also lists 4 key qualities of good research: it is systematic, logical, empirical, and replicable.
This document discusses inventory management techniques. It begins by explaining that inventory is a significant current asset that requires management to avoid unnecessary investment of funds. It then defines inventory control measures like order size, safety stock, and reorder points. It discusses the different types of inventories and the various reasons companies hold inventory. The objectives and techniques of effective inventory management are outlined, including determining economic order quantity and reorder points. ABC analysis is presented as a case study, classifying inventory into categories based on value to prioritize control efforts.
This document provides guidance on writing a research report. It discusses the significance of report writing, outlines the key steps in the process which include logical analysis, preparing an outline and rough draft, and rewriting. It also describes the typical layout of a research report, which includes preliminary pages, the main text with sections on introduction, findings, results, implications and summary, and end materials like appendices and bibliography. The main text aims to communicate research findings and solve problems by presenting details in a clear, objective and concise manner.
The document discusses various aspects of media research methodology. It outlines the steps involved including defining the research problem, developing objectives and hypotheses, reviewing literature, deciding the research design, collecting and analyzing data, and developing conclusions. It also discusses different research approaches and methods that can be used including experimental, exploratory, descriptive, case studies, surveys, and content analysis. The key aspects of ensuring rigorous media research are emphasized.
This document discusses the processing and analysis of collected data in research. It defines processing as editing, coding, classification and tabulation of data to prepare it for analysis. Analysis is defined as identifying patterns and relationships in the data and testing hypotheses. The document then outlines specific processing operations including editing collected data, coding responses numerically or symbolically, and classifying data into groups based on common attributes or quantitative values. It emphasizes the importance of processing data systematically and accurately for meaningful analysis and conclusions.
This document outlines the contents and structure of a research report. It discusses that a research report is a detailed account of a disciplined study conducted to solve problems or reveal new knowledge. The key sections of a research report include an introduction stating the purpose and significance of the study, a literature review, methodology, data interpretation, conclusions and suggestions, bibliography, and appendices. Characteristics of a good report are that it is attractive, has a clear topic, uses balanced language, avoids repetition, and describes difficulties and shortcomings. The methodology section explains how primary and secondary data was collected and analyzed.
There are many different types of reports used across various fields. Technical reports provide detailed methods, assumptions, findings and supporting data. They are used when a full written report is required for record keeping or public dissemination. Popular reports emphasize simplicity, attractiveness, and policy implications over technical details. They use charts, diagrams and clear writing. Oral presentations can supplement written reports and allow for discussion, but lack a permanent record. Technical and popular reports vary in their structure, level of technical detail, and intended audience.
This document discusses primary and secondary data collection. It defines primary data as original data collected specifically for the current study, such as through surveys, experiments, or observations. Secondary data is data previously collected by someone else for another purpose, such as published reports or census data. Both primary and secondary data have advantages and disadvantages for research. Primary data allows targeted questions but is more expensive and time-consuming to collect, while secondary data is easier to obtain but may not be specific to the current study. Qualitative and quantitative research methods are discussed for primary data collection.
Plant layout refers to the arrangement of machines, materials, personnel and supporting services within a manufacturing facility. The objectives of plant layout include streamlining material flow, minimizing handling, maintaining process balance, and maximizing space and employee efficiency. There are four main types of layouts: product layout arranges machines in linear sequence to produce a single product; process layout groups similar machines together; combination layout blends aspects of product and process; and fixed position layout keeps large products stationary while bringing materials and machines to them. The document discusses the characteristics and suitability of each layout type.
Interpretation - Meaning, Techniques and PrecautionsSundar B N
This document provides a reference for a research methodology book titled "Research methodology: Methods and techniques" written by C. R. Kothari and published by New Age International in 2004. The book covers topics related to research methodology including methods and techniques used for conducting research.
The document outlines the key criteria for good research including:
1) Clearly stating the research aim and using common concepts
2) Adequately describing the research procedures to allow for replication
3) Carefully planning the research design to obtain objective results
It also describes the key qualities of good research as being systematic, following a specified sequence of steps; logical, guided by rules of reasoning; and empirical, dealing with concrete data to allow external validation of results.
The document outlines the 5 main steps in the sampling process:
1. Identify the target population that researchers want to generalize findings to.
2. Select a sampling frame which is a list of the population units to sample from.
3. Specify the sampling technique as either probability/random or non-probability/non-random.
4. Determine an appropriate sample size based on factors like time, cost and desired accuracy.
5. Execute the sampling plan by implementing the selection of the specific sample units.
The document outlines the steps and format for preparing a research report. It discusses that a research report involves several steps like logical analysis of the subject matter, preparing outlines and drafts, and rewriting. The main sections of a research report include an introduction, literature review, methodology, results, discussion, and conclusion. A research report should be objective, concise, and written in simple language. It should disseminate findings, examine the validity of conclusions, and inspire further research. The goal is to effectively communicate the research work to others.
This document outlines the steps for preparing a research report. It discusses including an introduction, objective methodology, summary of findings, main report with conclusions, and end matter with appendices, bibliography and index. The main text should present information in a logical sequence with sections. Charts and illustrations should only be used if they clearly present information. Calculated confidence limits and constraints must be stated. The purpose of the research report is to effectively communicate findings to others, as the research is not fully completed until the report is presented.
tribhuvan University
M.A population Studies
Research methods for population analysis
Data Processing, editing and coding
if any mistakes, suggest me to improve it.
thank you
hope its useful for all :)
The 7 step research process includes: 1) defining the research problem, 2) reviewing relevant literature, 3) formulating testable hypotheses, 4) designing the research methodology, 5) collecting primary data through methods like surveys and interviews, 6) analyzing the collected data, and 7) interpreting the findings and reporting the results. The overall goal is to gather information to initiate, modify, or terminate investments or projects through a systematic process of exploring an issue, collecting evidence, and drawing conclusions.
This document provides an overview of inventory management techniques. It begins with defining inventory and its objectives. It then covers various inventory analysis methods like ABC analysis, which categorizes inventory items into A, B and C based on their value and demand. Other techniques discussed include FSN analysis to classify items based on consumption pattern, and make or buy decision analysis to determine whether to manufacture or outsource items. The document aims to explain key inventory management strategies and analysis methods used by companies.
This document discusses various sampling designs and their characteristics. It describes probability sampling designs like simple random sampling which gives every unit an equal chance of selection. It also describes non-probability sampling designs like purposive sampling which involves deliberately choosing units. Specific probability designs discussed include systematic sampling, stratified sampling, cluster sampling, area sampling, and multi-stage sampling.
Characteristics of a good sample design & types of sample designDr.Sangeetha R
The document discusses different types of sample designs, including their key characteristics and differences. It covers non-probability sampling designs like purposive sampling which rely on researcher judgement, and probability sampling designs like simple random sampling where every item has an equal chance of selection. Probability sampling is preferred because it allows estimating sampling errors and significance of results.
Methods of data collection (research methodology)Muhammed Konari
Included all types of data collection.Includes primary data collection and secondary data collection. Described each and every classification of Data collections which are included in KTU Kerala.
A research report is a condensed form of a brief description of research work done by the researcher. It involves several steps to present the report in the form of a thesis or dissertation. The purpose of a research report is to present at conferences, publish in journals or articles, and obtain grants or financial aid. It can also have implications or recommendations for clinical practice, education, and administration. A research report should be concise, clear, honest, and complete while maintaining accuracy. It must also show originality and provide ready availability of findings.
The document outlines 7 criteria for good scientific research:
1. The purpose and concepts should be clearly defined.
2. The research procedures should be described in detail so others can repeat the work.
3. The design should plan for objective results.
4. Any flaws in the design or their effects should be reported honestly.
It also lists 4 key qualities of good research: it is systematic, logical, empirical, and replicable.
This document discusses inventory management techniques. It begins by explaining that inventory is a significant current asset that requires management to avoid unnecessary investment of funds. It then defines inventory control measures like order size, safety stock, and reorder points. It discusses the different types of inventories and the various reasons companies hold inventory. The objectives and techniques of effective inventory management are outlined, including determining economic order quantity and reorder points. ABC analysis is presented as a case study, classifying inventory into categories based on value to prioritize control efforts.
This document provides guidance on writing a research report. It discusses the significance of report writing, outlines the key steps in the process which include logical analysis, preparing an outline and rough draft, and rewriting. It also describes the typical layout of a research report, which includes preliminary pages, the main text with sections on introduction, findings, results, implications and summary, and end materials like appendices and bibliography. The main text aims to communicate research findings and solve problems by presenting details in a clear, objective and concise manner.
The document discusses various aspects of media research methodology. It outlines the steps involved including defining the research problem, developing objectives and hypotheses, reviewing literature, deciding the research design, collecting and analyzing data, and developing conclusions. It also discusses different research approaches and methods that can be used including experimental, exploratory, descriptive, case studies, surveys, and content analysis. The key aspects of ensuring rigorous media research are emphasized.
This document discusses the processing and analysis of collected data in research. It defines processing as editing, coding, classification and tabulation of data to prepare it for analysis. Analysis is defined as identifying patterns and relationships in the data and testing hypotheses. The document then outlines specific processing operations including editing collected data, coding responses numerically or symbolically, and classifying data into groups based on common attributes or quantitative values. It emphasizes the importance of processing data systematically and accurately for meaningful analysis and conclusions.
Research design decisions and be competent in the process of reliable data co...Stats Statswork
Research Design may be described as the researchers scheme of outlining the flow of his project. It is based on research design, that the researcher goes about gathering data to answer his research question. It enables the researcher to prioritize his work, create better questionnaires and arrive at conclusions with greater clarity. Statswork offers statistical services as per the requirements of the customers. When you Order statistical Services at Statswork, we promise you the following – Always on Time, outstanding customer support, and High-quality Subject Matter Experts.
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Data processing involves 5 key steps: editing data, coding data, classifying data, tabulating data, and creating data diagrams. It transforms raw collected data into a usable format through these steps of cleaning, organizing, and analyzing the data. First, data is collected from sources and prepared by cleaning errors. It is then inputted and processed using algorithms before being output and interpreted in readable formats. Finally, the processed data is stored for future use and reports.
Data processing involves 5 key steps: 1) editing data to check for errors or omissions, 2) coding data by assigning numerals or symbols to categories, 3) classifying data into groups with common characteristics, 4) tabulating data by organizing it into a table for comparison and analysis, and 5) creating data diagrams or visual representations like graphs. The goal of data processing is to transform raw collected data into a readable and interpretable format that can be analyzed and used within an organization.
Systematic review article and Meta-analysis: Main steps for Successful writin...Pubrica
A review article is a piece of writing that gives a complete and systematic summary of results available in a certain field while also allowing the reader to perceive the subject from a different viewpoint.
Continue Reading: https://bit.ly/3m7OTqC
For our services: https://pubrica.com/services/research-services/systematic-review/
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When you order our services, We promise you the following – Plagiarism free | always on Time | 24*7 customer support | Written to international Standard | Unlimited Revisions support | Medical writing Expert | Publication Support | Biostatistical experts | High-quality Subject Matter Experts.
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This document provides guidance on survey design. It discusses key considerations for survey planning such as defining objectives, target populations, data requirements, and constraints. Preliminary research and establishing clear definitions are important preparatory steps. The goals are to formulate survey objectives, identify appropriate techniques, and design simple questionnaires.
The document outlines the key steps in the research process, which are: 1) defining the research problem; 2) reviewing relevant literature; 3) formulating testable hypotheses; 4) developing a research design; 5) determining sample design; 6) collecting data; 7) analyzing data; 8) generalizing and interpreting results; and 9) writing a report or thesis. It also discusses different types of research designs including exploratory, descriptive, and causal designs and levels of measurement such as nominal, ordinal, interval, and ratio scales. Common sources of error in measurement are issues with respondents, situational factors, flaws in measurement instruments, and errors in data handling.
The document discusses key steps in data analysis and interpretation for action research:
1) Data analysis involves summarizing collected data in an accurate manner depending on the type of data collected, such as using qualitative analysis for narrative data or quantitative analysis for numerical data.
2) Data interpretation finds meaning in the data by answering "So what?" and explaining trends, patterns, and relationships that emerge from the analysis.
3) Critical steps in analysis and interpretation include making data summaries, developing categories and coding, writing theoretical notes, quantification, and shaping metaphors to understand the data from different perspectives.
The document discusses various methods for analyzing and interpreting data. It describes descriptive analysis which helps summarize data patterns. Statistical analysis techniques like clustering, regression, and cohorts are explained. Inferential analysis makes judgments about differences between groups. Qualitative and quantitative methods are outlined for interpreting data through coding and establishing relationships. The purpose of data analysis and interpretation is to answer research questions and determine trends to support decision making.
There are several types of research discussed in the document. Applied research aims to solve specific organizational problems, while basic research seeks to understand problems and potential solutions. Descriptive research describes characteristics of variables, and exploratory research investigates problems where little is known. Industry research involves collecting data on a specific industry to understand trends. Quantitative research measures things precisely to test theories, while qualitative research provides an in-depth understanding through various sources like interviews. There are also different sampling methods, variables in research, steps to data mining, levels of information sources, and rating scales used in organizational research.
This proposal outlines a study to understand how social networks contribute feedback to mainstream media. The background discusses the growth of digital advertising, including social media advertising. The problem aims to analyze social network popularity, their current role, how feedback is provided to media, and importance in media reviews. Both qualitative and quantitative data will be collected through online surveys of 1000 social network users. Data will be analyzed for frequencies, percentages, and weighted means. The outcome is to assess social networks' effectiveness in providing feedback to mainstream media.
This document discusses key concepts in marketing research including:
1. It defines market research and marketing research, noting that market research focuses specifically on gathering market size and trend information while marketing research covers a broader range of activities.
2. It outlines the typical steps in the marketing research process including defining the problem, research design, data collection, analysis and reporting.
3. It provides details on key aspects of research design like secondary data sources, primary data collection methods, sampling, measurement scales and hypothesis testing.
The document discusses various steps involved in processing and analyzing qualitative and quantitative data. It describes processes like editing, classification, tabulation, content analysis and quantitative data analysis either manually or using computer software. Classification can be done based on attributes or class intervals. Tabulation involves arranging data in tables for further analysis. Content analysis involves identifying themes and coding responses. Quantitative data can be analyzed manually for small samples or using software like SPSS.
The document discusses the process of processing and analyzing data collected during scientific research. It explains that after collection, data must be processed through steps like editing, coding, classification, and tabulation to prepare it for analysis. The term analysis refers to using measures and searching for patterns to make comparisons between data groups. The document then provides details on specific processing operations like editing, coding, classification, and tabulation before discussing elements of analysis like descriptive analysis, correlation analysis, causal analysis, and multivariate analysis. It emphasizes that both descriptive and inferential statistical analysis are important tools in research for designing studies, summarizing data, and drawing conclusions.
This document provides information about getting fully solved assignments from an assignment help service. It lists a mail ID and phone number to contact for assistance with marketing research assignments. It then provides sample answers to 4 marketing research assignment questions, covering topics like primary research processes, types of data, qualitative vs. quantitative research methods, conjoint analysis, and probability sampling methods.
The document discusses data analysis and the discussion of findings in research. It provides details on the differences between data analysis and discussion of findings. It explains that data analysis involves evaluating and analyzing collected data using logical reasoning to form findings or conclusions. It discusses important issues in data analysis like using sufficient datasets and samples and not delegating the analysis. It also discusses common components of qualitative data analysis such as data archiving, exploring cases, finding themes and categories. The discussion of findings section explains that this part involves interpreting results in relation to research questions and existing knowledge to demonstrate what is known, differences found, and how findings extend knowledge in the field.
This document discusses research methodology and data processing and analysis. It covers topics like data processing operations including editing, coding, classification and tabulation. It also discusses problems in data processing, challenges faced by data scientists, different types of analysis including descriptive, diagnostic, exploratory, inferential, predictive, causal, mechanistic and prescriptive analysis. Finally, it covers editing and coding as important steps in data processing and provides examples of chi-square test in hypothesis testing.
This document discusses research methodology and data processing and analysis. It covers topics like:
- The main steps in data processing are editing, coding, classification and tabulation to organize data for analysis.
- Challenges in data processing include ensuring the right data is collected from multiple sources and dealing with unstructured data.
- The main types of data analysis covered are descriptive, diagnostic, exploratory, inferential, predictive, causal, mechanistic, and prescriptive analysis.
- Specific analytical techniques discussed include hypothesis testing using chi-square and z-tests, and their appropriate formulas.
Data Presentation & Analysis Meaning, Stages of data analysis, Quantitative & Qualitative data analysis methods, Descriptive & inferential methods of data analysis
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/temporal-event-neural-networks-a-more-efficient-alternative-to-the-transformer-a-presentation-from-brainchip/
Chris Jones, Director of Product Management at BrainChip , presents the “Temporal Event Neural Networks: A More Efficient Alternative to the Transformer” tutorial at the May 2024 Embedded Vision Summit.
The expansion of AI services necessitates enhanced computational capabilities on edge devices. Temporal Event Neural Networks (TENNs), developed by BrainChip, represent a novel and highly efficient state-space network. TENNs demonstrate exceptional proficiency in handling multi-dimensional streaming data, facilitating advancements in object detection, action recognition, speech enhancement and language model/sequence generation. Through the utilization of polynomial-based continuous convolutions, TENNs streamline models, expedite training processes and significantly diminish memory requirements, achieving notable reductions of up to 50x in parameters and 5,000x in energy consumption compared to prevailing methodologies like transformers.
Integration with BrainChip’s Akida neuromorphic hardware IP further enhances TENNs’ capabilities, enabling the realization of highly capable, portable and passively cooled edge devices. This presentation delves into the technical innovations underlying TENNs, presents real-world benchmarks, and elucidates how this cutting-edge approach is positioned to revolutionize edge AI across diverse applications.
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
5th LF Energy Power Grid Model Meet-up SlidesDanBrown980551
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdfChart Kalyan
A Mix Chart displays historical data of numbers in a graphical or tabular form. The Kalyan Rajdhani Mix Chart specifically shows the results of a sequence of numbers over different periods.
The Microsoft 365 Migration Tutorial For Beginner.pptxoperationspcvita
This presentation will help you understand the power of Microsoft 365. However, we have mentioned every productivity app included in Office 365. Additionally, we have suggested the migration situation related to Office 365 and how we can help you.
You can also read: https://www.systoolsgroup.com/updates/office-365-tenant-to-tenant-migration-step-by-step-complete-guide/
Conversational agents, or chatbots, are increasingly used to access all sorts of services using natural language. While open-domain chatbots - like ChatGPT - can converse on any topic, task-oriented chatbots - the focus of this paper - are designed for specific tasks, like booking a flight, obtaining customer support, or setting an appointment. Like any other software, task-oriented chatbots need to be properly tested, usually by defining and executing test scenarios (i.e., sequences of user-chatbot interactions). However, there is currently a lack of methods to quantify the completeness and strength of such test scenarios, which can lead to low-quality tests, and hence to buggy chatbots.
To fill this gap, we propose adapting mutation testing (MuT) for task-oriented chatbots. To this end, we introduce a set of mutation operators that emulate faults in chatbot designs, an architecture that enables MuT on chatbots built using heterogeneous technologies, and a practical realisation as an Eclipse plugin. Moreover, we evaluate the applicability, effectiveness and efficiency of our approach on open-source chatbots, with promising results.
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectorsDianaGray10
Join us to learn how UiPath Apps can directly and easily interact with prebuilt connectors via Integration Service--including Salesforce, ServiceNow, Open GenAI, and more.
The best part is you can achieve this without building a custom workflow! Say goodbye to the hassle of using separate automations to call APIs. By seamlessly integrating within App Studio, you can now easily streamline your workflow, while gaining direct access to our Connector Catalog of popular applications.
We’ll discuss and demo the benefits of UiPath Apps and connectors including:
Creating a compelling user experience for any software, without the limitations of APIs.
Accelerating the app creation process, saving time and effort
Enjoying high-performance CRUD (create, read, update, delete) operations, for
seamless data management.
Speakers:
Russell Alfeche, Technology Leader, RPA at qBotic and UiPath MVP
Charlie Greenberg, host
Discover top-tier mobile app development services, offering innovative solutions for iOS and Android. Enhance your business with custom, user-friendly mobile applications.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/how-axelera-ai-uses-digital-compute-in-memory-to-deliver-fast-and-energy-efficient-computer-vision-a-presentation-from-axelera-ai/
Bram Verhoef, Head of Machine Learning at Axelera AI, presents the “How Axelera AI Uses Digital Compute-in-memory to Deliver Fast and Energy-efficient Computer Vision” tutorial at the May 2024 Embedded Vision Summit.
As artificial intelligence inference transitions from cloud environments to edge locations, computer vision applications achieve heightened responsiveness, reliability and privacy. This migration, however, introduces the challenge of operating within the stringent confines of resource constraints typical at the edge, including small form factors, low energy budgets and diminished memory and computational capacities. Axelera AI addresses these challenges through an innovative approach of performing digital computations within memory itself. This technique facilitates the realization of high-performance, energy-efficient and cost-effective computer vision capabilities at the thin and thick edge, extending the frontier of what is achievable with current technologies.
In this presentation, Verhoef unveils his company’s pioneering chip technology and demonstrates its capacity to deliver exceptional frames-per-second performance across a range of standard computer vision networks typical of applications in security, surveillance and the industrial sector. This shows that advanced computer vision can be accessible and efficient, even at the very edge of our technological ecosystem.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
Skybuffer SAM4U tool for SAP license adoptionTatiana Kojar
Manage and optimize your license adoption and consumption with SAM4U, an SAP free customer software asset management tool.
SAM4U, an SAP complimentary software asset management tool for customers, delivers a detailed and well-structured overview of license inventory and usage with a user-friendly interface. We offer a hosted, cost-effective, and performance-optimized SAM4U setup in the Skybuffer Cloud environment. You retain ownership of the system and data, while we manage the ABAP 7.58 infrastructure, ensuring fixed Total Cost of Ownership (TCO) and exceptional services through the SAP Fiori interface.
Overcoming the PLG Trap: Lessons from Canva's Head of Sales & Head of EMEA Da...
Research methodology
1. The observation method is the most commonly used
method specially in studies relating t0 behavioral science
the under observation method, the information is sought by
way of investigator‟s own direct observation without asking
from the respondent. for instance in a study relating to
consumer behavior the investigator instead of asking the
brand of wrist watch used by respondent may himself look
at watch
2. The information obtained under this method relates
to what is currently happening it is not complicated
by either the past behaviour or future attitudes.
This method is independent of respondents
willingness to respond and as such is relatively less
demanding of active cooperation on the part of
respondents as happens to the case in the interview or
the questionnaire method.
3. Warranty cards- warranty cards are usually postal
sized cards which are used by dealers of consumer
durables to collect information regarding their
products. the information sought is printed in the
form of questions on the „warranty cards‟ which is
placed inside the package along with the product with
a request to the consumer to fill in the card and post it
back to the dealer.
4. Pantry audit- Pantry audit technique is used to estimate
consumption of the basket of goods at the consumer lebel . In
this type of audit the investigator collects an inventory of
types qualities and prices of commodities consumed. the usual
objective in a pantry audit is to find out what types of
consumers buy certain products and certain brands.
Distributor or store audits- distributor or store audits are
performed by distributors as well as manufactures through
their salesmen at regular intervals. Distributor get the retail
stores audited through salesmen and use such information to
estimate market size, market share, seasonal purchasing
pattern and so on.
5. Secondary data means data that are already available i.e.
they refer to the data which have already been collected
and analysed by someone else. secondary data may
either be published data or unpublished data. published
data are available
(a)various publication of the central ,state . And local
governments.
(b)various publications of foreign government or of
international bodies and their subsidiary organisation
(c)technical and trade journals.
(d)books, magazines and newspapers
(e)reports and publication of various associations
connected with business and industry, banks, stock
exchange
(f)public records and statistics, historical documents and
other sources of published information.
6. The sources of unpublished data are many they may
be found in diaries ,letters, unpublished biographies
and autobiographies and also may be available with
scholars and research workers, trade association ,
labour and other public private individuals and
organisations.
7. Secondary data must see that they possess following
characteristics.
Reliability of data- the reliability can be tested by
finding out such things about the said data
Who collected the data
What were the sources of data
Were they collected by using proper method
At what time were they collected
8. Suitability of data- the data that are suitable for one
enquiry may not necessarily be found suitable in
another enquiry hence if the available data are found to
be unsuitable ,they should not be used by the
researcher .in this context , the researcher must very
carefully scrutinise the definition of various terms and
units of collection used at the time of collecting the
data from the primary source originally
9. The data , after collection has to be processed and
analysed in accordance with the outline laid down for the
purpose at the time of developing the research plan .
This is essential for a scientific study and for ensuring
that we have all relevant data making contemplated
comparision and analysis
Technically speaking processing implises editing
,coding, classification, and tabulation of collected data
so that they are amenable to analysis
The term analysis refers to the computation of certain
measures along with searching for patterns of
relationship that exit among data group.
10. We can now proceed with the explanation of all the
processing operations.
Editing- editing of data is a process of examining the
collected raw material (specially in surveys) to detect errors
and omissions and to correct these when possible . As a
metter of fact, editing involves a careful scruitiny of the
completed questionnaires and or schedules.
Editing may be in the form of field editing or central editing
11. Field editing consists in the review of the
reporting forms by the investigator for
completing what the letter has written in
abbreviated and or in illegible form at the time
of recording the respondents responses.
Central editing should take place when all forms
or schedules have been completed and returned
to the office. This type of editing implises that
all form should get a through editing by a single
editor in a small study and by a team of editors
in case of large of inquiry.
12. Editors must keep in view several points while
performing their work
(a) they should be familiar with instructions given to
the interviewers and coders as well as with the editing
instructions supplied to them.
(b)they must make entries on the in some distinctive
colur and that too in a standardised form.
13. Coding refers to the process of assingning numerals
or other symbols to answers so that responses can be
put into a limited number of categories or classes.
Coding is necessary for efficient analysis and through
it the several replies may be reduced to a small
number of classes which contain the critical
information required for analysis.
14. Most research studies result in a large volume of raw data
which must be reduced into homogeneous group if we are
to get meaning full relationships.
the classification arranged on the basis of common
characteristics. Classification of two types
(a)Classification according to attributes
(b) Classification according to class intervals
15. When a mass of data has been assembled . It becomes
necessary for the researcher to arrange the same in some
kind of concise and logical order .this procedure is referred
to as tabulation thus tabulation is the process of
summarising raw data and displaying the same in compact
form(i.e. in the form of statistical tables) in a broader
sence , tabulation is an orderly arrangement of data in
columns and row
Tabulation is essentialy because of the following reasons
It facilitates the process of comparison.
It provides a basis for various statistical computation
16. Every table should be given a distinct number to facilitate
easy reference.
The column headings and the row headings of the table
should be clear and brief.
The columns may be numbered to facilitate reference.
Total of row should normally be placed in the extreme right
column and that of columns should be placed at the bottom.
17. We can take up the following two problems of processing
the data for analysis purpose.
(a)the problem concerning “don’t know”(or DK)
responses:- while processing the data the researcher often
comes across some responses that are difficult to handle .
One category of such responses may be „Don‟t know
response or simply DK response. When the DK response
group is small it is of little significance but when it is
relatively big it becomes a metter of major concern in which
the case the question arise.
(b)use of perccentage – percentages are often used in data
presentation for they simply numbers, reducing all of them
to a 0 to 100 range.
18. Two or more percentages must not be averaged unless each
is weighted by the group size from which it has been drived.
Use of too large percentage should be a voided since a
large percentage is difficult to understand and tends to
confuse , defeting the very purpose for which percentage
are used.
Percentage hide the base from which they have been
computed . If this is not kept in view the real difference may
not be correctly read.
19. As stated earlier , by analysis we mean the computation of certain
indices or measures along with searching for patterns of
relationship that exist among the data groups.
Analysis may , therefore be categorized as descriptive analysis
and inferential analysis
Descriptive analysis – descriptive analysis is largely the study of
distribution of one variable .this study provides us with profiles of
companies, work groups, persons and other subjects on any of a
multiple of characteristics such as size , composition , efficiency ,
preferences.
Inferential analysis- is concerned with the various tests of
significance for testing hypothesis in order to determine with what
validity data can be said to indicate some conclusion or
conclusions. It is also concerned with the estimation of population
values.
20. We can say that the case study method is a form of
qualitative analysis where in careful and complete
observation of an individual or a situation or an
institution is done efforts are made to study each and
every aspect of the concerning unit in minute details
and then from case data generalizations and inferences
are drawn.
The case study method is a very popular form of
qualitative analysis and involves a careful and complete
observation of a social unit , be that unit a person, a
family , an institution , a cultural group or even the
entire group.
21. The important characteristics case study method are as under
Under this method the researcher can take one single social
unit or more of such units for his study purpose
In respect of the case study method an effort is made to know
the mutual inter relationship of casual factor
Under the case study method the behaviour of the concerning
unit is studied directly and not by an indirect and abstract
approach
22. The case study method is based on the several assumption
The assumption of studying the natural history of the unit
concerned
The unit of comprehensive study of the unit cocerned
23. Sampling may be defined as the selection of some part of an
aggregate or totality on the basis of which a judgment about
the aggregate or totality is made.
In other words it is the process of obtaining information about
an entire population of by examining only a part of it
Need for sampling-
Sampling can save time and money. A sample study is
usually less expensive than a census study and produces
results at a relatively faster speed.
Sampling remains the only choice when a test involves the
destruction of the item under study.
Sampling may enable more accurate measurements for a
sample study is generally conducted by trained and
experienced investigator.
24. We should be familiar with some fundamental definations
concerning sampling concepts and principles…………..
1.Universe /population-:
From a statistical point of view the term „universe‟ refers to
the total of the items or units in any field of inquiry.
Whereas the term „population‟ refers to the total of all items
about which information is desired.
The population or universe cab be finite or infinite. The
population is said to be finite if it consists of a fixed number
of elements , for instance the population of a city , the
number of workers in a factory
An infinite population is that population in which it is
theoretically impossible to observe all element. For instance
the number of instance in a sky , possible rolls of a pair of
25.
26. Hypothesis is usually considered as the principal instrument in research . Its main
function is to suggest new experiments and observations. In fact , many experiments
are carried out with the deliberate object of testing hypothesis.
Characteristics of hypothesis-there are following characteristics of hypothesis
Hypothesis should be clear and precise . If the hypothesis is not clear and precise the
inferences drawn on its basis cannot be taken as reliable.
Hypotheis should state relationship between variables, if it happens to be a
relational hypothesis
Hypothesis should be limited in scope and must be specific. A researcher must
remember that narrower hypotheses are generally more testable and he should
develop such hypothesis.
Hypothesis should be consistent with most known facts i.e. it must be consistent
with a substantial body of established facts. In other words , it should be one which
judges accept as being the most likely.
27. Basic concept in the context of testing of hypothesis need to
be explained.
Null hypothesis and alternative hypothesis if we are
compare method A with method B about its superiority and
if we proceed on the assumption that both methods are
equally good , then this assumption is termed as the null
hypothesis .it is represented by H0
As against this , we may think that the method A is superior
or the method B is inferior , we are then stating what is
termed as alternative hypothesis . it is represented by Ha
The level of significance this is a very important concept
in the context of hypothesis testing .it is always some
percentage (usually 5%) the five percentage level of
28. Test of hypothesis- given a hypothesis Ho and an alternative
hypothesis Ha , we make a rule which is known as decision
rule according to which we accept Ho or reject Ha
Type I and Type II Errors- type I error means rejection of
hypothesis which should have been accepted and type II error
means accepting the hypothesis which should have been
rejected . Type I error is denoted by alpha known as alpha
error and type II error is denoted by beta known as beta error
29. Procedure for hypothesis testing- the various steps involved in
hypothesis testing are stated below
Making a formal statement
Selecting a significance level
Deciding the distribution to use
Selecting a random sample and computing an appropriate value
Calculation of probability
Comparing the probability
Making a formal statement the step consists in making a formal
statement of the null hypothesis (Ho) and also the alternative
hypothesis(Ha) this means that hypotheses should be clearly stated
considering the nature of research problem for example , Mr.
Mohan of the civil engineering department wants to the test the
load bearing capacity of an old bridge which must be more than 10
tons , in that case he can state his hypothesis as under
Null hypothesis Ho=10 tons
Alternative hypothesis Ha>10 tons
30. Selecting a significance level- the hypotheses are tested on a
pre determined level of significance and as such the same
should be specified . Generally , in practice, either 5% level or
1% level is adopted for the purpose. The factors that affect
the level of significance are
(a) the magnitude of the difference between the sample means
(b)the size of samples
(c)the variability of measurements with samples
Deciding the distribution to use – after deciding the level of
significance , the next step in hypothesis testing is to
determine the appropriate sampling distribution .the choice
generally remains between normal distribution and t –
distribution.
31. Selecting a random sample and computing an appropriate
value- another step is to select a random sample and compute
an appropriate value from the sample data concerning the test
statistic utilizing the relevant distribution .in other words ,
draw a sample to furnish empirical data.
Calculation of probability- once has then to calculate the
probability then the sample result would diverge as widely as
it has from expectations, if the null hypothesis were in fact
true
Comparing the probability-another step consists in
comparing the probability thus calculated with the specified
value for alpha ,the significance level .if the calculated
probability is equal to or smaller than the alpha value in case
of one tailed test then the reject null hypothesis .but if the
calculated probability is greater then accept the null
hypothesis
32. Classification of hypothesis
statisticians have developed several tests of hypotheses for the
purpose of testing of hypotheses which can be classified as-
(a)parametric tests or standard tests of hypotheses
(b)non parametric tests or distribution free test of hypotheses
(a)parametric tests or standard tests of hypotheses
Parametric tests usually assume certain properties of the parent
population from which we draw samples. Assumptions like
observations come from a normal population , sample size is large ,
assumptions about the population parameters like mean, variance
etc must hold good before parametric tests can be used.important
parameter test are z-test,t-test,chi square test, f-test
(b)non parametric tests or distribution free test of hypotheses-
when the researcher cannot or does not want to make such
assumptions ,in such situations we use statistical methods for
testing hypothesis which are called non parametric tests because
such test do not depend on any assumption about the parameters of
the parents population.
33. Research report- research report is considered a majore
component of the research study for the research task remains
incomplete till the report has been presented and or written
Different steps in writing report- the usual steps involved in
writing report are
Logical analysis of the subject matter
Preparation of the final outline
Preparation of the rough draft
Rewriting and polishing of the rough draft
Preparation of the final bibliography
Logical analysis of the subject matter- it is the first step which is
primarily concerned with the development of a subject . There are
two ways in which to develop a subject (a)logically (b)
chronologically . The logical development is made on the basis of
mental connections and association between the one thing and
another by means of analysis logical treatment often consists in
developing the material from the simple possible to the most
complex structures. Chronological development is based on a
connection or sequence in time or occurrence.
34. Preparation of the final outline – it is the next step in
writing the research report “ outlines are the framework upon
which long written works are constructed . They are an aid to
the logical organization of the material and a reminder of the
points to be stressed in the report”.
Preparation of the rough draft- This step importance for the
researcher now sits to write down what he has done in the
context of his research study. He will write down the
procedure adopted by him in collecting the material for his
study along with various limitations faced by him the
technique of analysis adopted by him the broad findings and
generalizations and the various suggestions he wants to offer
regarding the problem concerned.
35. Rewriting and polishing of the rough draft- this step
happens to be most difficult part of all formal writing .
Usually this step requires more time than the writing of rough
draft. The carefull revision makes the difference between a
mediocre and a good piece of writing. While rewriting and
polishing one should check the report for weakness in logical
development or presentation. The researcher should also see
whether or not the material as it is presented has unity and
cohesion
Preparation of the final bibliography – the bibliography
should be arranged alphabetically and may be divided into
two parts the first part may contain the names of books and
pamphlets , and the second part may contain the names of
magazines and newspaper articles . Generally , this pattern of
bibliography is considered convenient and satisfactory from
the point of view of reader , though it is not the only way of
presenting bibliography.
36. Layout of research report – a comprehensive layout of the research
report should comprise
Preliminary pages
Main text
End matter
(A)Preliminary pages – the report should carry a title and date followed
by acknowledgements in the form of preface or foreword then there
should be a table of contents followed by list of tables and illustrations
so that the decision maker or anybody interested in reading the report can
easily locate the required information in the report
(B)Main text-the main text provides the complete outline of the research
report along with all details title of the research study is repeated at the
top of the first page of the main text and then follows the other details on
pages numbered consecutively , beginning with the second page. The
main text of the report should have the following sections
Introduction
Statement of findings and recommendations
Results
Implications of the results
Summary
37. Introduction- the purpose of introduction is to introduce the
research project to the readers. It should contain a clear
statement of the objectives of research i.e. enough background
should be given to make clear to the reader why the problems
was considered worth investigating.
Statement of findings and recommendations –after
introduction , the research report must contain a statement of
findings and recommendations in non technical language so
that it can be easily understood by all concerned . If the
findings happen to be extensive , at this point they should be
put in the summarised form.
Result -a detailed presentation of the findings of the study ,
with supporting data in the form of tables and charts together
with a validation of results, is the next step in writing the main
text of the report.all the result should be presented in logical
sequence and splited into readily identifiable sections. All
relevant results must find a place in the report.
38. Implications of the results -towards the end of the main text ,
the researcher should again put down the results of his
research clearly and precisely . Such implications may have
three aspects as stated below
A statement of the inferences drawn from the present study
which may expected to apply in similar circumstances.
The condition of the present study which may limit the extent
of legitimate generalizations of the inferences drawn from the
study.
The relevant questions that still remain unanswered or new
questions raised by the study along with suggestions for the
kind of research that would provide answers for them .
Summary-I t has become customary to conclude the research
report with a very brief summary resting in brief the research
problem , the methodology the major findings and the majore
conclusions drawn from the research results.
39. (C)End matters-at the end of the report , appendices should
be enlisted in respect of all technical data such as
questionnaires, sample information , mathematical derivations
and the like ones. Bibliography of sources consulted should
also be given.
40. Types of report-reports may be classified in to two main
categories
Technical report
Popular report
Technical report- the technical report is used whenever a full
written report of the study is required whether for record keeping
or for public dissemination. A general outline of a technical report
can be as follows
Summary of the result
Nature of the study
Methods employed
Data
Analysis of data and presentations of findings
Conclusions
Bibliography
Technical appendices
Index
41. Summary of the result –a brief review of the main findings
just in two or three pages
Nature of the study-description of the general objectives of
study , formulation of the problem in operational terms , the
working hypothesis , the type of analysis and data required.
Methods employed- specific methods used in the study and
their limitations. For example in sampling studies we should
give details of sample designs viz., sample size , sample
selection etc
Data- discussion of data collected , their sources,
characteristics and limitations , if secondary data are used ,
their suitability to the problem at hand be fully assessed . In
case of a survey , the manner in which data were collected
should be fully described.
42. Analysis of data and presentations of findings –the analysis
of data and presentations of findings of the study with
supporting data in the form of tables and charts be fully
narrated . This in fact happens to be the main body of the
report usually extending over several chapters.
Conclusion- a detailed summary of the findings and the
policy implications drawn from the result explained
Bibliography- bibliography of various sources consulted be
prepared and attached
Technical appendices- appendices be given for all technical
metters relating to questionnaire mathematical derivations ,
elaboration on particular technique of analysis and the like
ones.
Index- index must be prepared and be given in variably in the
report at the end
43. Popular report- a popular report is used if the research result
have policy implications . The popular report is one which
gives emphasis on simplicity and attractiveness. The
simplification should be sought through clear writing ,
minimization of technical , particularly mathematical, details
and liberal use of charts and diagrams. We give below a
general outline of a popular report
The findings and their implications
Recommendations for actions
Objectives of the study
Method employed
Results
Technical appendices
44. The findings and their implications- emphasis in the report is
given on the findings of most practical interest and on the
implications of these findings
Recommendations for actions- recommendations for action on
the basis of the findings of the study is made in this sections of the
report
Objectives of the study- a general review of how the problems
arise is presented along with the specific objectives of the project
under study
Method employed- a brief and non technical description of the
methods and techniques used including a short review of the data
on which the study is based , is given in this part of the report.
Results- this sections constitues the main body of the report
wherein the results of the study are presented in clear and non
technical terms with liberal use of all sorts of illustrations such as
charts, diagrams, and the like ones.
Technical appendices- more detailed information on methods
used, forms, etc is presented in the form of appendices . But the
appendices are often not detailed if the report is entirely meant for
general public.
45. Precautions for writing research reports-research report is a
channel of communicating the research findings to the readers of
the report. as such it must be prepared keeping the following
precautions in view
A research report should not, if this can be avoided , be dull it
should be such as to sustain readers interest
Readers are often interested in acquiring a quick knowledge of the
main findings and as such the report must provide a ready
availability of the findings for this purpose charts, graphs and the
statistical tables may be used for the various results in the main
report in addition to the summary of important findings.
The layout of the report should be well thought out and must be
appropriate and in accordance with the objectives of the research
problems
Appendecies should be enlisted in respect of all the technical data
in the report.
Bibliography of sources consulted is a must for a good report and
must necessary be given
Index is also considered an essential parts of a good report and
must necessarily be given.