Rone
•Download as DOCX, PDF•
0 likes•1,376 views
This chapter outlines the methodology used in the study. A descriptive research design was used to determine the performance level of third year BSMT and BSMAR-E students in math at VMA Global College in the first semester of 2011-2012. The respondents were 400 third year students who were randomly selected using proportional sampling. Data was collected through a self-administered questionnaire that was validated by jurors and found to be "very good".
Report
Share
Report
Share
Recommended
Rone
This chapter outlines the methodology used in the study. A descriptive research design was used to describe the performance level of third year BSMT and BSMAR-E students in math. The respondents were third year students from 7 sections totaling 400 students. A random sampling technique was used to select 2 sections with 44 students each. Data was collected using a self-administered questionnaire which was validated by experts. Statistical tools like percentage and mean were used to analyze the data and determine performance levels and differences between the programs.
Chapter iii
This chapter outlines the methodology used in the study. The study used a descriptive analytic research design to gather information about existing conditions at Lagui-Sail Elementary School. The researcher utilized questionnaires, checklists, and observation to collect descriptive data on learning disabilities among primary grade students. The entire primary student population was included in the sample. Data was analyzed using statistical methods like percentage, ranking, and Pearson's correlation coefficient to interpret the results.
Collection of Quantitative Data
This document discusses techniques for collecting quantitative data. It describes quantitative data as measurable and numerical. The main techniques discussed are observation, surveys, experiments, and content analysis. Surveys can be conducted through questionnaires or interviews. Observation can be direct or indirect. Experiments involve a pre-test, treatment, and post-test. Measurement scales for quantitative data include nominal, ordinal, interval, and ratio scales.
Sampling
This document discusses different methods of sampling data from a population. There are two main methods: census, which collects data from every unit in the population, and sampling, which collects data from a subset of units. Sampling has advantages in terms of efficiency and feasibility for large populations. There are various sampling techniques including simple random sampling, stratified sampling, systematic sampling, and multi-stage sampling. The document also discusses principles of sampling and provides examples of random and non-random sampling methods.
Chapter 3
This chapter outlines the research methodology used in the study. A descriptive correlational research design was used to describe parents' perceptions of art courses and determine if those perceptions influence students' academic performance. The population was senior high school students majoring in digital art and their parents at a particular college. A quota sampling method was used to select 50 parents and 25 students. Survey questionnaires were distributed via Google Forms to collect data on parents' perceptions and students' GPAs. Statistical analysis including frequencies, percentages, weighted means, and correlation would then be used to analyze the data.
Sample and sampling methods
This document discusses different concepts related to sampling, including population, sample, sampling process, and probability sampling methods. It defines population as the total group being studied, while sample is a subset selected to represent the population. Probability sampling methods like simple random sampling, stratified random sampling, cluster sampling, and systematic random sampling are covered. These methods aim to select samples in a way that gives all population members an equal chance of being selected to avoid bias. The document provides details on how to implement each sampling technique.
Nonnegative matrix-fact
The document discusses conditions for effectively deriving a Q-Matrix from assessment data using Non-Negative Matrix Factorization (NMF). It describes a study that used NMF to interpret a Q-Matrix and derive the underlying skills assessed by test questions in mathematics, biology, history and French. The study analyzed response data from 297 respondents to a 40 question test. NMF was able to effectively cluster test questions that assessed well delineated skills.
Quantitative research methodologies
Experimental research involves deliberately influencing a variable to test cause and effect relationships using experimental and control groups randomly assigned subjects. Quantitative research methodologies also include correlational research which examines relationships between variables, causal-comparative research which determines causes or consequences of pre-existing differences, survey research which collects information from a sample using questionnaires, and single subject research which collects data from one subject at a time. Proper research design, sampling, instrumentation, and data analysis are important for validity.
Recommended
Rone
This chapter outlines the methodology used in the study. A descriptive research design was used to describe the performance level of third year BSMT and BSMAR-E students in math. The respondents were third year students from 7 sections totaling 400 students. A random sampling technique was used to select 2 sections with 44 students each. Data was collected using a self-administered questionnaire which was validated by experts. Statistical tools like percentage and mean were used to analyze the data and determine performance levels and differences between the programs.
Chapter iii
This chapter outlines the methodology used in the study. The study used a descriptive analytic research design to gather information about existing conditions at Lagui-Sail Elementary School. The researcher utilized questionnaires, checklists, and observation to collect descriptive data on learning disabilities among primary grade students. The entire primary student population was included in the sample. Data was analyzed using statistical methods like percentage, ranking, and Pearson's correlation coefficient to interpret the results.
Collection of Quantitative Data
This document discusses techniques for collecting quantitative data. It describes quantitative data as measurable and numerical. The main techniques discussed are observation, surveys, experiments, and content analysis. Surveys can be conducted through questionnaires or interviews. Observation can be direct or indirect. Experiments involve a pre-test, treatment, and post-test. Measurement scales for quantitative data include nominal, ordinal, interval, and ratio scales.
Sampling
This document discusses different methods of sampling data from a population. There are two main methods: census, which collects data from every unit in the population, and sampling, which collects data from a subset of units. Sampling has advantages in terms of efficiency and feasibility for large populations. There are various sampling techniques including simple random sampling, stratified sampling, systematic sampling, and multi-stage sampling. The document also discusses principles of sampling and provides examples of random and non-random sampling methods.
Chapter 3
This chapter outlines the research methodology used in the study. A descriptive correlational research design was used to describe parents' perceptions of art courses and determine if those perceptions influence students' academic performance. The population was senior high school students majoring in digital art and their parents at a particular college. A quota sampling method was used to select 50 parents and 25 students. Survey questionnaires were distributed via Google Forms to collect data on parents' perceptions and students' GPAs. Statistical analysis including frequencies, percentages, weighted means, and correlation would then be used to analyze the data.
Sample and sampling methods
This document discusses different concepts related to sampling, including population, sample, sampling process, and probability sampling methods. It defines population as the total group being studied, while sample is a subset selected to represent the population. Probability sampling methods like simple random sampling, stratified random sampling, cluster sampling, and systematic random sampling are covered. These methods aim to select samples in a way that gives all population members an equal chance of being selected to avoid bias. The document provides details on how to implement each sampling technique.
Nonnegative matrix-fact
The document discusses conditions for effectively deriving a Q-Matrix from assessment data using Non-Negative Matrix Factorization (NMF). It describes a study that used NMF to interpret a Q-Matrix and derive the underlying skills assessed by test questions in mathematics, biology, history and French. The study analyzed response data from 297 respondents to a 40 question test. NMF was able to effectively cluster test questions that assessed well delineated skills.
Quantitative research methodologies
Experimental research involves deliberately influencing a variable to test cause and effect relationships using experimental and control groups randomly assigned subjects. Quantitative research methodologies also include correlational research which examines relationships between variables, causal-comparative research which determines causes or consequences of pre-existing differences, survey research which collects information from a sample using questionnaires, and single subject research which collects data from one subject at a time. Proper research design, sampling, instrumentation, and data analysis are important for validity.
Prediction-Next-Term Student Performance Prediction: A Recommender Systems Ap...
In this study, the purpose was to compare about 10 prediction methods and find out which one is most effective in university students' garde. They used Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE) to compare the prediction methods. They found that Factorization Matrix (FM)-Random Forest (RF) hybrid the most effective method in general. It is an effective method to overcome the cold-start limitations that FM could not handle.
Sweeney, M., Rangwala, H., Lester, J., Johri, A. (2016). Next-Term Student Performance Prediction: A Recommender Systems Approach, Journal of Educational Data Mining, 8(1), 22-51.
Sample and sampling techniques
The paper discusses how to select representative samples and parameters for deciding sampling techniques. It also adopts a more friendly approach to the determination of samples for population parameters by adopting the use of sample size calculator
Non probability sampling process
Non-probability sampling techniques are commonly used in nursing research when random sampling is not possible. These include purposive sampling, where subjects are chosen based on a specific purpose; convenience sampling, where accessible subjects are selected; and snowball sampling, where existing subjects refer others. While non-probability sampling is less costly and time-consuming than probability methods, it produces biased samples that cannot be generalized to the larger population.
Sampling methods ppt
This document discusses different sampling methods used in research. It describes probability sampling methods like simple random sampling, systematic sampling, stratified sampling, cluster sampling, and multi-stage sampling. It also describes non-probability sampling methods like convenience sampling, purposive sampling, and snowball sampling. The key aspects of each sampling method are defined along with their advantages and disadvantages. Probability sampling aims to ensure that samples are representative of the larger population, while non-probability sampling does not allow determining the probability of sample selection.
Sampling Techniques
This document discusses various sampling techniques used in research. It defines sampling as selecting study units from a population. Probability sampling methods like simple random sampling, systematic sampling, stratified sampling and cluster sampling allow generalization to the population by giving units an equal chance of selection. Non-probability methods like convenience and quota sampling are used without a sampling frame. The document emphasizes the importance of representative, bias-free samples for research validity.
Presentation (1)
This document discusses the role and importance of statistics in analyzing assessment data. It explains that statistics is used to collect, analyze, organize, and interpret numerical data. It is important for drawing conclusions and inferences from facts. In education, statistics helps with constructing and standardizing tests, understanding individual student differences, comparing evaluation methods, and making predictions about student progress. The document also defines key differences between populations and samples, noting that a population includes all data elements while a sample is a subset, and their means and standard deviations are calculated differently.
Prediction-Improving Early Warning Systems With Categorized Course Resource U...
This study aimed to find out how STEM collage students' use of different course resources in an LMS predict their final grades. They used Logistic Regression Models to estimate assosciation between resourse use and final grade. The results showed that there is a positively significant association between exam-related sources use and final grade. On the other hand, when students use lecture-related resources, then they are less likely to have good grades.
Waddington, R. J., Nam, S., Lonn, S., Teasley, S. D. (2016). Improving early warning systems with categorized course resource usage. Journal of Learning Analytics, 3(3), 263–290.
Collecting Quantitative Datafinished
The document discusses planning a research study, including identifying the target population and sample, deciding on the appropriate level and size of sampling, and selecting appropriate data collection methods. Some key points covered are:
1) Researchers must identify the target population and determine whether to study individuals, organizations, or a combination. They must also decide how many people or organizations to include in the sample.
2) Researchers select a sampling method depending on rigor needed, population characteristics, and participant availability. Common methods include simple random sampling, stratified sampling, cluster sampling, and convenience/snowball sampling.
3) Researchers identify what data needs to be collected to measure the study variables. Common methods are tests, questionnaires, interviews, observations
Chapter 3
This chapter outlines the research methodology used in the study. A quantitative survey approach using questionnaires was used to collect data from 40 English teachers and 135 secondary school students in 3 schools in Petaling district, Malaysia. The questionnaires included sections on demographics, the English Learning Motivation Questionnaire (ELMQ) to measure students' motivation, the Teaching Styles Survey (TSS) to identify teachers' teaching styles, and open-ended questions. Data was analyzed using SPSS to identify patterns in teaching styles and their relationship to motivation. The study aims to identify teaching styles, recognize motivation levels, investigate the relationship between styles and motivation, and identify ways to improve motivation.
Lesson01_new
This document provides an introduction to statistics for management. It discusses descriptive versus inferential statistics and how they are used to collect and analyze data. Descriptive statistics are used to characterize and present data through tables, graphs and measures like the mean. Inferential statistics are used to make estimates and test hypotheses about populations based on sample data. The document also outlines different types of data and sources, sampling methods like simple random and stratified sampling, and potential survey errors.
Sampling techniques
This document discusses sampling techniques in research methodology. It defines a population as the overall group being studied and sampling as selecting a subset of individuals from the population to collect data from. There are two main types of sampling: probability sampling, which uses random selection to choose participants so that all members of the population have an equal chance of being selected; and non-probability sampling, which does not rely on random selection and can result in more bias. Several examples of probability and non-probability sampling techniques are provided.
AN INVESTIGATION OF THE IMPACT OF ATYPICAL PRINCIPAL PREPARATION PROGRAMS ON ...
AN INVESTIGATION OF THE IMPACT OF ATYPICAL PRINCIPAL PREPARATION PROGRAMS ON SCHOOL ACCOUNTABILITY AND STUDENT ACHIEVEMENT IN HIGH-POVERY SCHOOLS by Sheri L. Miller-Williams, Dissertation Chair: William Allan Kritsonis, PhD
Sampling
This presentation consists of description of sampling and developing a conceptual understanding of sampling.
Collection of data class 12th cbse
collection of data class 12th important notes with sanjay sir .for more videos subscribe my you tube channel sk knowledge point
Rp chapter 3 draft zulaikha
This document describes the methodology used in a study analyzing the effects of self-questioning reading strategies. It outlines the research design, population and sample, instruments used for data collection, and methods for data analysis. The study uses a quasi-experimental design with pre- and post-tests to evaluate the impact of self-questioning instruction on reading comprehension. Questionnaires, document analysis of students' questions, and comprehension tests are used to collect data. Statistical analysis including descriptive analysis, frequency calculation, and paired t-tests will analyze the data.
Sampling techniques
The sampling technique that would be most appropriate for this scenario is:
Stratified random sampling.
The population (town of 120,000 people) can be divided into strata based on characteristics like age, gender, area of town, etc. The committee could then randomly select a specific number of people from each stratum, with the number selected from each stratum being proportional to the stratum's size within the total population. This would help ensure the sample is representative.
ISI B.STAT/M.STAT TUITION COACHING ONLINE AND LIVE
ISI M.STAT TUITION/COACHING
CRASH COURSE IN KOLKATA
STUDY MATERIALS / MOCK TESTS
/ SOLUTION OF PREVIOUS PAPERS
/ MATHEMATICAL SHORT CUTS
SEPARATE BATCHES
SOLUTION OF ALL QUESTIONS FROM TEXTBOOK AND LAST 10 YEARS.
STUDENTS CAN ALSO HAVE A CRASH COURSE FOR A SHORT SPAN OF TIME.
AND SOLUTIONS TO ALL TEXTBOOK QUESTIONS.
NOTES, SUGGESTIONS, AND MOCK TESTS.
CLASSES AT:
GIRISH PARK
MAIDAN AND
FOR ANY FURTHER DETAILS
*CONTACT:
SOURAV SIR'S CLASSES
9836793076
Sampling in research
This document provides an overview of sampling techniques used in research. It defines key terms like population, sample, and sampling. It discusses characteristics of good sampling like being representative and free from bias. Probability sampling techniques like simple random sampling, stratified sampling, and systematic sampling are explained. Advantages of sampling like reducing time and costs are highlighted. The document outlines the sampling process and essentials of sampling. Types of sampling and various sampling methods are also summarized.
SAMPLING MEANING AND TYPES
Probability and non-probability sampling were discussed. Probability sampling methods like simple random sampling, systematic sampling, stratified sampling, and cluster sampling aim to ensure each unit has an equal chance of selection. Non-probability methods like convenience sampling, judgmental sampling, and snowball sampling rely on accessibility and do not ensure equal chance of selection. While statistical agencies prefer probability sampling, businesses often use non-probability sampling for market research due to increased respondent cooperation.
7. research_design.pptx
This document discusses methodology for quantitative research, including research design, sampling techniques, and instruments. It provides information on different types of quantitative research designs like descriptive, correlational, experimental, and quasi-experimental. It also outlines various sampling techniques including probability sampling methods like simple random sampling and stratified random sampling, and non-probability sampling methods like convenience and purposive sampling. Finally, it discusses developing instruments and providing examples of different question types for surveys.
(PR2) Research Design - Practical Research 2
This document discusses methodology for quantitative research, including research design, sampling techniques, and developing research instruments. It provides information on different types of quantitative research designs like descriptive, correlational, experimental, and quasi-experimental designs. It also discusses target populations, samples, and various probability and non-probability sampling techniques. Finally, it touches on developing valid and reliable instruments to collect quantitative data.
research_design.pptx
This document discusses methodology for quantitative research, including research design, sampling techniques, and developing research instruments. It provides descriptions of common quantitative research designs like experimental, quasi-experimental, correlational, and various sampling methods. It also addresses developing instruments, ensuring validity and reliability, and collecting data. The overall methodology is to choose an appropriate research design, determine sampling strategy, construct a valid instrument, and collect data to answer the research question.
More Related Content
What's hot
Prediction-Next-Term Student Performance Prediction: A Recommender Systems Ap...
In this study, the purpose was to compare about 10 prediction methods and find out which one is most effective in university students' garde. They used Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE) to compare the prediction methods. They found that Factorization Matrix (FM)-Random Forest (RF) hybrid the most effective method in general. It is an effective method to overcome the cold-start limitations that FM could not handle.
Sweeney, M., Rangwala, H., Lester, J., Johri, A. (2016). Next-Term Student Performance Prediction: A Recommender Systems Approach, Journal of Educational Data Mining, 8(1), 22-51.
Sample and sampling techniques
The paper discusses how to select representative samples and parameters for deciding sampling techniques. It also adopts a more friendly approach to the determination of samples for population parameters by adopting the use of sample size calculator
Non probability sampling process
Non-probability sampling techniques are commonly used in nursing research when random sampling is not possible. These include purposive sampling, where subjects are chosen based on a specific purpose; convenience sampling, where accessible subjects are selected; and snowball sampling, where existing subjects refer others. While non-probability sampling is less costly and time-consuming than probability methods, it produces biased samples that cannot be generalized to the larger population.
Sampling methods ppt
This document discusses different sampling methods used in research. It describes probability sampling methods like simple random sampling, systematic sampling, stratified sampling, cluster sampling, and multi-stage sampling. It also describes non-probability sampling methods like convenience sampling, purposive sampling, and snowball sampling. The key aspects of each sampling method are defined along with their advantages and disadvantages. Probability sampling aims to ensure that samples are representative of the larger population, while non-probability sampling does not allow determining the probability of sample selection.
Sampling Techniques
This document discusses various sampling techniques used in research. It defines sampling as selecting study units from a population. Probability sampling methods like simple random sampling, systematic sampling, stratified sampling and cluster sampling allow generalization to the population by giving units an equal chance of selection. Non-probability methods like convenience and quota sampling are used without a sampling frame. The document emphasizes the importance of representative, bias-free samples for research validity.
Presentation (1)
This document discusses the role and importance of statistics in analyzing assessment data. It explains that statistics is used to collect, analyze, organize, and interpret numerical data. It is important for drawing conclusions and inferences from facts. In education, statistics helps with constructing and standardizing tests, understanding individual student differences, comparing evaluation methods, and making predictions about student progress. The document also defines key differences between populations and samples, noting that a population includes all data elements while a sample is a subset, and their means and standard deviations are calculated differently.
Prediction-Improving Early Warning Systems With Categorized Course Resource U...
This study aimed to find out how STEM collage students' use of different course resources in an LMS predict their final grades. They used Logistic Regression Models to estimate assosciation between resourse use and final grade. The results showed that there is a positively significant association between exam-related sources use and final grade. On the other hand, when students use lecture-related resources, then they are less likely to have good grades.
Waddington, R. J., Nam, S., Lonn, S., Teasley, S. D. (2016). Improving early warning systems with categorized course resource usage. Journal of Learning Analytics, 3(3), 263–290.
Collecting Quantitative Datafinished
The document discusses planning a research study, including identifying the target population and sample, deciding on the appropriate level and size of sampling, and selecting appropriate data collection methods. Some key points covered are:
1) Researchers must identify the target population and determine whether to study individuals, organizations, or a combination. They must also decide how many people or organizations to include in the sample.
2) Researchers select a sampling method depending on rigor needed, population characteristics, and participant availability. Common methods include simple random sampling, stratified sampling, cluster sampling, and convenience/snowball sampling.
3) Researchers identify what data needs to be collected to measure the study variables. Common methods are tests, questionnaires, interviews, observations
Chapter 3
This chapter outlines the research methodology used in the study. A quantitative survey approach using questionnaires was used to collect data from 40 English teachers and 135 secondary school students in 3 schools in Petaling district, Malaysia. The questionnaires included sections on demographics, the English Learning Motivation Questionnaire (ELMQ) to measure students' motivation, the Teaching Styles Survey (TSS) to identify teachers' teaching styles, and open-ended questions. Data was analyzed using SPSS to identify patterns in teaching styles and their relationship to motivation. The study aims to identify teaching styles, recognize motivation levels, investigate the relationship between styles and motivation, and identify ways to improve motivation.
Lesson01_new
This document provides an introduction to statistics for management. It discusses descriptive versus inferential statistics and how they are used to collect and analyze data. Descriptive statistics are used to characterize and present data through tables, graphs and measures like the mean. Inferential statistics are used to make estimates and test hypotheses about populations based on sample data. The document also outlines different types of data and sources, sampling methods like simple random and stratified sampling, and potential survey errors.
Sampling techniques
This document discusses sampling techniques in research methodology. It defines a population as the overall group being studied and sampling as selecting a subset of individuals from the population to collect data from. There are two main types of sampling: probability sampling, which uses random selection to choose participants so that all members of the population have an equal chance of being selected; and non-probability sampling, which does not rely on random selection and can result in more bias. Several examples of probability and non-probability sampling techniques are provided.
AN INVESTIGATION OF THE IMPACT OF ATYPICAL PRINCIPAL PREPARATION PROGRAMS ON ...
AN INVESTIGATION OF THE IMPACT OF ATYPICAL PRINCIPAL PREPARATION PROGRAMS ON SCHOOL ACCOUNTABILITY AND STUDENT ACHIEVEMENT IN HIGH-POVERY SCHOOLS by Sheri L. Miller-Williams, Dissertation Chair: William Allan Kritsonis, PhD
Sampling
This presentation consists of description of sampling and developing a conceptual understanding of sampling.
Collection of data class 12th cbse
collection of data class 12th important notes with sanjay sir .for more videos subscribe my you tube channel sk knowledge point
Rp chapter 3 draft zulaikha
This document describes the methodology used in a study analyzing the effects of self-questioning reading strategies. It outlines the research design, population and sample, instruments used for data collection, and methods for data analysis. The study uses a quasi-experimental design with pre- and post-tests to evaluate the impact of self-questioning instruction on reading comprehension. Questionnaires, document analysis of students' questions, and comprehension tests are used to collect data. Statistical analysis including descriptive analysis, frequency calculation, and paired t-tests will analyze the data.
Sampling techniques
The sampling technique that would be most appropriate for this scenario is:
Stratified random sampling.
The population (town of 120,000 people) can be divided into strata based on characteristics like age, gender, area of town, etc. The committee could then randomly select a specific number of people from each stratum, with the number selected from each stratum being proportional to the stratum's size within the total population. This would help ensure the sample is representative.
ISI B.STAT/M.STAT TUITION COACHING ONLINE AND LIVE
ISI M.STAT TUITION/COACHING
CRASH COURSE IN KOLKATA
STUDY MATERIALS / MOCK TESTS
/ SOLUTION OF PREVIOUS PAPERS
/ MATHEMATICAL SHORT CUTS
SEPARATE BATCHES
SOLUTION OF ALL QUESTIONS FROM TEXTBOOK AND LAST 10 YEARS.
STUDENTS CAN ALSO HAVE A CRASH COURSE FOR A SHORT SPAN OF TIME.
AND SOLUTIONS TO ALL TEXTBOOK QUESTIONS.
NOTES, SUGGESTIONS, AND MOCK TESTS.
CLASSES AT:
GIRISH PARK
MAIDAN AND
FOR ANY FURTHER DETAILS
*CONTACT:
SOURAV SIR'S CLASSES
9836793076
Sampling in research
This document provides an overview of sampling techniques used in research. It defines key terms like population, sample, and sampling. It discusses characteristics of good sampling like being representative and free from bias. Probability sampling techniques like simple random sampling, stratified sampling, and systematic sampling are explained. Advantages of sampling like reducing time and costs are highlighted. The document outlines the sampling process and essentials of sampling. Types of sampling and various sampling methods are also summarized.
SAMPLING MEANING AND TYPES
Probability and non-probability sampling were discussed. Probability sampling methods like simple random sampling, systematic sampling, stratified sampling, and cluster sampling aim to ensure each unit has an equal chance of selection. Non-probability methods like convenience sampling, judgmental sampling, and snowball sampling rely on accessibility and do not ensure equal chance of selection. While statistical agencies prefer probability sampling, businesses often use non-probability sampling for market research due to increased respondent cooperation.
What's hot (19)
Prediction-Next-Term Student Performance Prediction: A Recommender Systems Ap...
Prediction-Next-Term Student Performance Prediction: A Recommender Systems Ap...
Prediction-Improving Early Warning Systems With Categorized Course Resource U...
Prediction-Improving Early Warning Systems With Categorized Course Resource U...
AN INVESTIGATION OF THE IMPACT OF ATYPICAL PRINCIPAL PREPARATION PROGRAMS ON ...
AN INVESTIGATION OF THE IMPACT OF ATYPICAL PRINCIPAL PREPARATION PROGRAMS ON ...
ISI B.STAT/M.STAT TUITION COACHING ONLINE AND LIVE
ISI B.STAT/M.STAT TUITION COACHING ONLINE AND LIVE
Similar to Rone
7. research_design.pptx
This document discusses methodology for quantitative research, including research design, sampling techniques, and instruments. It provides information on different types of quantitative research designs like descriptive, correlational, experimental, and quasi-experimental. It also outlines various sampling techniques including probability sampling methods like simple random sampling and stratified random sampling, and non-probability sampling methods like convenience and purposive sampling. Finally, it discusses developing instruments and providing examples of different question types for surveys.
(PR2) Research Design - Practical Research 2
This document discusses methodology for quantitative research, including research design, sampling techniques, and developing research instruments. It provides information on different types of quantitative research designs like descriptive, correlational, experimental, and quasi-experimental designs. It also discusses target populations, samples, and various probability and non-probability sampling techniques. Finally, it touches on developing valid and reliable instruments to collect quantitative data.
research_design.pptx
This document discusses methodology for quantitative research, including research design, sampling techniques, and developing research instruments. It provides descriptions of common quantitative research designs like experimental, quasi-experimental, correlational, and various sampling methods. It also addresses developing instruments, ensuring validity and reliability, and collecting data. The overall methodology is to choose an appropriate research design, determine sampling strategy, construct a valid instrument, and collect data to answer the research question.
Chapter-3.pptx
The document summarizes the methodology chapter of a research study. It describes the research design as exploratory and using a cross-sectional approach to determine the relationship between students' perceptions of hands-on chemistry activities and their understanding. The study was conducted at a public high school in Marinduque, Philippines with a sample of 84 STEM students selected through simple random sampling. A 20-item questionnaire was used to collect data on students' perceptions and understanding, which was validated by teachers and students. Data gathering procedures and statistical analysis plans involving appropriate tools are also outlined.
Final Project ScenarioA researcher has administered an anxiety.docx
Final Project Scenario
A researcher has administered an anxiety survey to students enrolled in graduate level statistics courses. The survey included three subscales related to statistics anxiety: (a) interpretation anxiety, (b) test anxiety, and (c) fear of asking for help. For the items that comprised the scales, students were asked to respond using a 5 point likert-type scale ranging from (1) No Anxiety to (5) High Anxiety. Therefore, higher scores on the anxiety subscales implied higher levels of anxiety.
In addition to the statistics anxiety subscales, the survey contained a subscale related to the use of statistical software and a subscale related to self-perceived confidence concerning general computer use. Students responded to items on the statistical software subscale using a response range from (1) Strongly Disagree to (7) Strongly Agree. For the computer confidence subscale, students responded to items using a range from (1) Strongly Disagree to (5) Strongly Agree. For each of these subscales, higher scores implied higher levels of confidence.
The researcher determined the score for each subscale by computing the mean response for the items associated with the subscale. This technique resulted in subscales that had the same possible range and the items that made up the subscale.
A subsample of the researcher’s dataset contains the following variables that should be used for completing the four final projects. The variables included in the dataset are:
Variable name:
Label:
Values:
gender
1: Female
2: Male
race
1: White
2: Non-White
age
courses
Number of online courses completed
1: 0-2 courses
2: 3-7 courses
3: 8 or more courses
interpret
Anxiety associated with reading and interpreting output from analyses
test
Anxiety associated with taking a test in a statistics course
help
Anxiety associated with asking for help during a statistics course
software
Self-reported level of confidence is using statistical software
computer
Self-reported confidence in general computer use
Final Project 1:
Use SPSS to conduct the necessary analysis of the Age variable and answer each of the following questions.
Questions:
1. What is the value of n?
2. What is the mean age?
3. What is the median age?
4. What was the youngest age?
5. What was the oldest age?
6. What is the range of ages?
7. What is the standard deviation of the ages?
8. What is the value of the skewness statistic?
9. What are the values of the 25th, 50th, and 75th percentiles?
10. Present the results as they might appear in an article. This must include a table and narrative statement that provides a thorough description of the central tendency and distribution of the ages.
Final Project 2
One of the researcher’s questions involved the difference in scores on the Interpretation Anxiety subscale between male and female respondents. Use SPSS to conduct the analysis that is appropriate for this research question and answer each o ...
Educational Resarch I, II Bimestre
This document provides an overview of educational research tools and methods. It discusses different types of sampling techniques including random sampling, stratified sampling, cluster sampling, and systematic sampling. It also covers various data collection instruments such as interviews, questionnaires, tests, scales, and observations. Key aspects of research validity and reliability are defined. The document concludes with an outline of the stages involved in developing an educational research proposal.
IJCER (www.ijceronline.com) International Journal of computational Engineerin...
This document summarizes a study that used a back-propagation neural network to estimate students' word recognition abilities based on their performance on a vocabulary test. The study collected test results from 83 elementary school students and used their scores on different word frequency groups as input for the neural network model. The model was trained and tested, showing high correlation between estimated and actual vocabulary volumes. The results demonstrated that a back-propagation neural network can accurately estimate word recognition and could be an effective alternative to traditional statistical methods.
CHAP-3-manuscript-latest.docx
The document describes the research methods and procedures used in the study. It discusses that quantitative research methods were used, including a validated computational thinking assessment and survey questionnaire administered to STEM students at Greenfield Montessori School. The assessment measures students' computational thinking skills and knowledge, while the questionnaire collects data on critical thinking skills. Responses will be analyzed to investigate the relationship between computational thinking activities and improved critical thinking. The study was conducted at Greenfield Montessori School in Tanay, Rizal and involved administering assessments and questionnaires to 30 STEM students selected through snowball sampling.
Survey Method in Research
This document discusses the process of conducting surveys. It defines what a survey is and lists its key characteristics. The document outlines the main steps in conducting a survey, which include: defining the problem, identifying the target population, choosing the data collection mode, selecting a sample, preparing the instrument, pretesting the instrument, and training interviewers. It also discusses different types of surveys, sampling techniques, question formats, and other considerations for designing an effective survey.
Chapter iii
The document describes the methodology used in a study investigating the use of mind mapping to improve students' understanding of modal verbs. It outlines the following key points:
- Data will be collected through pre-tests and post-tests administered to control and experiment groups.
- The population comprises 8th grade students from a specific school, with two classes selected as the control and experiment samples.
- Variables include the independent variable of using mind mapping and the dependent variable of understanding modal verbs.
- Observation, tests, validity, reliability and normality tests will be used as research instruments. The study uses an experimental method to investigate the impact of mind mapping on one group compared to a control group.
LAMAO ELEM.pptx
This document provides guidance for developing an action research proposal. It discusses why teachers should conduct research, how to formulate an action research topic by identifying a problem or gap, developing an intervention strategy, and formulating research questions and hypotheses. It also provides tips for composing different sections of the research proposal such as scope and delimitation, participants and sampling, data collection procedures, and data analysis. The overall purpose is to equip teachers with the knowledge and skills to develop their own research proposals in order to graduate, get promoted, earn incentives, and enhance research abilities.
Research-Info.docx
This document provides information about a research study on the effects of internet-based technology on students' learning in online classes. The study will survey 94 students total across three years of a Bachelor of Technical Education in Information and Communications Technology program. The research aims to determine the relationship between students' use of technology and their learning. A questionnaire using a Likert scale will be used to collect data on students' technology access and how it impacts their learning. Descriptive analysis and ANOVA statistical tests will then analyze and describe the effects of technology found in the study data.
sampling and statiscal inference
This document provides an overview of key concepts in sampling and statistics. It defines key terms like population, parameter, sample, and sampling error. It discusses different sampling methods like simple random sampling, systematic sampling, stratified sampling, cluster sampling, and multi-stage sampling. It also covers non-probability sampling methods. The document explains how to calculate sampling error and discusses other sources of bias. Overall, it serves as an introduction to important statistical concepts for sample surveys and studies.
Handouts-PR2-Week-1.docx
This document provides information on quantitative research, including its characteristics, strengths, weaknesses, and different types. It defines quantitative research as employing numbers and statistics to come up with generalizations. It lists characteristics like large sample sizes, objectivity, and ability to generalize findings. Strengths include being objective, allowing prediction of outcomes, and enabling fast data analysis. Weaknesses are an inability to explore issues in depth and not accounting for human experiences like feelings. The types of quantitative research discussed are descriptive, correlational, ex post facto, quasi-experimental, and experimental designs.
Do boys or girls have a larger growth spurt between the grades o.docx
Do boys or girls have a larger growth spurt between the grades of two and six?
By Nerlande Monfort
CMATH 6114
Comparative Study
The Plan
Ask a Question: Do boys or girls have a larger growth spurt between the grades of two and six?
Observational Unit: The boys and girls
Variable: Heights at grades 2 and 6
Collect Appropriate Data:
Since school is closed. I will be collecting data from students at our local Elementary and Middle School. The information is housed in the nurse’s office and is accessible through her. I will take the student information which is in alphabetical order and choose every third student until I gather heights for 20 girls and 20 boys. There are a total of 100 sixth graders in the school to choose from.
Analyze the Data: My data will be organized by grade and by gender. I will use a double line plot for boys and a separate double line plot for girls. I will find the mean of each plot to determine who had the larger growth spurt over those two grades.
Interpret the Results:
My expectations are to find that at this level girls will have the larger growth spurt. I am basing this simply on past observations. Boys seem to have their growth spurt in Middle school. Possible biases may include convenience sampling since my data is only being taken from one school. I may also have a measurement bias since these student’s heights were taken by hand and then copied onto a medical card. This information was then put into the computer.
ABSTRACT
In the study, the design applied to get the data will be simple random sampling without replacement.
The data will be analyzed and conclusions made by comparison of the students total heights in their genders at the two different grades.
Background
The previous research on this topic have reported the general growth but failed to count on the ages between these two grades. The applications of the previous research reports have shown reliance and believe in the general growth pattern of growth in young school going children though they have not specified on these two ages to explain whether it’s a just a believe that girls grow faster between these grades or its true from practical research findings.
Design of the research and data collection techniques
To ensure the collection of high-quality data, the data will be obtained from the identified population to get reliable and make conclusions. There will be a proper way of designing the sampling strategy used to ensure that potential boys and girls are picked who will be drawn from a representative sample of the intended population.
Design of the research and data collection techniques cont…
The samples will be obtained in a scientifically rigorous manner to ensure the findings will be generalizable to the intended population. The analysis of the data will not be homogenously because the selected survey compares two different grades and in different genders significantly.
Design of the research and data collect ...
Sampling and instrumentation
Samples are used in research studies to represent larger populations. While studying the entire population would provide the best data, samples are smaller and less expensive. Researchers define both the target population they wish to generalize to and the accessible population they can actually study. Random sampling involves chance to select participants while nonrandom sampling selects participants based on specific characteristics. Common sampling techniques include simple random, stratified, cluster, systematic, and convenience sampling.
sampling methods
This document discusses different sampling methods used in research. It begins by defining key terms like population, sample, sampling frame, and probability versus non-probability sampling. It then describes various probability sampling techniques in detail, including simple random sampling, systematic random sampling, stratified random sampling, and cluster random sampling. The document explains the steps for implementing each method and provides examples. It also notes advantages and disadvantages of sampling methods.
Research
This document discusses different sampling methods used in research methodology. It defines sampling as selecting a representative subset of a population to determine characteristics of the whole population. It then describes four main sampling techniques: simple random sampling, stratified random sampling, systematic sampling, and cluster sampling. For each technique, it provides an example, discusses advantages and disadvantages. The document aims to explain key sampling concepts and methods used in research.
Similar to Rone (20)
Final Project ScenarioA researcher has administered an anxiety.docx
Final Project ScenarioA researcher has administered an anxiety.docx
IJCER (www.ijceronline.com) International Journal of computational Engineerin...
IJCER (www.ijceronline.com) International Journal of computational Engineerin...
Do boys or girls have a larger growth spurt between the grades o.docx
Do boys or girls have a larger growth spurt between the grades o.docx
More from Rone Ryan Desierto
1
The document discusses mathematics from theoretical and applied perspectives. As a theoretical discipline, mathematics explores abstract relationships and patterns without concern for real-world applications. However, mathematics is also an applied science where problems originate from experience and are studied to develop new systems or models. Theoretical and applied mathematics influence each other, as theoretical discoveries often later enable practical applications and solving applied problems can lead to fundamental theoretical insights. The document frames mathematics as both a science of patterns and relationships as well as a process of logical thinking.
1
The document discusses mathematics from theoretical and applied perspectives. As a theoretical discipline, mathematics explores abstract relationships and patterns without concern for real-world applications. However, mathematics is also an applied science where problems originate from experience and are studied to develop new systems or models. Theoretical and applied mathematics influence each other, though theoretical work is not constrained by reality. The document also notes mathematics relies on both logic and creativity and serves practical purposes as well as intrinsic interest.
3
This document is an approval sheet for a study comparing the performance of BSMT and BSMar-E students in math. It lists the title of the study, the adviser who examined and approved the study, and the panel of examiners. It also states that the study was accepted in partial fulfillment of the requirements for the subject of research. The study contains 3 chapters that discuss the introduction, literature review, and methodology. Appendices include the survey questionnaire, validation of the questionnaire, and an interpretation guide.
2
This document appears to be a research study presented to the faculty of VMA Global College by a group of 7 students. The study compares the performance of students in the BSMT (Bachelor of Science in Maritime Transportation) program to those in the BSMAR-E (Bachelor of Science in Marine Engineering) program in mathematics. The group leaders are listed as Jerome Marianito J. Guillermo, with 6 other students contributing to the research. The study was submitted in October 2011.
Self
The document is a self-administered questionnaire for a research study comparing the performance of BSMT and BSMar-E students. It collects respondents' course of study and age. It then asks respondents to complete tasks like converting fractions to decimals, solving algebraic expressions, and identifying trigonometry terms. The questions cover topics like fraction conversion, algebra, and trigonometry. It will treat responses confidentially and have the instrument reviewed by jurors to validate its content and appropriateness.
Ryan
This document summarizes a research study that compares the performance of BSMT and BSMAR-E students in math at VMA Global College. The study aims to analyze the profiles of the students, assess their skills in specific math topics, and determine if there are significant differences between the two groups' performance. A panel of examiners will evaluate the study, which is dedicated to the students' parents and teachers for their support in completing the research.
Rone ryan r
The Honduras flag features three equal horizontal bands of blue (top), white, and blue. In the center white band are five blue, five-pointed stars arranged in an X pattern, representing the five countries of the former Federal Republic of Central America. The design is similar to the flags of El Salvador and Nicaragua, which also feature emblems centered in the white band referring to the Central American region.
Ron
BSMT and BSMAR-E students at VMA Global College were compared based on their math performance. BSMT students on average performed better than BSMAR-E students in the areas of fractions & decimals, algebraic expressions, and trigonometry based on their age, high school attainment, and other profile factors.
Retoke
The document summarizes a math summit held by Mosaica Education to discuss strategies for improving math achievement in their schools around the world. As a result of the summit, Mosaica will implement a new system-wide Math Initiative focusing on placing math coaches in schools, increasing the number of qualified math teachers, adjusting daily schedules to allow for more math instruction time, and ensuring math is taught in a fun way. The goal is to help students develop strong math skills and become lifelong learners who can succeed globally in the 21st century.
Reliability acknowledgement statistical tools and analytical scheme
This document discusses the methodology for assessing the reliability and validity of a research instrument. It will use the Z-test method to calculate correlation coefficients and compare scores from the first and second half of the questionnaire. The questionnaire will be administered to 20 respondents with similar characteristics to the actual study participants. Data will be gathered through interview schedules and analyzed using statistical tools like percentage, mean, and tests to determine performance differences between groups. The researchers acknowledge the support provided by various individuals and institutions in conducting the study.
Introduction
The document provides an overview of Japan's history, government, and population. It discusses how Japan transitioned from isolation in the 1600s to a regional power by the early 1900s. It then summarizes Japan's defeat in WWII and recovery to become an economic leader. The document also notes key details about Japan's population trends, including an aging society and low birth rates. It concludes with brief descriptions of Japan's emperor and prime minister roles in the government.
Gimu jmj
This document appears to be a research study comparing the math performance of BSMT (Bachelor of Science in Marine Transportation) and BSMAR-E (Bachelor of Science in Marine Engineering) students at VMA Global College. It includes an introduction, objectives, hypothesis, scope, definitions of terms, theoretical framework, and significance of the study. The study aims to analyze and compare the math capabilities of BSMT3 and BSMAR-E3 students in areas like fractions, decimals, volume, pressure, and conversions. It hopes to determine if there are significant differences in performance between the two programs and how this could benefit the school, students, faculty and maritime industry.
Finish chapter 1 of research
This document appears to be a research study comparing the math performance of BSMT (Bachelor of Science in Maritime Transportation) students and BSMarE (Bachelor of Science in Marine Engineering) students at VMA Global College. It includes an introduction, acknowledgments, dedication, and the beginning of chapter 1 which provides some background on the history and development of mathematics. The study was conducted by a group of 9 BSMT students and submitted to fulfill a research requirement.
F2
The required mathematics and science courses enhance students' ability to think quantitatively, critically, and logically. Students study fundamental math concepts like algebra, trigonometry, and calculus. They also take courses in chemistry and physics to understand natural science and technology issues. The courses teach students to apply scientific methods, collect and analyze data, and use math to solve problems in other disciplines.
Chapter 2
The document summarizes two foreign studies related to mathematics education. The first study discusses a math summit held by Mosaica Education to explore strategies for improving math achievement. As a result, Mosaica will implement a new Math Initiative focusing on math coaches, teachers, scheduling, and making math fun. The second section discusses mathematics course requirements and learning objectives at the college level, including applying math concepts to problem solving and other disciplines.
More from Rone Ryan Desierto (20)
Reliability acknowledgement statistical tools and analytical scheme
Reliability acknowledgement statistical tools and analytical scheme
Recently uploaded
Infrastructure Challenges in Scaling RAG with Custom AI models
Building Retrieval-Augmented Generation (RAG) systems with open-source and custom AI models is a complex task. This talk explores the challenges in productionizing RAG systems, including retrieval performance, response synthesis, and evaluation. We’ll discuss how to leverage open-source models like text embeddings, language models, and custom fine-tuned models to enhance RAG performance. Additionally, we’ll cover how BentoML can help orchestrate and scale these AI components efficiently, ensuring seamless deployment and management of RAG systems in the cloud.
TrustArc Webinar - 2024 Global Privacy Survey
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
Building Production Ready Search Pipelines with Spark and Milvus
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
Best 20 SEO Techniques To Improve Website Visibility In SERP
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
20240605 QFM017 Machine Intelligence Reading List May 2024
Everything I found interesting about machines behaving intelligently during May 2024
GraphRAG for Life Science to increase LLM accuracy
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
Generating privacy-protected synthetic data using Secludy and Milvus
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
Climate Impact of Software Testing at Nordic Testing Days
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Ocean lotus Threat actors project by John Sitima 2024 (1).pptx
Ocean Lotus cyber threat actors represent a sophisticated, persistent, and politically motivated group that poses a significant risk to organizations and individuals in the Southeast Asian region. Their continuous evolution and adaptability underscore the need for robust cybersecurity measures and international cooperation to identify and mitigate the threats posed by such advanced persistent threat groups.
AI 101: An Introduction to the Basics and Impact of Artificial Intelligence
Imagine a world where machines not only perform tasks but also learn, adapt, and make decisions. This is the promise of Artificial Intelligence (AI), a technology that's not just enhancing our lives but revolutionizing entire industries.
Removing Uninteresting Bytes in Software Fuzzing
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
Things to Consider When Choosing a Website Developer for your Website | FODUU
Choosing the right website developer is crucial for your business. This article covers essential factors to consider, including experience, portfolio, technical skills, communication, pricing, reputation & reviews, cost and budget considerations and post-launch support. Make an informed decision to ensure your website meets your business goals.
CAKE: Sharing Slices of Confidential Data on Blockchain
Presented at the CAiSE 2024 Forum, Intelligent Information Systems, June 6th, Limassol, Cyprus.
Synopsis: Cooperative information systems typically involve various entities in a collaborative process within a distributed environment. Blockchain technology offers a mechanism for automating such processes, even when only partial trust exists among participants. The data stored on the blockchain is replicated across all nodes in the network, ensuring accessibility to all participants. While this aspect facilitates traceability, integrity, and persistence, it poses challenges for adopting public blockchains in enterprise settings due to confidentiality issues. In this paper, we present a software tool named Control Access via Key Encryption (CAKE), designed to ensure data confidentiality in scenarios involving public blockchains. After outlining its core components and functionalities, we showcase the application of CAKE in the context of a real-world cyber-security project within the logistics domain.
Paper: https://doi.org/10.1007/978-3-031-61000-4_16
Full-RAG: A modern architecture for hyper-personalization
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
Presentation of the OECD Artificial Intelligence Review of Germany
Consult the full report at https://www.oecd.org/digital/oecd-artificial-intelligence-review-of-germany-609808d6-en.htm
Programming Foundation Models with DSPy - Meetup Slides
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.
Monitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
Recently uploaded (20)
Infrastructure Challenges in Scaling RAG with Custom AI models
Infrastructure Challenges in Scaling RAG with Custom AI models
Building Production Ready Search Pipelines with Spark and Milvus
Building Production Ready Search Pipelines with Spark and Milvus
Best 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERP
20240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 2024
GraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracy
Generating privacy-protected synthetic data using Secludy and Milvus
Generating privacy-protected synthetic data using Secludy and Milvus
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Climate Impact of Software Testing at Nordic Testing Days
Climate Impact of Software Testing at Nordic Testing Days
Ocean lotus Threat actors project by John Sitima 2024 (1).pptx
Ocean lotus Threat actors project by John Sitima 2024 (1).pptx
AI 101: An Introduction to the Basics and Impact of Artificial Intelligence
AI 101: An Introduction to the Basics and Impact of Artificial Intelligence
Things to Consider When Choosing a Website Developer for your Website | FODUU
Things to Consider When Choosing a Website Developer for your Website | FODUU
CAKE: Sharing Slices of Confidential Data on Blockchain
CAKE: Sharing Slices of Confidential Data on Blockchain
Full-RAG: A modern architecture for hyper-personalization
Full-RAG: A modern architecture for hyper-personalization
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Presentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of Germany
Programming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup Slides
Monitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift.pdf
Rone
- 1. Chapter 3 METHODOLOGY In this chapter, the researcher present the research method used, the respondents of the study, the date gathering instruments and statistical tools for date analysis. Research Design This study aimed to determined the performance level BSMT 3 and BSMAR-E 3 students math of VMA Global College this 1st semester of A.Y. 2011-2012. To meet the objective of this study the descriptive research design will be used to describe the nature of situation or a given state of affairs in terms of specified aspects or factors or characteristic of individual or group or physical environment or conditions (David 2002). With this study the researcher want to know if there is a significant difference to the performance level between the BSMT 3 to BSMAR-E 3 students in math of the VMA Global College for the first semester of 2011-2012. Likewise the study would give an insights to the faculty in the administration to deliver quality education.
- 2. Subject /Respondents The respondents of the study are the third year students of the VMA Global College that will be given self-administered questionnaires. The surveyed total population is 400. However, the respondents are selected in terms of section. The total number of section of which is 7 (as the present S.Y. 2011- 2012) the respondent for section are selected randomly to present their section as a group; the researcher will have to survey the respondents. Total Population - 400 Total number of section -7 No. o students in every Section = No. of Male = 400 No. Female =0 Using the Lynch formula, the researcher got the number of sample subject to present to population on which is based on any statement about the population from which it is drawn. n=NZ2 p(1-p) Ne2 +Z2p(1-p) Where: n = Of sample subject N = Total number of section e = Margin Error (5% or 0.05%) z = Confidence level value P = Largest possible portion, usually 50% or 0.5
- 3. Sampling Technique The sampling that we will utilize in this study is a sample random sampling, which is the basic and best-know probability sampling design that give each unit of the population an equal probability or chance of being included in the sample. From the list of total number of sections in VMA Global College respondents will be selected randomly using the table of random numbers. The researchers will select randomly the section they want to survey. Out of 7 sections the researchers decide to randomly select 2 sections of BSMT 3 and BSMAR-E 3 students of the VMA Global College. Then the researchers decided to focus on 44 respondents in every selected sections. Data Collection The data that will be used the study will be obtain by using a self-administered questionnaire. The questionnaire will be given to 44 students of VMA Global College. It will be properly filled up and the questionnaire will be retrieved by the researchers. The data will be obtained from the questionnaires will be subjected to the analysis of the data. Validity of Research Instrument To test the validity of the instruments, content validity will be used. The instrument will be shown to 3 jurors for them to go over the items to job the appropriateness and to make accommodation in order to improve the research instrument. Each jurors was requested to analyze and rate the questionnaire based on criteria presented by Carter V. Good and Douglas B. Scates. Validation for questionnaire rated 3.7 which interpreted “Very Good”.