The document discusses distributions of sample means and how they relate to the population from which the samples are drawn. It states that the mean of a distribution of sample means is equal to the population mean. The variance of a distribution of sample means is equal to the population variance divided by the sample size. The distribution of sample means will be approximately normal in shape if each sample is large enough or if the population is normally distributed. It provides examples to illustrate these concepts.
The document discusses key aspects of developing research questions and hypotheses for social science research projects. It identifies several criteria for developing a good research question, including ensuring the question is feasible, interesting, novel, ethical, and relevant. It also distinguishes between different types of research questions, such as questions of fact versus values and open-ended versus closed-ended questions. The document then covers how to develop precise research hypotheses, identifying the null and alternative hypotheses. It notes that the research hypothesis may be refined as the project develops but should not change once the project begins. Finally, it provides a brief definition of a variable as anything that can take on different values.
This document discusses conducting a survey to determine people's perceptions of the advantages and risks of social media. The survey will use a descriptive research method with a questionnaire containing Likert scale questions distributed directly to respondents. Responses will be analyzed both qualitatively and quantitatively. The analysis will show what respondents think about social media and if they understand the benefits as well as risks of using social media.
The document discusses key concepts in social science research methods including reliability and validity. Reliability refers to the consistency and stability of measurement and is assessed through measures like test-retest reliability and internal consistency. Validity determines how well a test measures the intended construct and includes content validity, criterion-related validity, and construct validity. Statistical techniques like factor analysis and Cronbach's alpha in SPSS are used to evaluate reliability and validity.
This document discusses research methodology and survey methods. It outlines the typical steps in research including problem formulation, literature review, hypothesis formulation, data collection and analysis. It then discusses different types of surveys and sampling methods. It covers probability sampling techniques like simple random sampling, stratified random sampling and systematic random sampling. It also discusses non-probability sampling and different data collection sources like primary and secondary data. Finally, it discusses various methods for data processing, analysis and representation through graphs, charts and diagrams.
This document discusses hypothesis construction and testing in statistical analysis. It defines key terms like the null and alternative hypotheses. The null hypothesis states that there is no effect or difference, while the alternative explores the research question. Hypotheses must be clear, testable, specify variable relationships, be limited in scope, stated simply, and consistent with known facts. The process of hypothesis testing involves setting up the hypotheses and significance level, determining a suitable test, identifying the critical region, performing computations, and making a decision. Hypotheses are not always necessary but can add clarity to research findings. The document also contrasts inductive and deductive approaches to research.
An emprirical investigation into factors affecting service quality among indi...iaemedu
This document summarizes a study that investigated factors affecting service quality among Indian airline service providers. A survey was conducted of 200 passengers at Coimbatore Airport to determine the significant factors influencing their perceptions of service quality. The top five factors identified were price, politeness of crew members, consistency between communications and experiences, check-in of luggage, and convenience of flight timings. The study concluded that passengers perceive service quality as a combination of physical, interaction, and corporate dimensions, which all need equal priority from Indian airline providers.
The document discusses various techniques for data analysis. It begins by explaining the concepts of data analysis and categories such as descriptive, statistical/mathematical. Common statistical methods are described including descriptive statistics which use sample data to explain population phenomena, and inferential statistics which use samples to infer population parameters and relationships. Examples of descriptive statistics like mean, median and quartiles are provided. The document concludes by emphasizing the importance of choosing the right technique for the research problem and avoiding common mistakes in data analysis.
The document summarizes a survey that will examine children and parents' views on social media usage versus time spent with friends and family. The survey will use descriptive research and questionnaires with Likert scale questions for children and parents. It will analyze responses to understand the perceived influence of social networking on family relationships and correlations between online and real-life interactions.
Normative Analysis and Statistical Treatment/Validity of the Likert ScalePeter J Stavroulakis
This document discusses the normative analysis and statistical treatment of validity for the Likert scale. It explores how the Likert scale implicitly discretizes emotions by measuring intensity on topics like mathematics. While the Likert scale treats responses as ordinal, averaging responses could be treated as interval if the underlying continuous domain was discretized into equal intervals. Further investigation is needed from subjects' perspectives to extract models for attitude instruments and pair them with experimental data to fully validate the statistical treatment of Likert scale responses.
A Hypothesis is a supposition or explanation (theory) that is provisionally accepted in order to interpret certain events or phenomena, and to provide guidance for further investigation. This presentation elucidates hypothesis in research.
The document discusses the Likert scale and provides an example. A Likert scale was used to rate user responses to the UI of Wikipedia from 1 to 5. The mean response of 3.6 was calculated, indicating that users almost agreed with the UI. Various types of variables are also defined, including categorical, ordinal, interval and ratio, and the appropriate statistical analyses for each are identified.
The document outlines the key components of a research methods chapter, including the research method used, population and sampling design, research instrument, data gathering procedure, and statistical treatment. It provides examples and guidelines for how to describe each component, such as defining the research method, explaining the sampling technique and sample size, describing the structure of the research instrument, and discussing how data was collected and analyzed.
understanding the validity and increased scrutiny of data used for compliance...All4 Inc.
This document discusses the validity and scrutiny of data used for environmental compliance purposes. It outlines the five components of next generation compliance according to the EPA: advanced monitoring, electronic reporting, regulation and permit design, innovative enforcement, and transparency. It then discusses increased regulatory scrutiny and the importance of understanding CMS data systems, management, and validation processes to ensure compliance.
This is a brief (exploratory) discussion of how to run statistical analysis of responses to Likert items. The data used is from a study I ran on users of the PARC Wikipedia dashboard "WikiDashboard" looking at how the tool changed perceptions of credibility.
The document discusses sampling and hypothesis testing. It defines key concepts like population, sample, parameter, statistic, sampling distribution, null hypothesis, alternative hypothesis, type I and type II errors. It explains different sampling methods and how to test hypotheses about population means using z-tests. Examples are provided to illustrate hypothesis testing for single and two population means. The summary tests hypotheses about population means using z-scores and critical values at given significance levels.
1. The students conducted a hypothesis test to determine if the average cost of textbooks reported by the college bookstore was accurate. Based on a sample of 100 students with a mean cost of $52.80, the students failed to reject the null hypothesis that the average cost is $52.
2. Environmentalists tested the claim of factories that they lowered the average pollutant levels in a river. Based on a sample of 50 with a mean of 32.5 ppm, the environmentalists failed to reject the null hypothesis that the average is 34 ppm.
3. A dental association tested if the estimated average family dental expenses of $1135 was accurate for their region. Based on a sample of 22 families with
The document discusses steps 4 and 5 of the research process - theoretical framework and hypothesis generation. It defines a theoretical framework as identifying and labeling variables and their relationships. A theoretical framework provides the foundation for developing testable hypotheses. Variables can be dependent, independent, moderating, or intervening. The document provides examples of each variable type. It emphasizes that a theoretical framework must clearly define the variables and their hypothesized relationships, along with explanations for why the relationships are expected to exist. Hypotheses are conjectured relationships between two or more variables expressed as testable statements. The document concludes by providing an example theoretical framework for air safety violations at Delta Airlines, identifying relevant variables and their hypothesized relationships.
Pilot Study for Validity and Reliability of an Aptitude TestBahram Kazemian
The study was conducted in the department of the English University of Gujrat during Spring- 2012 semester. A question
paper was designed to check the aptitude of the intermediate students of population 25. There were three sections; Grammar, vocabulary and reading comprehension, in the question paper. Section: A (Grammar) was proved valid with 84.33 % of validity. The validity of Section: B (vocabulary) and Section C (reading comprehension) were 91.64 % and 52.00 respectively. As a whole, the validity of all the questions was 75.99 %. Thus, the designed aptitude test may be considered reliable.
The document discusses distributions of sample means and how they relate to the population from which the samples are drawn. It states that the mean of a distribution of sample means is equal to the population mean. The variance of a distribution of sample means is equal to the population variance divided by the sample size. The distribution of sample means will be approximately normal in shape if each sample is large enough or if the population is normally distributed. It provides examples to illustrate these concepts.
The document discusses key aspects of developing research questions and hypotheses for social science research projects. It identifies several criteria for developing a good research question, including ensuring the question is feasible, interesting, novel, ethical, and relevant. It also distinguishes between different types of research questions, such as questions of fact versus values and open-ended versus closed-ended questions. The document then covers how to develop precise research hypotheses, identifying the null and alternative hypotheses. It notes that the research hypothesis may be refined as the project develops but should not change once the project begins. Finally, it provides a brief definition of a variable as anything that can take on different values.
This document discusses conducting a survey to determine people's perceptions of the advantages and risks of social media. The survey will use a descriptive research method with a questionnaire containing Likert scale questions distributed directly to respondents. Responses will be analyzed both qualitatively and quantitatively. The analysis will show what respondents think about social media and if they understand the benefits as well as risks of using social media.
The document discusses key concepts in social science research methods including reliability and validity. Reliability refers to the consistency and stability of measurement and is assessed through measures like test-retest reliability and internal consistency. Validity determines how well a test measures the intended construct and includes content validity, criterion-related validity, and construct validity. Statistical techniques like factor analysis and Cronbach's alpha in SPSS are used to evaluate reliability and validity.
This document discusses research methodology and survey methods. It outlines the typical steps in research including problem formulation, literature review, hypothesis formulation, data collection and analysis. It then discusses different types of surveys and sampling methods. It covers probability sampling techniques like simple random sampling, stratified random sampling and systematic random sampling. It also discusses non-probability sampling and different data collection sources like primary and secondary data. Finally, it discusses various methods for data processing, analysis and representation through graphs, charts and diagrams.
This document discusses hypothesis construction and testing in statistical analysis. It defines key terms like the null and alternative hypotheses. The null hypothesis states that there is no effect or difference, while the alternative explores the research question. Hypotheses must be clear, testable, specify variable relationships, be limited in scope, stated simply, and consistent with known facts. The process of hypothesis testing involves setting up the hypotheses and significance level, determining a suitable test, identifying the critical region, performing computations, and making a decision. Hypotheses are not always necessary but can add clarity to research findings. The document also contrasts inductive and deductive approaches to research.
An emprirical investigation into factors affecting service quality among indi...iaemedu
This document summarizes a study that investigated factors affecting service quality among Indian airline service providers. A survey was conducted of 200 passengers at Coimbatore Airport to determine the significant factors influencing their perceptions of service quality. The top five factors identified were price, politeness of crew members, consistency between communications and experiences, check-in of luggage, and convenience of flight timings. The study concluded that passengers perceive service quality as a combination of physical, interaction, and corporate dimensions, which all need equal priority from Indian airline providers.
The document discusses various techniques for data analysis. It begins by explaining the concepts of data analysis and categories such as descriptive, statistical/mathematical. Common statistical methods are described including descriptive statistics which use sample data to explain population phenomena, and inferential statistics which use samples to infer population parameters and relationships. Examples of descriptive statistics like mean, median and quartiles are provided. The document concludes by emphasizing the importance of choosing the right technique for the research problem and avoiding common mistakes in data analysis.
The document summarizes a survey that will examine children and parents' views on social media usage versus time spent with friends and family. The survey will use descriptive research and questionnaires with Likert scale questions for children and parents. It will analyze responses to understand the perceived influence of social networking on family relationships and correlations between online and real-life interactions.
Normative Analysis and Statistical Treatment/Validity of the Likert ScalePeter J Stavroulakis
This document discusses the normative analysis and statistical treatment of validity for the Likert scale. It explores how the Likert scale implicitly discretizes emotions by measuring intensity on topics like mathematics. While the Likert scale treats responses as ordinal, averaging responses could be treated as interval if the underlying continuous domain was discretized into equal intervals. Further investigation is needed from subjects' perspectives to extract models for attitude instruments and pair them with experimental data to fully validate the statistical treatment of Likert scale responses.
A Hypothesis is a supposition or explanation (theory) that is provisionally accepted in order to interpret certain events or phenomena, and to provide guidance for further investigation. This presentation elucidates hypothesis in research.
The document discusses the Likert scale and provides an example. A Likert scale was used to rate user responses to the UI of Wikipedia from 1 to 5. The mean response of 3.6 was calculated, indicating that users almost agreed with the UI. Various types of variables are also defined, including categorical, ordinal, interval and ratio, and the appropriate statistical analyses for each are identified.
The document outlines the key components of a research methods chapter, including the research method used, population and sampling design, research instrument, data gathering procedure, and statistical treatment. It provides examples and guidelines for how to describe each component, such as defining the research method, explaining the sampling technique and sample size, describing the structure of the research instrument, and discussing how data was collected and analyzed.
understanding the validity and increased scrutiny of data used for compliance...All4 Inc.
This document discusses the validity and scrutiny of data used for environmental compliance purposes. It outlines the five components of next generation compliance according to the EPA: advanced monitoring, electronic reporting, regulation and permit design, innovative enforcement, and transparency. It then discusses increased regulatory scrutiny and the importance of understanding CMS data systems, management, and validation processes to ensure compliance.
This is a brief (exploratory) discussion of how to run statistical analysis of responses to Likert items. The data used is from a study I ran on users of the PARC Wikipedia dashboard "WikiDashboard" looking at how the tool changed perceptions of credibility.
The document discusses sampling and hypothesis testing. It defines key concepts like population, sample, parameter, statistic, sampling distribution, null hypothesis, alternative hypothesis, type I and type II errors. It explains different sampling methods and how to test hypotheses about population means using z-tests. Examples are provided to illustrate hypothesis testing for single and two population means. The summary tests hypotheses about population means using z-scores and critical values at given significance levels.
1. The students conducted a hypothesis test to determine if the average cost of textbooks reported by the college bookstore was accurate. Based on a sample of 100 students with a mean cost of $52.80, the students failed to reject the null hypothesis that the average cost is $52.
2. Environmentalists tested the claim of factories that they lowered the average pollutant levels in a river. Based on a sample of 50 with a mean of 32.5 ppm, the environmentalists failed to reject the null hypothesis that the average is 34 ppm.
3. A dental association tested if the estimated average family dental expenses of $1135 was accurate for their region. Based on a sample of 22 families with
The document discusses steps 4 and 5 of the research process - theoretical framework and hypothesis generation. It defines a theoretical framework as identifying and labeling variables and their relationships. A theoretical framework provides the foundation for developing testable hypotheses. Variables can be dependent, independent, moderating, or intervening. The document provides examples of each variable type. It emphasizes that a theoretical framework must clearly define the variables and their hypothesized relationships, along with explanations for why the relationships are expected to exist. Hypotheses are conjectured relationships between two or more variables expressed as testable statements. The document concludes by providing an example theoretical framework for air safety violations at Delta Airlines, identifying relevant variables and their hypothesized relationships.
Pilot Study for Validity and Reliability of an Aptitude TestBahram Kazemian
The study was conducted in the department of the English University of Gujrat during Spring- 2012 semester. A question
paper was designed to check the aptitude of the intermediate students of population 25. There were three sections; Grammar, vocabulary and reading comprehension, in the question paper. Section: A (Grammar) was proved valid with 84.33 % of validity. The validity of Section: B (vocabulary) and Section C (reading comprehension) were 91.64 % and 52.00 respectively. As a whole, the validity of all the questions was 75.99 %. Thus, the designed aptitude test may be considered reliable.
1. The document discusses research design and methods for social science research. It focuses on maximizing systematic variance and minimizing error variance.
2. It examines the "Max Min Con" principle for research design, which aims to maximize systematic variance through treatment while minimizing error variance. It also discusses controlling for extraneous variables.
3. The document outlines various research design approaches including pre-experimental, true experimental, and quasi-experimental designs. It evaluates threats to internal and external validity for different design types.
The document discusses the scientific method and research process. It covers topics like the different types of research (e.g. quantitative vs. qualitative), stages of research like developing research questions and hypotheses, variables that are studied, and techniques for idea generation. The overall goal of research is to systematically generate and test knowledge to better understand the world.
This document discusses key terminology and methods used in qualitative research including phenomenology, interpretivism, hermeneutics, participant observation, in-depth interviews, case studies, ethnography, grounded theory, sampling techniques, qualitative interviewing, life histories, focus groups, recording observations, qualitative data processing and analysis. It also covers the strengths, weaknesses and standards for evaluating qualitative studies.
This document provides a template for reviewing related literature in a research paper. It outlines 8 key sections to address: 1) key theories, concepts and ideas, 2) epistemological and ontological approaches, 3) research questions or hypotheses, 4) topic relevance, 5) gaps in existing literature, 6) political standpoint considerations, 7) major issues to examine, and 8) overall significance. It also provides a generic 5-part structure for literature reviews with sections on exploration, analysis, discussion, criticism, and summary.
The document discusses several key concepts in sociological theory, including:
1) Auguste Comte, regarded as the founder of sociology, who argued that human thought progresses through theological, metaphysical, and positive/scientific stages of development.
2) Phenomenology, which studies conscious experience and how individuals construct the social world, influencing sociologists like Alfred Schutz.
3) Theories, concepts, propositions, hypotheses, and paradigms as important components of sociological frameworks for understanding social phenomena.
4) Emile Durkheim's study of suicide, which hypothesized that stronger social integration leads to stronger social cohesion within a society.