Correlational-Research.pptx
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Correlational research is a non-experimental method that studies the relationship between two variables. It establishes whether and how two variables are related without manipulating the variables. There are three types of relationships: positive correlation, negative correlation, and zero correlation. The strength of a relationship is measured on a scale from -1 to 1. Correlational research is non-experimental, backward-looking as it analyzes past data, and dynamic as the relationships between variables can change over time.
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Final corraletional research ppts
This document discusses correlational research, which aims to describe relationships between variables and measure their strength. Correlational research observes how variables change together without manipulation. A correlation indicates the direction, form, and consistency of a relationship. Positive relationships involve variables changing in the same direction, while negative relationships involve opposite direction changes. Correlational designs can be explanatory, relating co-varying variables, or predictive, identifying predictors of an outcome variable. Correlational research allows investigating relationships but cannot determine causation due to low internal validity.
Relational and correlational research
Correlational research investigates the connection between two or more variables that are already present in a group. The aim is to identify if changes in one variable result in changes in another. There are three types: positive correlation where increases in one variable produce increases in another; negative correlation where increases in one produce decreases in another; and no correlation where the variables are independent. Common data collection methods include naturalistic observation, archival data, and surveys. Correlational research is non-experimental, backward-looking, and dynamic as relationships can change over time. The correlation coefficient indicates the strength and direction of relationships between variables.
Nw Microsoft PowerPoint Presentation.pptx
Correlational research establishes relationships between variables without determining cause, using dependent variables only. It demonstrates relationships exist but not causation. A correlation coefficient measures the direction and strength of relationships between two variables on a scale from -1 to 1, with higher positive or negative values indicating stronger linear relationships. Statistical analysis evaluates numerical data through correlation coefficients and scatter plots to describe variable relationships.
Correlation in Statistical Analysis .pdf
Correlation analyzes the relationship between two or more variables. It provides a quantitative measure of their degree of relationship but does not indicate causation. There can be positive correlation, where variables increase together, negative correlation where they change oppositely, or no correlation. Correlation coefficients range from -1 to 1, with higher positive or negative values indicating a stronger linear relationship. Common coefficients are Pearson's r and Spearman's rho. While correlation reveals associations, it cannot prove one variable causes another.
Correlation
Correlation is a statistical technique used to determine the degree of relationship between two variables. Correlational research aims to identify and describe relationships but does not imply causation. Positive correlation indicates high scores on one variable are associated with high scores on the other, while negative correlation means high scores on one variable are associated with low scores on the other. Correlational research can be used for explanatory or predictive purposes. More complex techniques like multiple regression allow prediction using combinations of variables. Threats to internal validity like subject characteristics must be controlled.
Correlation Studies - Descriptive Studies
Descriptive studies- meaning, objectives.
Correlation Studies - introduction, definition, significance of study, types of correlation, methods of studying, merits and demerits
Correlation
This ppt is made to complete from our lecture about Correlation Design in research
Check our website https://bclassof2018.wixsite.com/website
Correlations
Correlational studies examine the systematic relationship between two variables. Psychologists may conduct a correlation study to determine if there is a real relationship between variables like height and shoe size, which were initially observed to possibly be related based on a small sample. A correlational analysis identifies the strength and direction of the association between two co-variables without distinguishing a dependent or independent variable. The correlation coefficient calculated ranges from -1 to +1, indicating the direction and strength of the relationship. While correlations can reveal trends, they do not imply that one variable causes the other.
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Final corraletional research ppts
This document discusses correlational research, which aims to describe relationships between variables and measure their strength. Correlational research observes how variables change together without manipulation. A correlation indicates the direction, form, and consistency of a relationship. Positive relationships involve variables changing in the same direction, while negative relationships involve opposite direction changes. Correlational designs can be explanatory, relating co-varying variables, or predictive, identifying predictors of an outcome variable. Correlational research allows investigating relationships but cannot determine causation due to low internal validity.
Relational and correlational research
Correlational research investigates the connection between two or more variables that are already present in a group. The aim is to identify if changes in one variable result in changes in another. There are three types: positive correlation where increases in one variable produce increases in another; negative correlation where increases in one produce decreases in another; and no correlation where the variables are independent. Common data collection methods include naturalistic observation, archival data, and surveys. Correlational research is non-experimental, backward-looking, and dynamic as relationships can change over time. The correlation coefficient indicates the strength and direction of relationships between variables.
Nw Microsoft PowerPoint Presentation.pptx
Correlational research establishes relationships between variables without determining cause, using dependent variables only. It demonstrates relationships exist but not causation. A correlation coefficient measures the direction and strength of relationships between two variables on a scale from -1 to 1, with higher positive or negative values indicating stronger linear relationships. Statistical analysis evaluates numerical data through correlation coefficients and scatter plots to describe variable relationships.
Correlation in Statistical Analysis .pdf
Correlation analyzes the relationship between two or more variables. It provides a quantitative measure of their degree of relationship but does not indicate causation. There can be positive correlation, where variables increase together, negative correlation where they change oppositely, or no correlation. Correlation coefficients range from -1 to 1, with higher positive or negative values indicating a stronger linear relationship. Common coefficients are Pearson's r and Spearman's rho. While correlation reveals associations, it cannot prove one variable causes another.
Correlation
Correlation is a statistical technique used to determine the degree of relationship between two variables. Correlational research aims to identify and describe relationships but does not imply causation. Positive correlation indicates high scores on one variable are associated with high scores on the other, while negative correlation means high scores on one variable are associated with low scores on the other. Correlational research can be used for explanatory or predictive purposes. More complex techniques like multiple regression allow prediction using combinations of variables. Threats to internal validity like subject characteristics must be controlled.
Correlation Studies - Descriptive Studies
Descriptive studies- meaning, objectives.
Correlation Studies - introduction, definition, significance of study, types of correlation, methods of studying, merits and demerits
Correlation
This ppt is made to complete from our lecture about Correlation Design in research
Check our website https://bclassof2018.wixsite.com/website
Correlations
Correlational studies examine the systematic relationship between two variables. Psychologists may conduct a correlation study to determine if there is a real relationship between variables like height and shoe size, which were initially observed to possibly be related based on a small sample. A correlational analysis identifies the strength and direction of the association between two co-variables without distinguishing a dependent or independent variable. The correlation coefficient calculated ranges from -1 to +1, indicating the direction and strength of the relationship. While correlations can reveal trends, they do not imply that one variable causes the other.
CORRELATIONAL-RESEARCH.pptx
This document discusses correlational research, which examines relationships between variables without manipulating them. It defines correlational research and describes its non-experimental design, purpose to test associations between variables with limited control, and high external validity. Examples of positive, negative, and no correlations are provided. Characteristics like being non-experimental and backward-looking are outlined. Common data collection methods include surveys, observations, and secondary data. Correlation and regression analyses can quantify and predict relationships between variables, though correlation does not imply causation due to directionality and third variable problems.
Biostatistics - Correlation explanation.pptx
This document discusses correlation and methods for studying correlation. Correlation refers to the relationship between two variables, where a positive correlation means the variables change in the same direction and a negative correlation means they change in opposite directions. Methods for studying correlation include scatter plots, Karl Pearson's coefficient of correlation (denoted r), and the coefficient of determination (denoted r2). The coefficient of correlation quantifies the strength and direction of the linear relationship between variables while the coefficient of determination indicates how much variability in one variable can be predicted from the other variable.
HOWs CORRELATIONAL STUDIES are performed
Correlational research establishes relationships between variables but does not determine cause-and-effect. It uses correlation coefficients to measure the direction and strength of relationships between two variables. Statistical analysis of scores from each individual on two variables can show their relationship graphically in a scatter plot. Experimental research determines cause-and-effect relationships, while descriptive research explores characteristics without determining relationships.
Correlational research.pptx
The document discusses correlational research, which examines relationships between two variables without manipulating them. Correlational research can establish that variables are related but cannot prove one causes the other. Key points covered include:
- Correlation coefficients measure the strength and direction of relationships between variables.
- Positive correlations indicate variables increase together, while negative correlations mean one decreases as the other increases.
- Correlational research has advantages like lower cost but cannot prove causation like experiments can.
- Common data collection methods are naturalistic observation, surveys, archival data, and secondary data. Correlation and regression analyses are frequently used to analyze correlational data and make predictions.
Correlational research
Correlational research examines the relationships between two or more variables. It determines how changes in one variable correlate with changes in another variable without external influence. The purpose is to understand statistical relationships between variables by analyzing collected data and determining a correlation coefficient between -1 and 1. A positive correlation means an increase in one variable correlates with an increase in the other. A negative correlation means an increase in one variable correlates with a decrease in the other. Zero correlation means the variables are independent.
Correlational Research
Correlational research examines relationships between two or more quantifiable variables without manipulating the variables. It involves collecting data from a sample of at least 30 participants to determine if a relationship exists and the degree of relationship. Positive correlations indicate that as one variable increases, the other also increases, while negative correlations show an inverse relationship. Correlation coefficients between -1 and +1 indicate the strength and direction of relationships. Common types of correlational research include natural observation, surveys, and analyzing archival data.
Quantitative Research Design
This document discusses different types of quantitative research design, including correlational research, ex post facto research, experimental research, quasi-experimental research, single case research, and meta-analysis research. Correlational research examines relationships between two variables, while ex post facto research investigates possible cause-and-effect relationships by observing existing conditions retrospectively. Experimental research involves deliberately controlling and manipulating independent variables to observe their effects. Quasi-experimental research controls measurement factors but not exposure factors. Single case research assesses aspects of behavior over time through intervention effects. Meta-analysis aggregates results from multiple studies. Key terms discussed include correlation, variables, and ex post facto.
Presentation1
Correlational studies examine the relationship between two or more variables. They measure variables in different categories and look for relationships between them, such as more democratic parents being correlated with better-behaved children. Correlational studies can help make predictions but cannot prove causation, as there may be other unmeasured factors influencing the relationship between the variables. Correlational studies also do not show the direction of the relationship or reveal if another variable is causing it.
Presentation1
Correlational studies examine the relationship between two or more variables. They measure variables in different categories and look for relationships between them, such as more democratic parents being correlated with better behaved children. Correlational studies can reveal relationships among variables and make predictions, but cannot prove causation, as there may be other unmeasured factors influencing the relationship. Correlations can be positive, with variables increasing or decreasing together, or negative, with variables changing in opposite directions.
CORRELATION.ppt
This document discusses correlation and regression analysis. It defines correlation as a statistical measure of how two variables are related or associated. A correlation coefficient between -1 and 1 indicates the strength and direction of the linear relationship between variables. Scatterplots can show these relationships visually. The Pearson correlation coefficient is the most common measure used, where 0 indicates no correlation and 1 or -1 indicates perfect correlation. Correlation only measures linear relationships and does not necessarily imply causation between variables.
correlational research method
The document discusses correlational research methods, which examine relationships between two measured variables without manipulating variables. Correlational research can describe the direction (positive/negative), form (linear/nonlinear), and strength (magnitude) of relationships. Statistical analyses like Pearson correlation and regression can analyze correlational data. While correlational research allows observation of many variables, it cannot prove causation, as relationships may be due to other unmeasured variables.
Correlations and t scores (2)
This document discusses key concepts related to correlations, t scores, and inferential statistics. It defines populations and samples, and explains that samples are used to make generalizations about populations. It also discusses variables, data, and different types of research methods including correlational and experimental designs. Specifically, it explains what correlations measure, how to interpret positive, negative, and no correlations. It emphasizes that correlation does not imply causation and discusses reasons for this. Finally, it introduces t scores as a way to standardize comparisons between distributions.
Nonexperimental quantitative design
This document discusses nonexperimental quantitative research designs, including descriptive and correlational designs. Descriptive designs aim to observe and describe a situation as it naturally occurs, while correlational designs measure relationships between two or more variables. Correlations can be positive, meaning variables increase together, or negative, meaning they change in opposite directions. Correlation coefficients range from +1 to -1 to indicate the strength of relationships. Correlational research has advantages like observing natural phenomena, but cannot determine cause and effect.
Correlational research - Research Methodology - Manu Melwin Joy
A correlation is simply defined as a relationship between two variables. The whole purpose of using correlations in research is to figure out which variables are connected.
Chi-Square Test Non Parametric Test Categorical Variable
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This document discusses correlational research designs. Correlational studies can show relationships between two variables to indicate cause and effect or predict future outcomes. There are three main types of correlational studies: observational research, survey research, and archival research. Correlational research allows analysis of relationships among many variables and provides correlation coefficients to measure direction and degree of relationships. Interpreting correlations involves scattergrams, correlation coefficients from -1 to 1, and determining explained variance through r-squared values. However, correlation does not necessarily prove causation as third variables could be the true cause.
Discuss the strengths and weaknesses of correlational and regression.pdf
Discuss the strengths and weaknesses of correlational and regression studies; discuss concepts
such as positive and negative correlations, correlation coefficients, confounding, and causality.
Solution
M. Ed (1 st ) SESSION: 2011-2012 DEPARTMENT OF EDUCATIONAL TRAINING Nature
of Correlational Studies Types of Correlations Positive and negative Correlation: A positive
correlation means high scores on the one variablehave a propensity to be associated with high
scores on other variable. A negative correlationmeans high score on the one variable is related
with low scores on the other variable and lowscores on the one are associated with high scores
on the either.Linear and Non Linear Correlation: The correlation between two variables is
believed to belinear if be consistent to a unit change in one variable, there is constant change in
other variableover entire array of values. The relationship between two variables is thought to be
non-linear if corresponding to a unit change in first variable, but the other variable does not
change at aconstant rate, but at varying rate. Types of Correlational Designs There are many
methods for correlational studies with their own strengths and weaknesses. Onetrendy method is
called naturalistic observation, which necessitates a researcher to observe andrecord the natural
environment without interference. One benefit of naturalistic observation isthat the researcher is
observing variables in a natural state. Some limitations are that it can bedifficult to control the
variables or to avoid outside influences from faking the results.Another type of correlational
research is called the survey method. Surveys are easy on the pocket and swift, and can be used
to gather information from very large sample size. However, poorly written survey questions can
distort results. Another hitch is that survey results are alsodependent on survey respondents, who
are not always trustworthy.A third method for correlational design is archival research, which
analyzes historical records.An improvement in this method is that it’s a workable way to analyze
large amounts of datawithout expending a lot of money. A lapse of this particular research
method is that theresearcher has no way of knowing if the original data collection methods were
reliable.Correlational studies are a helpful tool for conducting research. However, it must be kept
in mindthat no study method is perfect. Researchers must take into consideration the limitations
of boththeir preferred research method and correlational studies as a general rule.Correlational
designs may be cross-sectional, in which all observations are made at the same point with
context to time, or they may be longitudinal, in which calculations are made at two or more
different time points.
COR-RELATIONAL DESIGN
This document discusses correlational research design, which examines relationships between variables without manipulation. It has independent and dependent variables, and the researcher determines how changes in one variable correlate with changes in the other through statistical analysis. Correlational design can be either prospective, observing relationships from cause to effect over time, or retrospective, examining current phenomena in relation to past events. Examples given are a prospective study of tsunami stress and a retrospective study of adolescent drug abuse risk factors.
CO-RELATIONAL DESIGN
This document discusses correlational research design, which examines relationships between variables without manipulation. It has independent and dependent variables, and the researcher determines how changes in one variable correlate with changes in the other through statistical analysis. Correlational design can be either prospective, observing relationships from cause to effect over time, or retrospective, examining current phenomena in relation to past events. Examples given are a prospective study of tsunami stress and a retrospective study of adolescent drug abuse risk factors.
Correlation and regression
The document discusses correlation and regression analysis. It defines correlation as the statistical relationship between two variables, where a change in one variable corresponds to a change in the other. The key types of correlation are positive, negative, simple, partial and multiple, and linear and non-linear. Regression analysis establishes the average relationship between an independent and dependent variable in order to predict or estimate values of the dependent variable based on the independent variable. Methods for studying correlation include scatter diagrams and Karl Pearson's coefficient of correlation, while regression analysis uses equations to model the linear relationship between variables.
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CORRELATIONAL-RESEARCH.pptx
This document discusses correlational research, which examines relationships between variables without manipulating them. It defines correlational research and describes its non-experimental design, purpose to test associations between variables with limited control, and high external validity. Examples of positive, negative, and no correlations are provided. Characteristics like being non-experimental and backward-looking are outlined. Common data collection methods include surveys, observations, and secondary data. Correlation and regression analyses can quantify and predict relationships between variables, though correlation does not imply causation due to directionality and third variable problems.
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This document discusses correlation and methods for studying correlation. Correlation refers to the relationship between two variables, where a positive correlation means the variables change in the same direction and a negative correlation means they change in opposite directions. Methods for studying correlation include scatter plots, Karl Pearson's coefficient of correlation (denoted r), and the coefficient of determination (denoted r2). The coefficient of correlation quantifies the strength and direction of the linear relationship between variables while the coefficient of determination indicates how much variability in one variable can be predicted from the other variable.
HOWs CORRELATIONAL STUDIES are performed
Correlational research establishes relationships between variables but does not determine cause-and-effect. It uses correlation coefficients to measure the direction and strength of relationships between two variables. Statistical analysis of scores from each individual on two variables can show their relationship graphically in a scatter plot. Experimental research determines cause-and-effect relationships, while descriptive research explores characteristics without determining relationships.
Correlational research.pptx
The document discusses correlational research, which examines relationships between two variables without manipulating them. Correlational research can establish that variables are related but cannot prove one causes the other. Key points covered include:
- Correlation coefficients measure the strength and direction of relationships between variables.
- Positive correlations indicate variables increase together, while negative correlations mean one decreases as the other increases.
- Correlational research has advantages like lower cost but cannot prove causation like experiments can.
- Common data collection methods are naturalistic observation, surveys, archival data, and secondary data. Correlation and regression analyses are frequently used to analyze correlational data and make predictions.
Correlational research
Correlational research examines the relationships between two or more variables. It determines how changes in one variable correlate with changes in another variable without external influence. The purpose is to understand statistical relationships between variables by analyzing collected data and determining a correlation coefficient between -1 and 1. A positive correlation means an increase in one variable correlates with an increase in the other. A negative correlation means an increase in one variable correlates with a decrease in the other. Zero correlation means the variables are independent.
Correlational Research
Correlational research examines relationships between two or more quantifiable variables without manipulating the variables. It involves collecting data from a sample of at least 30 participants to determine if a relationship exists and the degree of relationship. Positive correlations indicate that as one variable increases, the other also increases, while negative correlations show an inverse relationship. Correlation coefficients between -1 and +1 indicate the strength and direction of relationships. Common types of correlational research include natural observation, surveys, and analyzing archival data.
Quantitative Research Design
This document discusses different types of quantitative research design, including correlational research, ex post facto research, experimental research, quasi-experimental research, single case research, and meta-analysis research. Correlational research examines relationships between two variables, while ex post facto research investigates possible cause-and-effect relationships by observing existing conditions retrospectively. Experimental research involves deliberately controlling and manipulating independent variables to observe their effects. Quasi-experimental research controls measurement factors but not exposure factors. Single case research assesses aspects of behavior over time through intervention effects. Meta-analysis aggregates results from multiple studies. Key terms discussed include correlation, variables, and ex post facto.
Presentation1
Correlational studies examine the relationship between two or more variables. They measure variables in different categories and look for relationships between them, such as more democratic parents being correlated with better-behaved children. Correlational studies can help make predictions but cannot prove causation, as there may be other unmeasured factors influencing the relationship between the variables. Correlational studies also do not show the direction of the relationship or reveal if another variable is causing it.
Presentation1
Correlational studies examine the relationship between two or more variables. They measure variables in different categories and look for relationships between them, such as more democratic parents being correlated with better behaved children. Correlational studies can reveal relationships among variables and make predictions, but cannot prove causation, as there may be other unmeasured factors influencing the relationship. Correlations can be positive, with variables increasing or decreasing together, or negative, with variables changing in opposite directions.
CORRELATION.ppt
This document discusses correlation and regression analysis. It defines correlation as a statistical measure of how two variables are related or associated. A correlation coefficient between -1 and 1 indicates the strength and direction of the linear relationship between variables. Scatterplots can show these relationships visually. The Pearson correlation coefficient is the most common measure used, where 0 indicates no correlation and 1 or -1 indicates perfect correlation. Correlation only measures linear relationships and does not necessarily imply causation between variables.
correlational research method
The document discusses correlational research methods, which examine relationships between two measured variables without manipulating variables. Correlational research can describe the direction (positive/negative), form (linear/nonlinear), and strength (magnitude) of relationships. Statistical analyses like Pearson correlation and regression can analyze correlational data. While correlational research allows observation of many variables, it cannot prove causation, as relationships may be due to other unmeasured variables.
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This document discusses key concepts related to correlations, t scores, and inferential statistics. It defines populations and samples, and explains that samples are used to make generalizations about populations. It also discusses variables, data, and different types of research methods including correlational and experimental designs. Specifically, it explains what correlations measure, how to interpret positive, negative, and no correlations. It emphasizes that correlation does not imply causation and discusses reasons for this. Finally, it introduces t scores as a way to standardize comparisons between distributions.
Nonexperimental quantitative design
This document discusses nonexperimental quantitative research designs, including descriptive and correlational designs. Descriptive designs aim to observe and describe a situation as it naturally occurs, while correlational designs measure relationships between two or more variables. Correlations can be positive, meaning variables increase together, or negative, meaning they change in opposite directions. Correlation coefficients range from +1 to -1 to indicate the strength of relationships. Correlational research has advantages like observing natural phenomena, but cannot determine cause and effect.
Correlational research - Research Methodology - Manu Melwin Joy
A correlation is simply defined as a relationship between two variables. The whole purpose of using correlations in research is to figure out which variables are connected.
Chi-Square Test Non Parametric Test Categorical Variable
Chi-Square Test Non Parametric Test Categorical VariableNigar Kadar Mujawar,Womens College of Pharmacy,Peth Vadgaon,Kolhapur,416112
The chi-square test is used to determine if there is a significant association between two categorical variables. It can be used for independence tests between two variables or goodness-of-fit tests to determine if observed data fits a theoretical distribution. The chi-square test calculates expected frequencies and compares them to observed frequencies to determine if any differences could be due to chance or indicate a true association. It is widely applied in research fields to analyze relationships in categorical data.Correlational research
This document discusses correlational research designs. Correlational studies can show relationships between two variables to indicate cause and effect or predict future outcomes. There are three main types of correlational studies: observational research, survey research, and archival research. Correlational research allows analysis of relationships among many variables and provides correlation coefficients to measure direction and degree of relationships. Interpreting correlations involves scattergrams, correlation coefficients from -1 to 1, and determining explained variance through r-squared values. However, correlation does not necessarily prove causation as third variables could be the true cause.
Discuss the strengths and weaknesses of correlational and regression.pdf
Discuss the strengths and weaknesses of correlational and regression studies; discuss concepts
such as positive and negative correlations, correlation coefficients, confounding, and causality.
Solution
M. Ed (1 st ) SESSION: 2011-2012 DEPARTMENT OF EDUCATIONAL TRAINING Nature
of Correlational Studies Types of Correlations Positive and negative Correlation: A positive
correlation means high scores on the one variablehave a propensity to be associated with high
scores on other variable. A negative correlationmeans high score on the one variable is related
with low scores on the other variable and lowscores on the one are associated with high scores
on the either.Linear and Non Linear Correlation: The correlation between two variables is
believed to belinear if be consistent to a unit change in one variable, there is constant change in
other variableover entire array of values. The relationship between two variables is thought to be
non-linear if corresponding to a unit change in first variable, but the other variable does not
change at aconstant rate, but at varying rate. Types of Correlational Designs There are many
methods for correlational studies with their own strengths and weaknesses. Onetrendy method is
called naturalistic observation, which necessitates a researcher to observe andrecord the natural
environment without interference. One benefit of naturalistic observation isthat the researcher is
observing variables in a natural state. Some limitations are that it can bedifficult to control the
variables or to avoid outside influences from faking the results.Another type of correlational
research is called the survey method. Surveys are easy on the pocket and swift, and can be used
to gather information from very large sample size. However, poorly written survey questions can
distort results. Another hitch is that survey results are alsodependent on survey respondents, who
are not always trustworthy.A third method for correlational design is archival research, which
analyzes historical records.An improvement in this method is that it’s a workable way to analyze
large amounts of datawithout expending a lot of money. A lapse of this particular research
method is that theresearcher has no way of knowing if the original data collection methods were
reliable.Correlational studies are a helpful tool for conducting research. However, it must be kept
in mindthat no study method is perfect. Researchers must take into consideration the limitations
of boththeir preferred research method and correlational studies as a general rule.Correlational
designs may be cross-sectional, in which all observations are made at the same point with
context to time, or they may be longitudinal, in which calculations are made at two or more
different time points.
COR-RELATIONAL DESIGN
This document discusses correlational research design, which examines relationships between variables without manipulation. It has independent and dependent variables, and the researcher determines how changes in one variable correlate with changes in the other through statistical analysis. Correlational design can be either prospective, observing relationships from cause to effect over time, or retrospective, examining current phenomena in relation to past events. Examples given are a prospective study of tsunami stress and a retrospective study of adolescent drug abuse risk factors.
CO-RELATIONAL DESIGN
This document discusses correlational research design, which examines relationships between variables without manipulation. It has independent and dependent variables, and the researcher determines how changes in one variable correlate with changes in the other through statistical analysis. Correlational design can be either prospective, observing relationships from cause to effect over time, or retrospective, examining current phenomena in relation to past events. Examples given are a prospective study of tsunami stress and a retrospective study of adolescent drug abuse risk factors.
Correlation and regression
The document discusses correlation and regression analysis. It defines correlation as the statistical relationship between two variables, where a change in one variable corresponds to a change in the other. The key types of correlation are positive, negative, simple, partial and multiple, and linear and non-linear. Regression analysis establishes the average relationship between an independent and dependent variable in order to predict or estimate values of the dependent variable based on the independent variable. Methods for studying correlation include scatter diagrams and Karl Pearson's coefficient of correlation, while regression analysis uses equations to model the linear relationship between variables.
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Educational facilities play an important role in effective teaching and learning. They are developed based on comprehensive planning that involves stakeholders. Key principles of educational facility planning include maximizing collaboration, building proactive management, and planning schools as neighborhood centers that are accessible to the entire community. School mapping is also an important process that involves analyzing the distribution and capacity of existing schools to identify the need for new or expanded facilities.
WEEK 4- PRESENT EGG DISHES.pptx
This document provides instructions and information about presenting egg dishes. It discusses factors to consider like plate size, height, odd numbers, and the clock method of placement. Students will learn to identify cooking methods, garnishing, side dishes and evaluate presentations based on a rubric. Activities include analyzing pictures of egg dishes, comparing presentations, arranging jumbled words, sketching their own dish and research easy plating styles. Kitchen rules and a performance task evaluation rubric are also outlined.
Presentation (2).pptx
This document provides a business proposal for a bread and beverage business called Bread and Beverage. It outlines the vision, mission, goals and scope of the business. It introduces the business owners and managers. It describes the products being offered, the production process and tools required. It analyzes the market and competitors through a SWOT analysis. Finally, it discusses the business strategies around improving customer service, personal selling and advertising.
w3-Prepare Sweet Sauces.pptx
This document discusses different types of sauces that can be used for desserts. It describes sauces as flavored liquid blends that enhance food, while fudge is a soft confection made of butter, sugar and chocolate. There are various kinds of sauces including rich, light, hot and cold sauces. Common thickening agents include starch, cornstarch, cream and eggs. Most dessert sauces fall into custard sauces, fruit purees or syrups. Guidelines are provided for making vanilla custard sauce and storing sauces properly in airtight containers in the refrigerator.
CREATE NEW BUSINESS IDEAS IN FOOD AND.pptx
This document outlines a performance task for students to create business plan proposals in groups. It provides instructions that each group must prepare a business plan using a given template. It also schedules presentation dates for groups to present their progress and the final business plan proposals. Guidelines are given for the business plan proposal paper and presentation, including grading criteria for each.
w3-Prepare Sweet Sauces.pptx
This document provides information on preparing dessert sauces. It discusses different types of sauces including custard sauces, fruit purees, and syrups. Guidelines are provided for making vanilla custard sauce, including scalding milk, slowly beating hot milk into egg yolks and sugar, and cooking the mixture while stirring. Sauces should be stored in airtight containers in the refrigerator or cool, dry place and used promptly to avoid bacterial growth.
w2-ingredientsneededinpreparingdessertsandsweetsauces.pptx
Here are definitions for the requested terms:
A. Sauce: A sauce is a liquid, cream, or semi-solid food served on or used in preparing other foods. Sauces are not normally consumed by themselves; they add flavor, moisture, and visual appeal to other foods.
B. Fudge: Fudge is a type of soft, creamy candy that is made by boiling sugar, milk or cream, and butter. It is flavored with vanilla or other flavorings. Fudge is dense and soft and is often cut or broken into pieces to serve.
w1-Types and characteristics of desserts.pptx
The document discusses different types of desserts. It begins by defining dessert as a sweet course served at the end of a meal, usually pastry or ice cream. It then lists reasons for serving desserts such as balancing out a meal and being an opportunity for creativity. The main types of desserts discussed are fruits, cheese, gelatin, custard, puddings, fruit cobblers, and frozen desserts like ice cream, sherbet, and frozen soufflés. For each type, characteristics and examples are provided. The document aims to classify and describe different kinds of common desserts.
ingredientsneededinpreparingdessertsandsweetsauces-160119112409.pptx
Here are the definitions you requested:
A. Sauce: A sauce is a liquid, cream, or semi-solid food served on or used in preparing other foods. Sauces are not normally consumed by themselves; they add flavor, moisture, and visual appeal to other foods.
B. Fudge: Fudge is a type of sugar candy that is made by boiling sugar, milk or cream, and butter. It is heated until it reaches the soft-ball stage at 240–248 °F (116–120 °C) on a candy thermometer. Fudge is then beaten until thickened, creamy, and losing its gloss. Flavorings such as vanilla, chocolate, or nuts are often added. Fudge is
typesofdessert-160116064706.pptx
This document classifies and describes different types of desserts. It discusses fruits, cheese, gelatin desserts, custards, puddings, fruit cobblers, and frozen desserts. For each category it provides characteristics and examples. It also includes a short quiz asking the reader to provide one example for each dessert type and assigns the reader to explain the difference between cold and hot desserts and list common dessert ingredients.
cooker10cookmeat-190118000912.pptx
This document provides information on cooking meat, including definitions, composition, tools, preparation methods, cuts from different animals, and ways to tenderize tough cuts. It discusses:
- Meat refers to animal flesh that is eaten as food, consisting mainly of water, protein, and fat.
- Tools for meat preparation include various knives, cutting boards, thermometers, and twine.
- Methods like trimming, slicing, seasoning, and coating prepare meat for cooking.
- Cooking techniques include dry heat methods like roasting and grilling or moist heat like braising and stewing.
- Marinades tenderize meat using acids, oils, and herbs/spices.
Week 1- Market Forms-tools-cuts.pptx
1. There are several market forms of meat including fresh meat, chilled meat, frozen meat, cured meat, processed meat, and dried meats.
2. Fresh meat is slaughtered meat that has not been chilled or frozen. Chilled meat is meat cooled to just above freezing within 24 hours of slaughter. Frozen meat is meat cuts frozen to -40°C.
3. Cured meat has been treated with curing agents like salt, nitrates, sugar and spices. Processed meat can include prepared meat products. Dried meats are dehydrated meats like beef jerky.
Cooking Cordon Bleu.pptx
This document provides a recipe for making chicken cordon bleu with a white sauce. It describes flattening chicken breasts, layering them with ham and cheese, wrapping them, and breading and frying the rolls. It also includes instructions for making a bechamel white sauce with butter, flour and milk to serve with the chicken cordon bleu.
Week 7-reconstitutingstockssoupandsauces-190205113306.pptx
This document discusses storing and reconstituting stocks, soups, and sauces. It provides instructions for properly cooling and storing stocks in the refrigerator for up to five days or freezing for several months. Sauces and starches should be stored in airtight containers in a cool, dry place. Stocks can be reconstituted by adding water or other liquids like evaporated milk or fruit juices. The document also lists common storage equipment like glass containers and stock pots, and provides guidelines for assessing students' knowledge of proper storage and reheating methods.
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educationalfacilitiesandmapping-120726030120-phpapp01 (1).pptx
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- 2. 1. Define correlational research 3. Define the characteristics of correlational research Learning Objectives 2. Identify the types of correlational research
- 3. Correrational Research • non-experimental research method which studies the relationship between two variables • establishing a relationship between two variables
- 4. Correlational Research • looking for variables that seem to interact with each other • used to investigate the direction and magnitude of relationships between variable
- 5. Correlational Research • designed to study the changes in one characteristics/phenomenon which corresponds to the changes in another
- 6. Direction Positive Correlation indicates that there is a positive relationship between the two variables
- 8. Direction Positive Correlation indicates that there is a positive relationship between the two variables Negative Correlation shows negative relationship between the two variables
- 10. Direction Positive Correlation indicates that there is a positive relationship between the two variables Negative Correlation shows negative relationship between the two variables Zero Correlation there is no relationship between the two variables
- 11. Strong correlation Zero / No Correlation Weak Correlation Magnitude Ranges from -1 to +1(perfect negative and perfect positive
- 12. -1, +1, +0.34, -0.48, 0.0, +0.88, -0.75
- 13. -1, +1, +0.34, -0.48, 0.0, +0.88, -0.75
- 14. -1, +1, +0.34, -0.48, 0.0, +0.88, -0.75
- 15. Characteristics of correlational research Non-Experimental Researchers need not manipulative variables with a scientific methodology to either agree or disagree with hypothesis
- 16. Characteristics of correlational research Non-Experimental Backward-looking Only looks back at historical data and observes events in the past Researchers need not manipulative variables with a scientific methodology to either agree or disagree with hypothesis
- 17. Characteristics of correlational research Non-Experimental Dynamic The patterns between two variables from correlational research are never constant and are always changing Researchers need not manipulative variables with a scientific methodology to either agree or disagree with hypothesis Backward-looking Only looks back at historical data and observes events in the past
- 18. Batangas State University The National Engineering University CONCLUSION Correlational Research