IMPORTANCE OF QUANTITATIVE RESEARCH IN SOCIAL SCIENCES FOR PHD RESEARCH SCHOLAR An Academic presentation by Dr. Nancy Agnes, Head, Technical Operations, Phdassistance Group www.phdassistance.com Email: [email protected]
Quantitative analysis in social sciences for PhD Research Scholar – PhD Assistance
Jul 23, 2022
To determine that association,
you’d need to Collect Data on workers’ years of schooling and their
pay. You will find the best dissertation for future researchers enrolled in business and management.
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To determine that association, you’d need to Collect Data on workers’ years of schooling and their pay. You will find the best dissertation for future researchers enrolled in business and management.
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PA-Importance of Quantitative research in social sciences for Phd Research Scholar IMPORTANCE OF QUANTITATIVE RESEARCH IN SOCIAL SCIENCES FOR PHD RESEARCH SCHOLAR
An Academic presentation by
Email: [email protected]
TODAY'S OUTLINE
Concluding remarks
IN-BRIEF
INTRODUCTION
Q uantitative analysis is used in social sciences to determine the relationship between an independent variable (a type of quantity that captures observed values of things that can be manipulated) and a dependent variable (the observed results of manipulating the independent variable) in a given population.
For example, you might be interested in identifying the association between years of schooling (the independent variable) and earnings paid to garment workers (the dependent variable).
To determine that association, you'd need to collect data on workers' years of schooling and their pay.
You might also be interested in finding the link between a balanced diet (the independent variable) and schoolchildren's cognitive abilities.
In this situation, you'd need to gather data on food intake, such as the number of meals consumed each day, as well as administer cognitive achievement exams in reading, math, and written language.
PhD Dissertation on Social Sciences Research Methodology must contain clear academic evidence and justification for all the research choices.
PEARSON’S PRODUCT-MOMENT CORRELATION COEFFICIENT
The Pearson's product-moment correlation coefficient, often known as Pearson's rho, or simply Pearson's r, is a standard method for determining the direction and degree of a correlation between two variables.
It is the product of the linear relationship between a dependent and independent variable. 3 The Pearson's correlation coefficient is defined as the product of two variables' standard deviations divided by their covariance.
The standard deviation is a measure of how much variation exists between the observed values of the two variables and the mean, whereas covariance is a measure of how much the two variables vary together.
You'll need to employ hypothesis testing and confidence levels procedures to determine the relevance of such correlations.
When utilising Pearson's r, the independent and dependent variables must be measured continuously in interval or ratio scales.
Even though they have no meaningful zero value, interval variables allow us to detect equally spaced values in intervals.
Temperature measured on the Fahrenheit scale, where a zero degree does not mean there is no temperature, but rather a very cold temperature of around -17.78 degrees Celsius, is a popular example of an interval variable.
In the social sciences, however, we rarely use interval variables and instead rely on ratio scales. P hD Q ualitative Research Methodolog y S ervices & Hel p you to select a perfect research methodology work.
The qualities of ratio scale variables are similar to those of interval variables, but they differ in that they have a definable zero point. Ratio scale variables include income, expenditures, revenues, costs, profits, and other continuous variables.
Ratio scales offer the advantage of being able to be measured, compared, and ranked in terms of magnitude differences, such as when two individuals, A and B, report monthly incomes of US $2000 and US $1000, respectively, in a dataset.
The correlation coefficient's direction can range from -1 to +1, passing through zero. Increases in the independent variable, x, are related with an increase in the dependent variable, y, whereas increases in the independent variable are connected with a reduction in the dependent variable, y.
If your data shows that workers with more years of education earn more money, you can conclude that there is a positive relationship between education and pay.
The plotted points migrate from the lower left-hand corner to the upper right-hand corner of the scattergram in this hypothetical scenario, as shown in Figure 1.
Similarly, if your data shows that higher alcohol use among workers is linked to premature death, you can conclude that alcohol intake and life expectancy are negatively associated.
Hire PhD Assistance expertsto develop your research work for your B usiness and Mana g ement dissertation Services .
You should be aware that the level of correlation between two variables, in either a positive or negative direction, may not be as obvious as you might think in many circumstances.
Figure 2 depicts the relationship between the number of children in a household and the household head's age.
The Pearson's correlation coefficient (r= -0.17) demonstrates a weak and negative relationship between the two variables, indicating that the relationship is not a straight line.
Phd assistance has vast experience in developing dissertation topics for students pursuing the UK dissertation in both engineering and management. Order Now
The existence of exceptionally low and high values in the scattergram, which are referred to as outliers by academics.
The inclusion of a few outliers in a dataset might lead to misleading results, especially when the sample size of your data is small.
Phdassistance experts has experience in handling Q ualitative & Q uantitative Research in Business and management research with assured 2:1 distinction. Talk to Experts Now
CONCLUDING REMARKS
that are
I've briefly addressed quantitative research approaches commonly utilized in development research in this work.
Some of these procedures are complicated and necessitate a high level of statistical, econometric, and study design knowledge.
If you want to conduct a study but don't have a background in Economics, Statistics, or Behavioural Sciences, you should seek advice from a quantitative research methods expert, keeping in mind the difficulties I've raised throughout this work.
Keep in mind that your methodological approach will be guided by your study aims. Data gathering will decide whether or not randomization is viable in terms of context and/or ethical, budgetary, and time constraints.
It is significant to select a social science research methodology, which exactly suits your research work, and you must clearly state the reason why you have chosen a particular research method.
If you found difficult in identifying research methodology, you can consult with Best PhD Research Methodology Help provider online to identify Best D issertation Research Methodolo g y .
Contact us
UNITED KINGDOM
+44 7537144372
An Academic presentation by
Email: [email protected]
TODAY'S OUTLINE
Concluding remarks
IN-BRIEF
INTRODUCTION
Q uantitative analysis is used in social sciences to determine the relationship between an independent variable (a type of quantity that captures observed values of things that can be manipulated) and a dependent variable (the observed results of manipulating the independent variable) in a given population.
For example, you might be interested in identifying the association between years of schooling (the independent variable) and earnings paid to garment workers (the dependent variable).
To determine that association, you'd need to collect data on workers' years of schooling and their pay.
You might also be interested in finding the link between a balanced diet (the independent variable) and schoolchildren's cognitive abilities.
In this situation, you'd need to gather data on food intake, such as the number of meals consumed each day, as well as administer cognitive achievement exams in reading, math, and written language.
PhD Dissertation on Social Sciences Research Methodology must contain clear academic evidence and justification for all the research choices.
PEARSON’S PRODUCT-MOMENT CORRELATION COEFFICIENT
The Pearson's product-moment correlation coefficient, often known as Pearson's rho, or simply Pearson's r, is a standard method for determining the direction and degree of a correlation between two variables.
It is the product of the linear relationship between a dependent and independent variable. 3 The Pearson's correlation coefficient is defined as the product of two variables' standard deviations divided by their covariance.
The standard deviation is a measure of how much variation exists between the observed values of the two variables and the mean, whereas covariance is a measure of how much the two variables vary together.
You'll need to employ hypothesis testing and confidence levels procedures to determine the relevance of such correlations.
When utilising Pearson's r, the independent and dependent variables must be measured continuously in interval or ratio scales.
Even though they have no meaningful zero value, interval variables allow us to detect equally spaced values in intervals.
Temperature measured on the Fahrenheit scale, where a zero degree does not mean there is no temperature, but rather a very cold temperature of around -17.78 degrees Celsius, is a popular example of an interval variable.
In the social sciences, however, we rarely use interval variables and instead rely on ratio scales. P hD Q ualitative Research Methodolog y S ervices & Hel p you to select a perfect research methodology work.
The qualities of ratio scale variables are similar to those of interval variables, but they differ in that they have a definable zero point. Ratio scale variables include income, expenditures, revenues, costs, profits, and other continuous variables.
Ratio scales offer the advantage of being able to be measured, compared, and ranked in terms of magnitude differences, such as when two individuals, A and B, report monthly incomes of US $2000 and US $1000, respectively, in a dataset.
The correlation coefficient's direction can range from -1 to +1, passing through zero. Increases in the independent variable, x, are related with an increase in the dependent variable, y, whereas increases in the independent variable are connected with a reduction in the dependent variable, y.
If your data shows that workers with more years of education earn more money, you can conclude that there is a positive relationship between education and pay.
The plotted points migrate from the lower left-hand corner to the upper right-hand corner of the scattergram in this hypothetical scenario, as shown in Figure 1.
Similarly, if your data shows that higher alcohol use among workers is linked to premature death, you can conclude that alcohol intake and life expectancy are negatively associated.
Hire PhD Assistance expertsto develop your research work for your B usiness and Mana g ement dissertation Services .
You should be aware that the level of correlation between two variables, in either a positive or negative direction, may not be as obvious as you might think in many circumstances.
Figure 2 depicts the relationship between the number of children in a household and the household head's age.
The Pearson's correlation coefficient (r= -0.17) demonstrates a weak and negative relationship between the two variables, indicating that the relationship is not a straight line.
Phd assistance has vast experience in developing dissertation topics for students pursuing the UK dissertation in both engineering and management. Order Now
The existence of exceptionally low and high values in the scattergram, which are referred to as outliers by academics.
The inclusion of a few outliers in a dataset might lead to misleading results, especially when the sample size of your data is small.
Phdassistance experts has experience in handling Q ualitative & Q uantitative Research in Business and management research with assured 2:1 distinction. Talk to Experts Now
CONCLUDING REMARKS
that are
I've briefly addressed quantitative research approaches commonly utilized in development research in this work.
Some of these procedures are complicated and necessitate a high level of statistical, econometric, and study design knowledge.
If you want to conduct a study but don't have a background in Economics, Statistics, or Behavioural Sciences, you should seek advice from a quantitative research methods expert, keeping in mind the difficulties I've raised throughout this work.
Keep in mind that your methodological approach will be guided by your study aims. Data gathering will decide whether or not randomization is viable in terms of context and/or ethical, budgetary, and time constraints.
It is significant to select a social science research methodology, which exactly suits your research work, and you must clearly state the reason why you have chosen a particular research method.
If you found difficult in identifying research methodology, you can consult with Best PhD Research Methodology Help provider online to identify Best D issertation Research Methodolo g y .
Contact us
UNITED KINGDOM
+44 7537144372
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