Quantitative Research Methods for Social Scientists
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This assignment covers four levels of measurement, measures of central tendency and dispersion, descriptive and inferential statistics, and interpretation of results. It emphasizes the relative idea of quantitative social research and provides interpretations of test results in a concise manner.
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LC572: Quantitative Research Methods for Social Scientists
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Table of Contents Introduction......................................................................................................................................3 Main Body.......................................................................................................................................3 1. Four levels of measurement with examples.......................................................................3 2. Measures of Central Tendency and Measures of Dispersion.............................................3 3. Difference between Descriptive statistics and Inferential statistics...................................4 4. Define.................................................................................................................................4 5. Interpretation......................................................................................................................4 Conclusion.......................................................................................................................................5 References........................................................................................................................................6 APPENDIX......................................................................................................................................7 A.1 Frequency table................................................................................................................7 A.2 Cross tabulation...............................................................................................................7 A.3 Chi-square test.................................................................................................................8 A.4 Phi/Cramer’s V................................................................................................................8
Introduction Quantitative approaches are concerned with data collecting using statistical, mathematical and objective measurements. The offered assignment will focus on emphasizing major problems that have been discussed in class in recent weeks. There will also be a discussion of the relative idea of quantitative social research. Finally, interpretations are given for the test results that are delivered in a concise manner(Abu-Bader, 2021). Main Body 1. Four levels of measurement with examples The word measuring scale refers to a set of numerical or statistical data that provides information. The level of measurement is the process of assigning variables to one another so thatinformationmaybeconveyedwithinthevalues(Allan,2020).Thefourlevelsof measurement are as follows, with examples: Nominal: Only the most basic information regarding the input data is given. Furthermore, each variable is given a number, which aids in the classification of observations or variables. In the Gender variable, for example, Male is represented by a significant numeric value, whereas Female is represented by another. Ordinal:Whencomparedtonominalscales,ordinalscalesprovidealotmore information.Thereisanorderedlinkbetweenthevariable'sobservationsatthis measurement level. For example, a class of 150 students is placed first in merit and second in pass. Interval: The offered scale provides more descriptive information than an ordinal scale of assessment. This degree of assurance provides confidence that discrepancies in values are equal. Temperature measurement, for example, is an example of interval scale. Ratio: Of all the measuring scales, ratio scales are thought to be the most informative. Using such a scale, you may create a ranking and verify that the scale values differ equally. Money measurement is an example of a ratio scale. 2. Measures of Central Tendency and Measures of Dispersion The measure of central tendency is based on a single value in the data set and is used to locate the data's centre. The words presented are also known as summary statistics of input data that take into account available variables (dependent and independent) in the data-set. This
usually includes the mean, median, and mode. Measures of dispersion, or simply dispersion, relate to a spread or dispersed state. It assesses the trend for which possible variations in measures of central tendency will differ from the actual mean value in terms of statics. The word aids researchers in comprehending the dispersion of data collected from a range of sources (Boeren, 2019). 3. Difference between Descriptive statistics and Inferential statistics BasisDescriptive statisticsInferential Statistics MeaningThe term descriptive statistics referstonormallyusedto determine as well as conclude dataforclassifyingitina rational manner(Liamputtong, 2019). Theinferentialstatistics formulateabetter understanding for formulating predictionsundergroupof variables. Tools usedMedian, mean and mode.Variance analysis, hypothesis testing, etc. 4. Define Hypothesis and null hypothesis: A hypothesis is an explanation for phenomena that is suggested. It is a broad assumption based on the problem specified in the study subject and goal. A component of the hypothesis represented by H0 is the null hypothesis. For a given sample size, this illustrates a negative association between variable(s). Variables that are independent and dependent: Any number, feature, or amount that can be measured or counted is referred to as a variable. Variables that are changed throughout a statistical experiment are referred to as independent variables. Dependent variables, on the other hand, are variables that are tested or assessed during a statistical experiment (Gephart, 2018). Extraneous variables: The respective variables are not being taken into consideration or tested when performing statistical tests or experiments. 5. Interpretation a.Frequency table
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From the evaluation of frequency table, it can be interpreted that 52% of the total active participants provides with stats that noisy neighbour or loud parties tends to be not at all common. In addition to this, very less proportion of individuals states about noisy neighbour are founded very common which can be backed through 4.7%. b. Cross-tabulation Taking the instance of the cross-tabulation table mentioned above, the majority of respondents agreed to the fact that it is not at all common the maximum agreeing is adult
population as per age group. Therefore, it can be said that 808 people think that noisy neighbours are not at all common. c. Chi-square result Through the analysis of the chi-square test table that displays the significant differences between the two categorical variables. The significant value from the test was obtained at 0.000. The value obtained is less than .05 which signifies the selection of an alternative hypothesis. Therefore, it is interpreted that there exists a difference between age and noisy neighbour. d. Phi/Cramer’s The analysis of Phi/ Cramer provides a glimpse about association between coefficient that outlines strength of relationship between two different variables. For the provided context, age and noisy neighbourhood it can be stated that Phi is 0.171 and Cramer V is 0.121. This states about strength and weakness of relationship between noisy neighbour and age in the data set.
Conclusion From the analysis of above statistical report document, it can be concluded that several research techniques and relative tools are made available when being indulged towards exploring social issues being raised in an economy. Furthermore, it can be stated that relevant information could be extracted for the researcher to attain the requirements of the brief.
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References Books and Journals Abu-Bader, S.H., 2021.Using statistical methods in social science research: With a complete SPSS guide. Oxford University Press, USA. Allan,G.,2020.Qualitativeresearch.InHandbookforresearchstudentsinthesocial sciences(pp. 177-189). Routledge. Boeren, E., 2019. Quantitative research in research on the education and learning of adults. InMapping out the Research Field of Adult Education and Learning(pp. 139-155). Springer, Cham. Gephart, R.P., 2018. Qualitative research as interpretive social science.The SAGE handbook of qualitative business and management research methods, pp.33-53. Liamputtong, P. ed., 2019.Handbook of research methods in health social sciences. Singapore:: Springer.