Week 1: Introduction: Descriptive and Inferential Statistics. Three aims to this lecture. The first is to talk briefly through the term's course and discuss how. Download PDF Statistical Methods for the Social Sciences (5th Edition) | PDF books Ebook Free Download Here. Find all the study resources for Statistical Methods for the Social Sciences by Alan Agresti; Barbara Finlay. Answers agresti & portal7.info 18Pages:
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The purpose of this book is to acquaint the reader with the increasing number of applications of statistics in engineering and the social sciences. The book presents an introduction to statistical methods for students majoring in social science disciplines. No previous knowledge of statistics. Lecture 1 is based on chapters 1 and 2 of. Statistical Methods for the Social Sciences (4th. Edition) by A. Agresti and B. Finlay (AF). • Interesting and entertaining.
Statistics is employed in economics , psychology , political science , sociology and anthropology. There is a debate regarding the uses and value of statistical methods in social science, especially in political science, with some statisticians questioning practices such as data dredging that can lead to unreliable policy conclusions of political partisans who overestimate the interpretive power that non-robust statistical methods such as simple and multiple linear regression allow. Indeed, an important axiom that social scientists cite, but often forget, is that " correlation does not imply causation. But where men suffer adverse statistical indicators such as greater imprisonment rates or a higher suicide rate, that is not usually accepted as evidence of gender bias acting against them. The use of statistics has become so widespread in the social sciences that many universities such as Harvard , have developed institutes focusing on "quantitative social science. However, some experts in causality feel that these claims of causal statistics are overstated,   Statistical methods in social sciences[ edit ] Methods, techniques and concepts used in quantitative social sciences include:.
Are you sure you want to Yes No. Be the first to like this. No Downloads. Views Total views. Actions Shares. Embeds 0 No embeds. No notes for slide. Book Details Author: Alan Agresti Pages: Hardcover Brand: Statistical methods applied to social sciences, made accessible to all through an emphasis on concepts Statistical Methods for the Social Sciences introduces statistical methods to students majoring in social science disciplines.
With an emphasis on concepts and applications, this book assumes you have no previous knowledge of statistics and only a minimal mathematical background.
It contains sufficient material for a two-semester course. It continues to downplay mathematics—often a stumbling block for students—while avoiding reliance on an overly simplistic recipe-based approach to statistics.
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Explain how the actual analysis differs from the planned analysis. Explain your handling of missing data and why any missing data does not undermine the validity of your analysis. Explain the techniques you used to "clean" your data set.
Choose a minimally sufficient statistical procedure; provide a rationale for its use and a reference for it. Specify any computer programs used.
Describe the assumptions for each procedure and the steps you took to ensure that they were not violated. When using inferential statistics, provide the descriptive statistics, confidence intervals, and sample sizes for each variable as well as the value of the test statistic, its direction, the degrees of freedom, and the significance level [report the actual p value].
Avoid inferring causality, particularly in nonrandomized designs or without further experimentation. Use tables to provide exact values; use figures to convey global effects. Keep figures small in size; include graphic representations of confidence intervals whenever possible. Always tell the reader what to look for in tables and figures.
Armonk, NY: M. Sharpe, ; Quantitative Research Methods. Writing CSU. Colorado State University; Singh, Kultar. Quantitative Social Research Methods.
Los Angeles, CA: Sage, Basic Research Design for Quantitative Studies Before designing a quantitative research study, you must decide whether it will be descriptive or experimental because this will dictate how you gather, analyze, and interpret the results. A descriptive study is governed by the following rules: subjects are generally measured once; the intention is to only establish associations between variables; and, the study may include a sample population of hundreds or thousands of subjects to ensure that a valid estimate of a generalized relationship between variables has been obtained.
An experimental design includes subjects measured before and after a particular treatment, the sample population may be very small and purposefully chosen, and it is intended to establish causality between variables. Introduction The introduction to a quantitative study is usually written in the present tense and from the third person point of view. It covers the following information: Identifies the research problem -- as with any academic study, you must state clearly and concisely the research problem being investigated.
Reviews the literature -- review scholarship on the topic, synthesizing key themes and, if necessary, noting studies that have used similar methods of inquiry and analysis. Note where key gaps exist and how your study helps to fill these gaps or clarifies existing knowledge. Describes the theoretical framework -- provide an outline of the theory or hypothesis underpinning your study. If necessary, define unfamiliar or complex terms, concepts, or ideas and provide the appropriate background information to place the research problem in proper context [e.
Methodology The methods section of a quantitative study should describe how each objective of your study will be achieved. Be sure to provide enough detail to enable the reader can make an informed assessment of the methods being used to obtain results associated with the research problem. The methods section should be presented in the past tense. Study population and sampling -- where did the data come from; how robust is it; note where gaps exist or what was excluded.
Note the procedures used for their selection; Data collection — describe the tools and methods used to collect information and identify the variables being measured; describe the methods used to obtain the data; and, note if the data was pre-existing [i. If you gathered it yourself, describe what type of instrument you used and why.
Note that no data set is perfect--describe any limitations in methods of gathering data. Data analysis -- describe the procedures for processing and analyzing the data.
If appropriate, describe the specific instruments of analysis used to study each research objective, including mathematical techniques and the type of computer software used to manipulate the data. Results The finding of your study should be written objectively and in a succinct and precise format. In quantitative studies, it is common to use graphs, tables, charts, and other non-textual elements to help the reader understand the data.
Make sure that non-textual elements do not stand in isolation from the text but are being used to supplement the overall description of the results and to help clarify key points being made. Further information about how to effectively present data using charts and graphs can be found here. Statistical analysis -- how did you analyze the data? What were the key findings from the data?
The findings should be present in a logical, sequential order.
Describe but do not interpret these trends or negative results; save that for the discussion section. The results should be presented in the past tense. Discussion Discussions should be analytic, logical, and comprehensive. The discussion should meld together your findings in relation to those identified in the literature review, and placed within the context of the theoretical framework underpinning the study.
The discussion should be presented in the present tense.