Statistics without Tears: An Introduction for Non-Mathematicians

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If cases of a disease are being ascertained through their attendance at a hospital outpatient department (OPD), rather than by field surveys in the community, it will be necessary to define the population according to the so-called catchment area of the hospital OPD. For administrative purposes, a dispensary, health center or hospital is usually considered to serve a population within a defined geographic area. But these catchment areas may only represent in a crude manner with the actual use of medical facilities by the local people. For example, in OPD study of psychiatric illnesses in a particular hospital with a defined catchment area, many people with psychiatric illnesses may not visit the particular OPD and may seek treatment from traditional healers or religious leaders. Statistical Inquiry. Making Sense of Experience. What is Statistics? Descriptive and Inferential Statistics. Collecting a Sample. From Sample to Population. Estimates and Inferences. The Logic of Sampling. A Distribution of Sample-Means. Estimating the Population-Mean. Estimating Other Parameters.

However, the author achieves what he sets out to do -- create a readable statistics book without any mathematical formulas. Ascertainment of a particular disease within a particular area may be incomplete either because some patient may seek treatment elsewhere or some patients do not seek treatment at all. Focus group discussions (qualitative study) with local people, especially those residing away from the health center, may give an indication whether serious underreporting is occurring. urn:oclc:877059383 Republisher_date 20141007164952 Republisher_operator [email protected] Scandate 20141001152035 Scanner scribe3.richflorida.archive.org Scanningcenter richflorida Worldcat (source edition) This classic book uses words and diagrams, rather than formulas and equations, to help readers understand what statistics is, and how to think statistically. It focuses on the ideas behind statistics only; readers are not required to perform any calculations.Derek Rowntree has spent most of his working life in higher education.In 1969 he was appointed as one of the founding members of the OpenUniversity and played his part in developing new kinds of teaching tomeet the challenges posed by the innovatory concept of 'open learningand distance education'. 30 years later, having stayed long enough tohelp a generation of academics learn how to teach and assess studentsthey might never meet and, finally, to develop the first online courses, he retired as Professor of Educational Development. Sometimes, a strictly random sample may be difficult to obtain and it may be more feasible to draw the required number of subjects in a series of stages. For example, suppose we wish to estimate the number of CATSCAN examinations made of all patients entering a hospital in a given month in the state of Maharashtra. It would be quite tedious to devise a scheme which would allow the total population of patients to be directly sampled. However, it would be easier to list the districts of the state of Maharashtra and randomly draw a sample of these districts. Within this sample of districts, all the hospitals would then be listed by name, and a random sample of these can be drawn. Within each of these hospitals, a sample of the patients entering in the given month could be chosen randomly for observation and recording. Thus, by stages, we draw the required sample. If indicated, we can introduce some element of stratification at some stage (urban/rural, gender, age). I have a rather irregular history with statistics. After disliking maths GCSE but getting a very good mark, I avoided A-level maths like the plague. Upon arriving at university as a fresh-faced undergrad, I was disconcerted to discover that the first year of my social science degree included a compulsory statistics module. I passed that, then chose modules with no maths for the remaining two years. My dissertation was entirely qualitative. When I returned to studying as postgrad years later, I’d grudgingly come to accept that statistics are useful. My masters course included two statistics modules, which I appreciated the purpose of without enjoying. Then somehow, during the peculiar derangement of my PhD, I ended up teaching myself to use a fairly complex statistical methodology: multinomial logistic regression. The majority of my PhD research was quantitative. Now I find myself actually teaching statistics to undergrads. My 18 year old self would be amazed and horrified. It’s quite possible that I’m still outgrowing an ingrained dislike of maths that has much more to do with uninspired school teaching than the subject itself. In any case, I have a decent grasp of what stats are and why they’re useful, by social science standards.

Lccn 82003157 Ocr_converted abbyy-to-hocr 1.1.20 Ocr_module_version 0.0.17 Openlibrary OL15150627M Openlibrary_edition Rowntree's text does provide a good overview in very general and broad terms on statistical topics in layman's terms. It is consciously targeted towards non-mathematicians, and provides a great resource for understanding basic statistical topics. This book is for people who must casually digest and interpret statistics, and not for those of us who need to produce them. In retrospect, these appear to be mistakes. As an aspiring trader, my world is deeply tied to statistics and programming languages (although I still think “R” is ugly). Reading “Statistics Without Tears” slowly chipped away at my prejudice toward the subject. Derek Rowntree writes and educates in a way that I believe most statistics teachers can only dream of doing. Instead of dosing off during the book’s “lectures,” like I did in university ones (on the ones I didn’t skip), this book had me hooked from beginning to end. A brief and informative read that helped me review the statistics material I had studied, but I need to qualify that by saying this will not be enough. It's a good starting point, and if you've studied statistics before then it will remind you of the terms and help you conceptually. However, you will need to supplement this with other reading and practice centred around why you want to understand statistics and the tools you want to use. Research workers in the early 19th century endeavored to survey entire populations. This feat was tedious, and the research work suffered accordingly. Current researchers work only with a small portion of the whole population (a sample) from which they draw inferences about the population from which the sample was drawn.Analyzing Relationships. Paired Values. Three Kinds of Correlation. The Strength of a Correlation. The Significance of a Correlation Coefficient. Interpreting a Correlation Coefficient. Prediction and Regression. Postscript. Review. Caution. the possibility of bias in samples, the distinction between significance and importance, the fact that correlation does not imply causation, and that people sometimes simply get things wrong.' From sample to population.Estimates and inferences.The logic of sampling.A distribution of sample-means.Estimating the population-mean.Estimating other parameters. So why read this book? Because the undergrads I taught this term, and probably the postgrads I’ll teach next term, appear petrified and confused by quantitative methods. It’s so difficult to tell whether students are really grasping the concepts you explain in lectures, particularly when there’s no exam to test comprehension. These are social science students and their prior exposure to stats seems to have been minimal. When I spotted this book in library, I wondered if it could help me to explain the basics more clearly. And I think it just might. I found it very easy to follow and a helpful reminder. Rowntree’s explanation of the difference between parametric and non-parametric tests is especially lucid and useful. That said, I doubt I'll have time to include such careful and painstaking explanations in my lectures. I’ll definitely recommend the book to students, though. It’s not at all fashionable to suggest students read entire books, but honestly I think this one is much better than an explanatory video, the more trendy teaching medium.