This book is written for anyone who needs or wants to know how statistics work. It assumes no expert knowledge, and teaches through words and diagrams rather than through figures, formulae and equations - providing the perfect approach for the non-mathematical reader. Written as a "tutorial in print", Derek Rowntree includes questions in his argument; readers can answer them as they go, enabling them to measure their performance and judge how far they have mastered the subject. Rowntree says at the end If you feel I've raised more questions in your mind than I've answered, I shan't be surprised or apologetic. The library shelves groan with the weight of books in which you'll find answers to such questions (p185), although having said that to my eyes this is pretty comprehensive for a non-technical reader and the kinds of questions it has raised are not ones I require answers to. The book is clear and plainly explained with worked examples it is written in a seminar style - so the flow is interrupted by mini-questions. I was interested by one example which set out how by doing a single tailed analysis in a drugs trial you can potentially skew the presentation of the result to make a drug appear far more effective than it is ( Lies, damned lies and statistics afterall) Further Matters of Significance. One- Versus Two-Tailed Tests. Z-Tests and T-Tests. Comparing Several Means. Comparing Proportions. urn:oclc:877059383 Republisher_date 20141007164952 Republisher_operator [email protected] Scandate 20141001152035 Scanner scribe3.richflorida.archive.org Scanningcenter richflorida Worldcat (source edition) 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:lcp:statisticswithou00rown_0:epub:c97bc723-554d-4e5e-ab77-2b248c22f77f Foldoutcount 0 Identifier statisticswithou00rown_0 Identifier-ark ark:/13960/t8kd4qz7j Invoice 11 Isbn 9780024040909 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. Further matters of significance.One- versus two-tailed tests.z-tests and t-tests.Comparing several means.Comparing proportions.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. However, the author achieves what he sets out to do -- create a readable statistics book without any mathematical formulas. Comparing samples.From the same or different populations?Significance testing.The significance of significance.Comparing dispersions.Non-parametric methods. The choice of sampling methods is usually dictated by feasibility in terms of time and resources. Field research is quite messy and difficult like actual battle. It may be sometimes difficult to get a sample which is truly random. Most samples therefore tend to get biased. To estimate the magnitude of this bias, the researcher should have some idea about the population from which the sample is drawn. In conclusion, the following quote cited by Bradford Hill[ 4] elegantly sums up the benefit of random sampling: 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.

In statistics, a population is an entire group about which some information is required to be ascertained. A statistical population need not consist only of people. We can have population of heights, weights, BMIs, hemoglobin levels, events, outcomes, so long as the population is well defined with explicit inclusion and exclusion criteria. In selecting a population for study, the research question or purpose of the study will suggest a suitable definition of the population to be studied, in terms of location and restriction to a particular age group, sex or occupation. The population must be fully defined so that those to be included and excluded are clearly spelt out (inclusion and exclusion criteria). For example, if we say that our study populations are all lawyers in Delhi, we should state whether those lawyers are included who have retired, are working part-time, or non-practicing, or those who have left the city but still registered at Delhi. The Shape of a Distribution. Skewed Distributions. Introducing the Normal Distribution. Proportions Under the Normal Curve. Comparing Values. Lccn 82003157 Ocr_converted abbyy-to-hocr 1.1.20 Ocr_module_version 0.0.17 Openlibrary OL15150627M Openlibrary_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. From sample to population.Estimates and inferences.The logic of sampling.A distribution of sample-means.Estimating the population-mean.Estimating other parameters.

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Statistical inquiry.Making sense of experience.What is statistics?Descriptive and inferential statistics.Collecting a sample.