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. Rowntree wants you to understand the concepts instead of the formulas, so it makes the read easier. If you ever had to do null-hypothesis testing in school decades ago, the content should come easy to you. 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.

Statistics without tears, a primer for non-mathematicians, Statistics without tears, a primer for non-mathematicians,

Catchment areas depend on the demography of the area and the accessibility of the health center or hospital. Accessibility has three dimensions – physical, economic and social.[ 2] Physical accessibility is the time required to travel to the health center or medical facility. It depends on the topography of the area (e.g. hill and tribal areas with poor roads have problems of physical accessibility). Economic accessibility is the paying capacity of the people for services. Poverty may limit health seeking behavior if the person cannot afford the bus fare to the health center even if the health services may be free of charge. It may also involve absence from work which, for daily wage earners, is a major economic disincentive. Social factors such as caste, culture, language, etc. may adversely affect accessibility to health facility if the treating physician is not conversant with the local language and customs. In such situations, the patient may feel more comfortable with traditional healers. I consider this a must-read if you've ever taken postsecondary or college-level math (which would have covered the basic statistics mentioned in the book). A population is a complete set of people with a specialized set of characteristics, and a sample is a subset of the population. The usual criteria we use in defining population are geographic, for example, “the population of Uttar Pradesh”. In medical research, the criteria for population may be clinical, demographic and time related. 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.' This book was probably the most lucidly written book that I have come across that explains Statistics to a person entirely alien to the field.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). The focus of this book is on the 'why' of performing statistical calculations so that the 'how' of those same calculations makes sense. A sample is any part of the fully defined population. A syringe full of blood drawn from the vein of a patient is a sample of all the blood in the patient's circulation at the moment. Similarly, 100 patients of schizophrenia in a clinical study is a sample of the population of schizophrenics, provided the sample is properly chosen and the inclusion and exclusion criteria are well defined. To save this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you used this feature, you will be asked to authorise Cambridge Core to connect with your Google Drive account.

Statistics without tears: Populations and samples - PMC Statistics without tears: Populations and samples - PMC

I'm not sure, whether this book is great, or it is just the cumulative result of many months of studying, but after reading it, I finally got the grasp on many basic things in statistics. There is the third option - I'm just too silly for statistics. 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. Regardless, this should be the first book anyone should read if they want an introduction to the world of statistics. It contains no calculations and it is very engaging. Depending on the type of exposure being studied, there may or may not be a range of choice of cohort populations exposed to it who may form a larger population from which one has to select a study sample. For instance, if one is exploring association between occupational hazard such as job stress in health care workers in intensive care units (ICUs) and subsequent development of drug addiction, one has to, by the very nature of the research question, select health care workers working in ICUs. On the other hand, cause effect study for association between head injury and epilepsy offers a much wider range of possible cohorts. have a stats test tomorrow, revising the concepts actually made sense.. very grateful but we will see how it goes

Article contents

As someone that has previously studied many of the covered topics, this was a comfortable way of reviewing and organising the subject matter. I found that some of the explanations provided were far more accessible than the way in which I was first taught statistics. BOPA presents a 6 part live e-learning Statistics Webinar series to help you understand and work on Statistics without Tears! We’ve got a great speaker lined up with content that will be vital in your oncology pharmacy career. The sessions will be interactive and questions will be welcomed to help you with your statistical fears. We will run these on a monthly basis and the first one is free to all and then subsequently free to BOPA members. 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:

Statistics without Tears: An Introduction for Non-Mathematicians Statistics without Tears: An Introduction for Non-Mathematicians

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.This is an excellent introduction to statistical thinking. The language used is conversational and easy to understand as you are guided through examples and ways of thinking about statistics. Stat อย่างผม อ่านแล้วอยากจะดึงคนเขียนมาจุ๊บด้วยความขอบคุณสักที เป็นสถิติแบบที่ใช้เรียนตอนป.ตรีเลย แต่อธิบายด้วยภาษาคน และการใส่ตัวอย่างมาแบบไม่มีกั๊ก ทำให้เนื้อหาหลายๆ อย่างที่ตอนเรียนเรารู้สึกว่า "ทำไมมันนามธรรมจังวะ? ตกลงไอ้ที่เรากำลังคำนวณกันอยู่นี่มันคืออะไร?" เคลียร์ขึ้นมาเยอะเลย