Statistics without Tears: An Introduction for Non-Mathematicians

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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. urn:lcp:statisticswithou00rown_0:epub:c97bc723-554d-4e5e-ab77-2b248c22f77f Foldoutcount 0 Identifier statisticswithou00rown_0 Identifier-ark ark:/13960/t8kd4qz7j Invoice 11 Isbn 9780024040909 Essentially, the book covers all the statistics in A Level Maths (and bits of Further Stats), explaining it in an accessible way and actively encourages you to think (so there really is no escape). The hatred of crunching numbers and learning methods without understanding what I was doing has now been rectified.

The Shape of a Distribution. Skewed Distributions. Introducing the Normal Distribution. Proportions Under the Normal Curve. Comparing Values. 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.

Further Matters of Significance. One- Versus Two-Tailed Tests. Z-Tests and T-Tests. Comparing Several Means. Comparing Proportions. 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.

From sample to population.Estimates and inferences.The logic of sampling.A distribution of sample-means.Estimating the population-mean.Estimating other parameters. 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.

Statistics without tears

Comparing Samples. From the Same or Different Populations? Significance Testing. The Significance of Significance. Comparing Dispersions. Non-Parametric Methods.

Analysing 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. The shape of a distribution.Skewed distributions.Introducing the normal distribution.Proportions under the normal curve.Comparing values. 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. Further matters of significance.One- versus two-tailed tests.z-tests and t-tests.Comparing several means.Comparing proportions. 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).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. 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.