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Medical Statistics from Scratch, An Introduction for Health Professionals

  • Erscheinungsdatum: 07.08.2014
  • Verlag: Wiley-Interscience
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Medical Statistics from Scratch,

Correctly understanding and using medical statistics is a key skill for all medical students and health professionals. In an informal and friendly style, Medical Statistics from Scratch provides a practical foundation for everyone whose first interest is probably not medical statistics. Keeping the level of mathematics to a minimum, it clearly illustrates statistical concepts and practice with numerous real world examples and cases drawn from current medical literature. This fully revised and updated third edition includes new material on: missing data, random allocation and concealment of data intra-class correlation coefficient effect modification and interaction diagnostic testing and the ROC curve standardisation
Medical Statistics from Scratch is an ideal learning partner for all medical students and health professionals needing an accessible introduction, or a friendly refresher, to the fundamentals of medical statistics.

Produktinformationen

    Format: ePUB
    Kopierschutz: AdobeDRM
    Seitenzahl: 408
    Erscheinungsdatum: 07.08.2014
    Sprache: Englisch
    ISBN: 9781118519394
    Verlag: Wiley-Interscience
    Größe: 13677 kBytes
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Medical Statistics from Scratch,

Chapter 1
First things first - the nature of data

Learning objectives

When you have finished this chapter, you should be able to:

Explain the difference between nominal, ordinal and metric data.
Identify the type of any given variable.
Explain the non-numeric nature of ordinal data. Variables and data

Let's start with some numbers. Have a look at Figure 1.1 .
2240 4110 3590 2880 2850 2660 4040 3580 1960 3550 3050 3130 2660 3150 3220 3990 4020 3040 3460 4230 4110 2780 2840 3660 3580 2780 3560 2350 2720 2460 3200 2650 3000 3170 3500 2400 3300 3740 2760 3840 3740 2380 3300 3480 3740 3770 2520 3570 3400 3780 3040 3170 3300 3560 3180 2920 4000 2700 3680 2500 2920 2980 3780 2650 2880 4550 3570 1620 3000 3700 4080 3280 3800 2800 2560 2740 3180 3200 3120 4880 2800 3640 4020 3080 2590 3360 3630 3740 2960 3300 3090 3600 3720 2840 3320 2940 3640 2720 3220 4140
Figure 1.1 Some numbers. Actually, the birthweight (g) of a sample of 100 babies. Data from the Born in Bradford Cohort Study. Born in Bradford, Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust

These numbers are actually the birthweights of a sample of 100 babies (measured in grams). We call these numbers sample data . These data arise from the variable birthweight . To state the blindingly obvious, a variable is something whose value can vary. Other variables could be blood type, age, parity and so on; the values of these variables can change from one individual to the other. When we measure a variable, we get data - in this case, the variable birthweight produces birthweight data .

Figure 1.2 contains more sample data, in this case, for the gender of the same 100 babies.
M M F F M M F F M M M M M F M M F F M M F F M M F F M F F F M M F F M M M M F F M M F F M F F F F F F M F M M M F F M F F F M M M

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