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Statistics (Chapter 3) Statistics Forensic science is based in experiment, measurement, and analysis. Whenever measurements are made, however, there is an inherent variability and uncertainty in the measurement… CHE 113 2 Uncertainty in Measurement • Precision vs. Accuracy – Precision - how closely individual measurements agree – Accuracy- how closely the measurements agree with the true value • Significant Figures – All measurements are inaccurate intrinsically – measured quantities are reported such that the last figure is uncertain CHE 113 3 Measurement Measurement and Significant Digits • You can only be as precise as the instrument used to make the measurement • Significant figures give the reader an idea of how well you could actually measure/report your data Sig Figs • 12.34500 kg of drugs – 7 significant figures What if scale only reads measures to 12.345 kg? http://chemsite.lsrhs.net/measurement/sig_fig .html http://chemsite.lsrhs.net/measurement/sig_fig .html Statistics vs. Probability •Statistics is focused upon the collection, handling, validation, and interpretation of data. •learn about the properties of a larger population from studying a small subset or sample of the population •Probability deals with representing the likelihood that a particular event or set of events will occur given a set of reference data. •learn about a particular sample given knowledge about the larger population. CHE 113 9 Statistics and Probability CHE 113 10 Statistical Terms to Know • Average or Arithmetic Mean: – The average or mean is the sum of the values of each of the individual data points divided by the total number of data points in the set. • Mode: – The mode is that value that occurs most frequently in a data set. Statistical Terms to Know • Range: – The difference between the lowest and highest value in a set of data is the range. • Standard Deviation (σ or SD): – How spread out numbers are in a set of data Statistical Terms to Know • Variance : – The square of the standard deviation relates the total variance found in the data set… You and your friends have just measured the heights of your dogs (in millimeters): Height in mm The heights (at the shoulders) are: 600mm, 470mm, 170mm, 430mm and 300mm. Find out the Mean, the Variance, and the Standard Deviation. Your first step is to find the Mean: Answer: Mean = 600 + 470 + 170 + 430 + 300 5 = 1970 5 http://www.mathsisfun.com/data/standard-deviation.html = 394mm so the mean (average) height is 394 mm. Let's plot this on the chart: Height in mm Now, we calculate each dogs difference from the Mean: http://www.mathsisfun.com/data/standard-deviation.html To calculate the Variance, take each difference, square it, and then average the result: So, the Variance is 21,704. And the Standard Deviation is just the square root of Variance, so: Standard Deviation: σ = √21,704 = 147.32... = 147 (to the nearest mm) And the good thing about the Standard Deviation is that it is useful. Now we can show which heights are within one Standard Deviation (147mm) of the Mean: So, using the Standard Deviation we have a "standard" way of knowing what is normal, and what is extra large or extra small. Rottweilers are tall dogs. And Dachshunds are a bit short ... but don't tell them! Statistics in Forensics Relate alcohol in small blood sample to that believed in whole body Probability Probability is the chance that something will happen. It can be shown on a line Experimental Probability Of the last 18 trains to arrive at Danville Station, 15 were on time. What is the experimental probability that the next train to arrive will be on time? Answer: on time/total= 15/18= 5/6 CHE 113 20 Theoretical Probability If we toss a fair coin, what is the probability that a tail will show up? 1/2 What about Head, Head, Head and Tail? CHE 113 21 Jury Vote Likelihood ratio = Probability of Prosecution Hypothesis/Probability of Defense Hypothesis Table 3.2.2. Evidential values based upon = Likelihood Ratios (LR) P[P]/P[D] Likelihood Ratio Value of Evidence in Support of Hypothesis <1 Does not support 1 No support or refute 1 to 10 Weak support 10 to 100 Limited support 100 to 1,000 Strong support >1,000 Very strong support Probability that this hair came from someone else than suspect? Hair from a crime scene Suspect Need to examine a SAMPLE and compare it to a POPULATION