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Chapter 8. STA 200 Summer I 2011. Valid vs. Invalid Measurement. A variable will be valid if it’s relevant as a measurement of a property. measuring weight with a scale: valid measuring intelligence via cranial circumference: invalid. Predictive Validity.
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Chapter 8 STA 200 Summer I 2011
Valid vs. Invalid Measurement • A variable will be valid if it’s relevant as a measurement of a property. • measuring weight with a scale: valid • measuring intelligence via cranial circumference: invalid
Predictive Validity • Sometimes, the variable we want to measure is related to a future event. • In this scenario, we won’t be able to take a direct measurement, so we’ll have to use a proxy. • Examples: What measurements would we look at if we were interested in… • estimating a person’s risk of heart disease? • a high school student’s readiness for college? • tomorrow’s weather?
Predictive Validity (cont.) • Predictive validity is the ability of a measurement to predict the outcome of future tasks. • Examples: • LDL (bad cholesterol) level is a good predictor of potential heart trouble. • Students with high SAT scores are more likely to graduate from college and have a high GPA than students with low SAT scores.
Errors in Measurement • When measuring a property of an individual, we may not get the true value as a measurement. • Measured Value = True Value + Bias + Random Error
Measurement Problems • Biased Measurement: • Random Error and Reliability:
Example • A person’s temperature was 99.1˚, 99.2˚, 99.1˚, and 99.1˚ when measured four times with the same thermometer. • Their actual temperature was 98.4˚. • Is the measurement process biased? • Is the measurement process reliable?
Another Example • The length of a plot of land is measured several times. The actual length of the plot is 147 feet. • Suppose 5 measurements of the length of the plot were taken, and that the measurements are biased and unreliable. What might their values be?
Rates vs. Counts • The rate (proportion or percentage) at which something occurs is a more valid measure than a count of occurrences. • Example: A chain of appliance stores is comparing two brands of washing machines. • Brand A: 479 service calls on 1,190 machines sold • Brand B: 1,211 service calls on 8,922 machines sold • Which machine has a lesser chance of breaking down?
Rates vs. Counts (cont.) • A researcher studied the number of traffic accidents that were attributed to driver fatigue at different times of the day. • He noticed that the number of such accidents was higher in late afternoon (5pm - 6pm) than early afternoon (1pm - 2pm). • The researcher concluded that driver fatigue plays a larger role in traffic accidents during late afternoon. • Is this conclusion justified?