Student Exploration: Sight vs. Sound Reactions Vocabulary: histogram‚ mean‚ normal distribution‚ range‚ standard deviation‚ stimulus Prior Knowledge Questions (Do these BEFORE using the Gizmo.) Most professional baseball pitchers can throw a fastball over 145 km/h (90 mph). This gives the batter less than half a second to read the pitch‚ decide whether to swing‚ and then try to hit the ball. No wonder hitting a baseball is considered one of the hardest things to do in sports! 1. What
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Chapter 7 #42 The accounting department at Weston Materials‚ Inc.‚ a national manufacturer of unattached garages‚ reports that it takes two construction workers a mean of 32 hours and a standard deviation of 2 hours to erect the Red Barn model. Assume the assembly times follow the normal distribution. a. Determine the z values for 29 and 34 hours. What percent of the garages take between 32 hours and 34 hours to erect? z(29) = (29-32)/2 = -3/2 z(34) = (34-32)/2 = 1 z(32) = 0 P(32 < x <
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99‚ 96‚ 98‚ 97‚ 91‚ 98‚ 80‚ 95‚ 98‚ 96‚ 80‚ 95‚ 88‚ 99‚ 102‚ 95‚ 101‚ 94‚ 92‚ 99‚ 101‚ 97‚ 94‚ 97‚ 102‚ 61. The claim can be rejected; correct answer may be either above 98 or below it. 2. Salaries for Actuaries nationwide graduates entering the actuarial field earn $40‚000. A college placement officer feels that this number is too low. She surveys 36 graduates entering the actuarial field and finds the average salary to be $41‚000. The population standard deviation is $3000. Can her claim
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The population standard deviation σ of a discrete random variable ‚ Measure how close a random variable tends to be the population mean μ‚ so you must understand μ before you understand σ If you have a random variable like a bet at a casino or and investment then the standard deviation σ measure the risk‚ if there is a lot of risk then the standard deviation is high The formulas for standard deviation are given below but you should look at the examples first Population mean Population variance
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Mean and Standard Deviation The mean‚ indicated by μ (a lower case Greek mu)‚ is the statistician ’s jargon for the average value of a signal. It is found just as you would expect: add all of the samples together‚ and divide by N. It looks like this in mathematical form: In words‚ sum the values in the signal‚ xi‚ by letting the index‚ i‚ run from 0 to N-1. Then finish the calculation by dividing the sum by N. This is identical to the equation: μ =(x0 + x1 + x2 + ... + xN-1)/N. If you are not
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between geographic location‚ health status ( healthy or one or more comorbidities)‚ and depression. Random samples of 20 healthy individuals were selected from three geographic locations: Florida‚ New York‚ and North Carolina. Then‚ each was given a standardized test to measure depression (higher test scores indicate higher levels of depression). Similarly‚ random samples of 20 individuals with one or more comorbidities (arthritis‚ hypertension‚ and/or heart ailment) were taken from the three geographic
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Explain the difference between a population and a sample. In which of these is it important to distinguish between the two in order to use the correct formula? mean; median; mode; range; quartiles; variance; standard deviation. Solution: A sample is a subset of a population. A population consists of every member of a particular group of interest. The variance and the standard deviation require that we know whether we have a sample or a population. 2. The following numbers represent the weights in
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according to the following rules: i) Two out of three consecutive points fall beyond the 2σ limit on the same side of the centerline. ii) Four out of five consecutive points fall beyond the 1σ limit‚ on the same side of the centerline. iii) Eight consecutive points falling on one side of the centerline When the process is in statistical control‚ find the false alarm probability (Type-I error) for each case. The corresponding probability measures are obtained from the Normal table as P(3 "
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R 6 The Normal Distribution Objectives Outline After completing this chapter‚ you should be able to 1 2 3 Identify distributions as symmetric or skewed. 4 Find probabilities for a normally distributed variable by transforming it into a standard normal variable. Introduction 6–1 Normal Distributions Identify the properties of a normal distribution. Find the area under the standard normal distribution‚ given various z values. 5 Find specific data values
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A population of measurements is approximately normally distributed with mean of 25 and a variance of 9. Find the probability that a measurement selected at random will be between 19 and 31. Solution: The values 19 and 31 must be transformed into the corresponding z values and then the area between the two z values found. Using the transformation formula from X to z (where µ = 25 and σ √9 = 3)‚ we have z19 = (19 – 25) / 3 = -2 and z31 = (31 - 25) / 3 = +2 From the area between z =±2 is 2(0
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