personnel are based on correlational research‚ in which variables are measured and the statistical association between them is assessed. A statistically significant correlation between two variables indicates that the variables are associated‚ and that this association is unlikely to have arisen by chance. For example‚ a significant positive correlation between stress and absenteeism means that in general‚ individuals who are experiencing higher stress tend to be absent from work more often than individuals
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Business Statistics MGSC-372 Review Normal Distribution The Normal Distribution aka The Gaussian Distribution The Normal Distribution y 1 f ( x) e 2 1 x 2 2 x Areas under the Normal Distribution curve -3 -2 - 68% 95% 99.7% + +2 +3 X = N( ‚ 2 ) Determining Normal Probabilities Since each pair of values for and represents a different distribution‚ there are an infinite number of possible normal distributions. The number of statistical tables
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Review Topic I: Describing Data [pic] [pic] [pic] [pic] [pic] [pic] [pic] [pic] [pic] FREE RESPONSE Use the given data set of test grades from a college statistics class for this question. 85 72 64 65 98 78 75 76 82 80 61 92 72 58 65 74 92 85 74 76 77 77 62 68 68 54 62 76 73 85 88 91 99 82 80 74 76 77 70 60 A. Construct two different graphs of these data B. Calculate the five-number summary and the mean and standard deviation of the data. C. Describe the distribution of the
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Question 2: [20 points] If a resistor with resistance R ohms carries a current of I amperes‚ the potential difference across the resistor‚ in volts‚ is given by V=IR. Suppose that I is lognormal with parameters μI =1 and σI2 = 0.2‚ R is lognormal with parameters μR =4 and σR2 = 0.1‚ and that I and R are independent. (a) Show that V is lognormally distributed ‚ and compute the parametersμV and σV2 (Hint: ln V = ln I + ln R) (b) Find P(V < 200) (c) Find P(150≦V≦300) (d) Find the mean of V (e) Find
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Marks: 1 Assume that X has a normal distribution‚ and find the indicated probability. The mean is μ = 60.0 and the standard deviation is σ = 4.0. Find the probability that X is less than 53.0. Choose one answer. a. 0.5589 b. 0.0401 c. 0.9599 d. 0.0802 Question2 Marks: 1 Use the given degree of confidence and sample data to find a confidence interval for the population standard deviation. Assume that the population has a normal distribution. Weights of eggs: 95% confidence;
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Type I error Type II error Negative interval | 2. Bivariate statistics refers to the statistical analysis of the relationship between two variables. (Points : 1) | True False | 3. Positive relationships between two variables indicate that‚ as the score of one increases‚ the score of the other increases. (Points : 1) | True False | 4. A result that is probably not attributable to chance is: (Points : 1) | Type I error
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HOMEWORK 2 FROM CHAPTER 6 and 7‚ NORMAL DISTRIBUTION AND SAMPLING Instructor: Asiye Aydilek PART 1- Multiple Choice Questions ____ 1. For the standard normal probability distribution‚ the area to the left of the mean is a. –0.5 c. any value between 0 to 1 b. 0.5 d. 1 Answer: B The total area under the curve is 1. The area on the left is the half of 1 which is 0.5. ____ 2. Which of the following is not a characteristic of the normal probability distribution? a. The mean and median are
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Annual prize distribution | | | |The program is about to commence. We need no musical interlude. Therefore you are requested to switch off your mobile phones. | |
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The Normal and Lognormal Distributions John Norstad j-norstad@northwestern.edu http://www.norstad.org February 2‚ 1999 Updated: November 3‚ 2011 Abstract The basic properties of the normal and lognormal distributions‚ with full proofs. We assume familiarity with elementary probability theory and with college-level calculus. 1 1 DEFINITIONS AND SUMMARY OF THE PROPOSITIONS 1 Definitions and Summary of the Propositions ∞ √ Proposition 1: −∞ 2 2 1 e−(x−µ) /2σ
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show‚ given that John does. Answer: P(B/A) = P(B/A)= P(A and B) c) Do John and Jane watch the show independently of each other? Justify your answer. Answer: The two event are not independent because: P(A and B) P(A). P(B) = 0.4 x 0.5 = 0.20 P(A and B) P(A). P(B) So the two event no (independent) Question 3 Consider the following probability mass function x -2 0 1 2 P(X= x) .2 .3 .3 .2 Find the following:
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