Many people believe that the daily change in price of a company's stock in the stock market is a random variable with mean 0 and variance $\sigma^2$ during the middle 2 months between 2 earning report dates when there is not much news released. That is, if $Y_n$ represents the closing price of the stock on the $n$th trading day of that period, then $Y_n = Y_{n-1} + X_n$, for $1 \leq n \leq 60$, where $X_1, X_2, \ldots, X_{60}$ are independent and identically distributed random variables with mean 0 and variance $\sigma^2$. Suppose that the stock price at the beginning of the 2-month period is 100. If $\sigma = 2$, what is the approximate probability that the stock’s closing price on the 30th trading day will exceed 110, i.e., what is $P(Y_{30} > 110)$

Answered: Image /qna-images/answer/b641e74a-f4d0-414b-8023-ac3703b978f7.jpg

Answered: Many people believe that the daily…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Suppose that the return for a particular investment is normally distributed with a population mean of 10.1% and a population standard deviation of 5.4%. A person must score in the upper 5% of the population on an IQ test to qualify for a particular occupation If IQ scores are normally distributed with a mean of 100 and a standard deviation of 15, what score must a person have to qualify for this occupation?
Need only a handwritten solution only (not a typed one).
The time between calls is exponentially distributed with a mean time between calls of 9 minutes. (a) What is the probability that the time until the first call is less than 5 minutes? (Round your answer to 4 decimal places.) (b) What is the probability that time the until the first call is between 5 and 15 minutes? (Round your answer to 4 decimal places.) (c) If the mean time between calls is 10 minutes, determine the length of an interval of time such that the probability of at least one call in the interval is 0.90. (in minutes) (Round your answer to 2 decimal places.) (a) (b) i (c) i
n 11 of 17 > The Centers for Disease Control and Prevention (CDC) estimated the percent of individuals in each state who are classified as overweight or obese in different years. They calculated the estimates separately for three different age classes, including children (2-4 years old), adolescents (students in grades 9-12), and adults (aged 18 years and older). The boxplots and five-number summaries apply to the data sets of two different age classes. Match the appropriate descriptions to the data sets. Answer Bank the distribution is skewed to the left 33 34 35 36 37 38 39 25% of values are less than 11.25 Adults who were overweight in 2013 (%) the distribution is close to symmetrical Min Q1 Median 03 Max 25% of the values are more than 13.50 33.40 34.70 35.40 36.58 38.60 25% of values are less than 34.70 the distribution is skewed to the right 25% of the values are more than 18.00 6. 10 12 14 16 18 20 25% of the values are less than 6.40 Adolescents who were obese in 2013 (%) 25%…
This cardiologist gets a report on his patients' sugar consumption from the nutritionist. He becomes concerned that his patients seem to consume even more sugar that what is in a typical American diet. He decides to take a random sample of 100 of his patients and calculate the mean sugar consumption, x̅, of these 100 patients. The mean sugar consumption for these 100 patients is 17.3 teaspoons. Let's assume, for the moment, that his patients are no different than the general population of Americans with µ (daily sugar consumption) = 16.1 teaspoons and σ = 3.5 teaspoons and that his sample of 100 patients is one random sample from this population. What is the probability of obtaining a mean sugar consumption of 17.3 teaspoons (or more) in his sample of 100 patients if his patients are similar to the general population? What is the probability that the average (x̅) is greater than 17.3?
A researcher is using a panel data set on n = 1000 workers over T = 10years (from 2001 through 2010) that contains the workers’ earnings, gender,education, and age. The researcher is interested in the effect of educationon earnings. Give some examples of unobserved person-specific variablesthat are correlated with both education and earnings. Can you think ofexamples of time-specific variables that might be correlated with educationand earnings? How would you control for these person-specific and time-specific effects in a panel data regression?
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