Concept explainers
(a)
To explain:
The data set contains the value
(a)
Answer to Problem 20E
Always true
Explanation of Solution
Given:
The data set
Concept used:
The median is the middle number in a sorted ascending or descending list of numbers and more descriptive of that data set than the average.
Calculation:
The first quartile denoted by
Order the data and the median of the lower half.
Always true
(b)
To explain:
The data set contains the value
(b)
Answer to Problem 20E
Not Always true
Explanation of Solution
Given:
The data set
Concept used:
The median is the middle number in a sorted ascending or descending list of numbers and more descriptive of that data set than the average.
Calculation:
The first quartile denoted by
Order the data and the median of the lower half.
The difference of the greatest value and the least value of the data set is different
The first quartile denoted by
Order the data and the median of the lower half.
Not Always true
There may not be
(c)
To explain:
The distribution is skewed right of the given data.
(c)
Answer to Problem 20E
Sales rep B sales are
Explanation of Solution
Given:
The data set
Concept used:
The median is the middle number in a sorted ascending or descending list of numbers and more descriptive of that data set than the average.
Calculation:
The first quartile denoted by
Order the data and the median of the lower half.
Always true
Since the right whisker is longer than the left whisker.
(d)
To explain:
The mean of the given data is
(d)
Explanation of Solution
Given:
The data set
Concept used:
The median is the middle number in a sorted ascending or descending list of numbers and more descriptive of that data set than the average.
Calculation:
The first quartile denoted by
Order the data and the median of the lower half.
Always true
Since the average of the data set.
Chapter 7 Solutions
BIG IDEAS MATH Integrated Math 1: Student Edition 2016
- 1 (Expected Shortfall) Suppose the price of an asset Pt follows a normal random walk, i.e., Pt = Po+r₁ + ... + rt with r₁, r2,... being IID N(μ, o²). Po+r1+. ⚫ Suppose the VaR of rt is VaRq(rt) at level q, find the VaR of the price in T days, i.e., VaRq(Pt – Pt–T). - • If ESq(rt) = A, find ES₁(Pt – Pt–T).arrow_forward2 (Normal Distribution) Let rt be a log return. Suppose that r₁, 2, ... are IID N(0.06, 0.47). What is the distribution of rt (4) = rt + rt-1 + rt-2 + rt-3? What is P(rt (4) < 2)? What is the covariance between r2(2) = 1 + 12 and 13(2) = r² + 13? • What is the conditional distribution of r₁(3) = rt + rt-1 + rt-2 given rt-2 = 0.6?arrow_forward3 (Sharpe-ratio) Suppose that X1, X2,..., is a lognormal geometric random walk with parameters (μ, o²). Specifically, suppose that X = Xo exp(rı + ...Tk), where Xo is a fixed constant and r1, T2, ... are IID N(μ, o²). Find the Sharpe-ratios of rk and log(Xk) — log(Xo) respectively, assuming the risk free return is 0.arrow_forward
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