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a.
To obtain: The
a.
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Answer to Problem 26CQ
The probability of getting a sum 6 or 7 is
Explanation of Solution
Given info:
A pair of six-sided dice is rolled.
Calculation:
The possibilities for rolling a pair of six-sided dice is,
Thus, the total number of outcomes is 36.
Let
Hence, the possible outcomes for getting a sum 6 are,
That is, there are 5 outcomes for event A.
The formula for probability of event A is,
Substitute 5 for ‘Number of outcomes in A’ and 36 for ‘Total number of outcomes in the
Let event B denote getting a sum 7.
Hence, the possible outcomes for getting a sum 7 are,
That is, there are 6 outcomes for eventB.
The formula for probability of event B is,
Substitute 6 for ‘Number of outcomes in B’ and 36 for ‘Total number of outcomes in the sample space’,
The formula for probability of getting event A or event B is,
Substitute
Thus, the probability that the outcome is sum less than 9 is
b.
To obtain: The probability of getting a sum greater than 8.
b.
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Answer to Problem 26CQ
The probability of getting a sum greater than 8 is
Explanation of Solution
Calculation:
Let event C denote getting a sum greater than 8.
Hence, the possible outcomes for getting a sum greater than 8 are,
That is, there are 10 outcomes for eventC.
The formula for probability of event C is,
Substitute 10 for ‘Number of outcomes in C’ and 36 for ‘Total number of outcomes in the sample space’,
Thus, the probability of getting a sum greater than 8 is
c.
To obtain: The probability of getting a sum less than 3 or greater than 8.
c.
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Answer to Problem 26CQ
The probability of getting a sum less than 3 or greater than 8 is
Explanation of Solution
Calculation:
Let event D denote getting a less than 3.
Hence, the possible outcomes for getting a sum less than 3 are,
That is, there are 1 outcome for eventD.
The formula for probability of event D is,
Substitute 1 for ‘Number of outcomes in A’ and 36 for ‘Total number of outcomes in the sample space’,
Let event E denote getting a sum greater than 8.
Hence, the possible outcomes for getting a sum greater than 8 are,
That is, there are 10 outcomes for eventE.
The formula for probability of event E is,
Substitute 10 for ‘Number of outcomes in E’ and 36 for ‘Total number of outcomes in the sample space’,
Addition Rule:
The formula for probability of getting event A or event B is,
Substitute
Thus, the probability of getting a sum less than 3 or greater than 8 is
d.
To obtain: The probability of getting a sum divisible 3.
d.
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Answer to Problem 26CQ
The probability of getting a sum divisible 3 is
Explanation of Solution
Calculation:
Let event E denote getting a sum greater than 8.
Hence, the possible outcomes for getting a sum divisible 3 are,
That is, there are 12 outcomes for eventE.
The formula for probability of event E is,
Substitute 12 for ‘Number of outcomes in E’ and 36 for ‘Total number of outcomes in the sample space’,
Thus, the probability of getting a sum divisible 3 is
e.
To obtain: The probability of getting a sum of 16.
e.
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Answer to Problem 26CQ
The probability of getting a sum of 16 is0.
Explanation of Solution
Calculation:
Let event F denote getting a sum of 16.
Here, the number of possible outcomes for getting a sum of 16 is 0.
That is, there are 0 outcomes for eventF.
The formula for probability of event F is,
Substitute 0 for ‘Number of outcomes in F’ and 36 for ‘Total number of outcomes in the sample space’,
Thus, the probability of getting a sum of 16 is0.
f.
To obtain: The probability of getting a sum less than 11.
f.
![Check Mark](/static/check-mark.png)
Answer to Problem 26CQ
The probability of getting a sum less than 11 is
Explanation of Solution
Calculation:
Let event G denote getting a sum less than 11.
Hence, the possible outcomes for getting a sum divisible 3 are,
That is, there are 33 outcomes for eventG.
The formula for probability of event G is,
Substitute 33 for ‘Number of outcomes in F’ and 36 for ‘Total number of outcomes in the sample space’,
Thus, the probability of getting a sum less than 11 is
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Chapter 4 Solutions
Elementary Statistics: A Step By Step Approach
- Let X be a random variable with support SX = {−3, 0.5, 3, −2.5, 3.5}. Part ofits probability mass function (PMF) is given bypX(−3) = 0.15, pX(−2.5) = 0.3, pX(3) = 0.2, pX(3.5) = 0.15.(a) Find pX(0.5).(b) Find the cumulative distribution function (CDF), FX(x), of X.1(c) Sketch the graph of FX(x).arrow_forwardA well-known company predominantly makes flat pack furniture for students. Variability with the automated machinery means the wood components are cut with a standard deviation in length of 0.45 mm. After they are cut the components are measured. If their length is more than 1.2 mm from the required length, the components are rejected. a) Calculate the percentage of components that get rejected. b) In a manufacturing run of 1000 units, how many are expected to be rejected? c) The company wishes to install more accurate equipment in order to reduce the rejection rate by one-half, using the same ±1.2mm rejection criterion. Calculate the maximum acceptable standard deviation of the new process.arrow_forward5. Let X and Y be independent random variables and let the superscripts denote symmetrization (recall Sect. 3.6). Show that (X + Y) X+ys.arrow_forward
- 8. Suppose that the moments of the random variable X are constant, that is, suppose that EX" =c for all n ≥ 1, for some constant c. Find the distribution of X.arrow_forward9. The concentration function of a random variable X is defined as Qx(h) = sup P(x ≤ X ≤x+h), h>0. Show that, if X and Y are independent random variables, then Qx+y (h) min{Qx(h). Qr (h)).arrow_forward10. Prove that, if (t)=1+0(12) as asf->> O is a characteristic function, then p = 1.arrow_forward
- 9. The concentration function of a random variable X is defined as Qx(h) sup P(x ≤x≤x+h), h>0. (b) Is it true that Qx(ah) =aQx (h)?arrow_forward3. Let X1, X2,..., X, be independent, Exp(1)-distributed random variables, and set V₁₁ = max Xk and W₁ = X₁+x+x+ Isk≤narrow_forward7. Consider the function (t)=(1+|t|)e, ER. (a) Prove that is a characteristic function. (b) Prove that the corresponding distribution is absolutely continuous. (c) Prove, departing from itself, that the distribution has finite mean and variance. (d) Prove, without computation, that the mean equals 0. (e) Compute the density.arrow_forward
- 1. Show, by using characteristic, or moment generating functions, that if fx(x) = ½ex, -∞0 < x < ∞, then XY₁ - Y2, where Y₁ and Y2 are independent, exponentially distributed random variables.arrow_forward1. Show, by using characteristic, or moment generating functions, that if 1 fx(x): x) = ½exarrow_forward1990) 02-02 50% mesob berceus +7 What's the probability of getting more than 1 head on 10 flips of a fair coin?arrow_forward
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