EBK INTRODUCTION TO THE PRACTICE OF STA
8th Edition
ISBN: 9781319116828
Author: Moore
Publisher: VST
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Chapter 9.1, Problem 3UYK
To determine
To explain: The preferable distribution to interpret the data.
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20 km, because
GISS
Worksheet 10
Jesse runs a small business selling and delivering mealie meal to the spaza shops.
He charges a fixed rate of R80, 00 for delivery and then R15, 50 for each packet of
mealle meal he delivers. The table below helps him to calculate what to charge
his customers.
10
20
30
40
50
Packets of mealie
meal (m)
Total costs in Rands
80
235
390
545
700
855
(c)
10.1.
Define the following terms:
10.1.1. Independent Variables
10.1.2. Dependent Variables
10.2.
10.3.
10.4.
10.5.
Determine the independent and dependent variables.
Are the variables in this scenario discrete or continuous values? Explain
What shape do you expect the graph to be? Why?
Draw a graph on the graph provided to represent the information in the
table above.
TOTAL COST OF PACKETS OF MEALIE MEAL
900
800
700
600
COST (R)
500
400
300
200
100
0
10
20
30
40
60
NUMBER OF PACKETS OF MEALIE MEAL
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).
Chapter 9 Solutions
EBK INTRODUCTION TO THE PRACTICE OF STA
Ch. 9.1 - Prob. 1UYKCh. 9.1 - Prob. 2UYKCh. 9.1 - Prob. 3UYKCh. 9.1 - Prob. 4UYKCh. 9.1 - Prob. 5UYKCh. 9.1 - Prob. 6UYKCh. 9.1 - Prob. 7UYKCh. 9.1 - Prob. 8UYKCh. 9.1 - Prob. 9UYKCh. 9.1 - Prob. 10UYK
Ch. 9.1 - Prob. 11UYKCh. 9.1 - Prob. 12UYKCh. 9.1 - Prob. 13UYKCh. 9.1 - Prob. 14UYKCh. 9.2 - Prob. 15UYKCh. 9.2 - Prob. 16UYKCh. 9.2 - Prob. 17UYKCh. 9.2 - Prob. 18UYKCh. 9.2 - Prob. 19UYKCh. 9 - Prob. 50ECh. 9 - Prob. 51ECh. 9 - Prob. 20ECh. 9 - Prob. 27ECh. 9 - Prob. 28ECh. 9 - Prob. 29ECh. 9 - Prob. 22ECh. 9 - Prob. 31ECh. 9 - Prob. 32ECh. 9 - Prob. 37ECh. 9 - Prob. 38ECh. 9 - Prob. 39ECh. 9 - Prob. 40ECh. 9 - Prob. 41ECh. 9 - Prob. 42ECh. 9 - Prob. 49ECh. 9 - Prob. 52ECh. 9 - Prob. 53ECh. 9 - Prob. 54ECh. 9 - Prob. 55ECh. 9 - Prob. 21ECh. 9 - Prob. 23ECh. 9 - Prob. 24ECh. 9 - Prob. 25ECh. 9 - Prob. 26ECh. 9 - Prob. 30ECh. 9 - Prob. 33ECh. 9 - Prob. 34ECh. 9 - Prob. 35ECh. 9 - Prob. 36ECh. 9 - Prob. 43ECh. 9 - Prob. 44ECh. 9 - Prob. 45ECh. 9 - Prob. 46ECh. 9 - Prob. 47ECh. 9 - Prob. 48E
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Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, statistics and related others by exploring similar questions and additional content below.Similar questions
- A 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_forward8. 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_forward
- 9. 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_forward9. 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_forward
- 3. 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_forward1. 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_forward
- 1. 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_forward9. The concentration function of a random variable X is defined as Qx(h) sup P(x≤x≤x+h), h>0. = x (a) Show that Qx+b(h) = Qx(h).arrow_forward
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