a.
Construct the frequency distribution with approximately 5classes.
a.
Answer to Problem 31E
The frequency distribution is,
Number of Words | Frequency |
0-1,999 | 26 |
2,000-3,999 | 25 |
4,000-5,999 | 5 |
6,000-7,999 | 0 |
8,000-9,999 | 1 |
Total | 57 |
Explanation of Solution
Calculation:
The given information is that a table representing the number of words spoken in each of these addresses.
Frequency:
The frequencies are calculated by using the tally mark and the
- Based on the given information, the class intervals are 0-1,999, 2,000-3,999, 4,000-5,999, 6,000-7,999, 8,000-9,999.
- Make a tally mark for each value in the corresponding number of words spoken and continue for all values in the data.
- The number of tally marks in each class represents the frequency, f of that class.
Similarly, the frequency of remaining classes for the number of words spoken is given below:
Number of Words | Tally | Frequency |
0-1,999 | 26 | |
2,000-3,999 | 25 | |
4,000-5,999 | 5 | |
6,000-7,999 | 0 | |
8,000-9,999 | 1 | |
Total | 57 |
b.
Construct the frequency histogram based on the frequency distribution.
b.
Answer to Problem 31E
Output obtained from MINITAB software for the number of words spoken is:
Explanation of Solution
Calculation:
Frequency Histogram:
Software procedure:
- Step by step procedure to draw the relative frequency histogram for number of words spoken using MINITAB software.
- Choose Graph > Histogram.
- Choose Simple.
- Click OK.
- In Graph variables, enter the column of Number of Words.
- In Scale, Choose Y-scale Type as Frequency.
- Click OK.
- Select Edit Scale, Enter 0, 2,000, 4,000, 6,000, 8,000, 10,000 in Positions of ticks.
- In Binning, Under Interval Type select Cutpoint and under Interval Definition select Number of intervals as 5 and Cutpoint positions as 0, 2,000, 4,000, 6,000, 8,000, 10,000.
- In Labels, Enter 0, 2,000, 4,000, 6,000, 8,000, 10,000 in Specified.
- Click OK.
Observation:
From the bar graph, it can be seen that maximum number of words spoken are in the interval 0-2,000.
c.
Construct a relative frequency distribution for the data.
c.
Answer to Problem 31E
The relative frequency distribution for the data is:
Number of Words | Relative frequency |
0-1,999 | 0.456 |
2,000-3,999 | 0.439 |
4,000-5,999 | 0.088 |
6,000-7,999 | 0.000 |
8,000-9,999 | 0.018 |
Explanation of Solution
Calculation:
Relative frequency:
The general formula for the relative frequency is,
Therefore,
Similarly, the relative frequencies for the remaining number of words spoken are obtained below:
Number of Words | Frequency | Relative frequency |
0-1,999 | 26 | |
2,000-3,999 | 25 | |
4,000-5,999 | 5 | |
6,000-7,999 | 0 | |
8,000-9,999 | 1 |
d.
Construct the relative frequency histogram based on the frequency distribution.
d.
Answer to Problem 31E
Output obtained from MINITAB software for the number of words spoken is:
Explanation of Solution
Calculation:
Relative Frequency Histogram:
Software procedure:
- Step by step procedure to draw the relative frequency histogram for the number of words spoken using MINITAB software.
- Choose Graph > Histogram.
- Choose Simple.
- Click OK.
- In Graph variables, enter the column of Number of Words.
- In Scale, Choose Y-scale Type as Percent.
- Click OK.
- Select Edit Scale, Enter 0, 2,000, 4,000, 6,000, 8,000, 10,000 in Positions of ticks.
- In Binning, Under Interval Type select Cutpoint and under Interval Definition select Number of intervals as 5 and Cutpoint positions as 0, 2,000, 4,000, 6,000, 8,000, 10,000.
- In Labels, Enter 0, 2,000, 4,000, 6,000, 8,000, 10,000 in Specified.
- Click OK.
Observation:
From the bar graph, it can be seen that maximum number of words spoken is in the interval 0-2,000.
e.
Check whether the histograms are skewed to the left, skewed to the right or approximately symmetric.
e.
Answer to Problem 31E
The histogram is skewed to the right.
Explanation of Solution
From the given histogram, the right hand tail is larger than the left hand tail from the maximum frequency value. Hence, the shape of the distribution is right skewed.
f.
Construct the frequency distribution with approximately 9classes.
f.
Answer to Problem 31E
The frequency distribution is,
Number of Words | Frequency |
0-999 | 4 |
1,000-1,999 | 22 |
2,000-2,999 | 18 |
3,000-3,999 | 7 |
4,000-4,999 | 4 |
5,000-5,999 | 1 |
6,000-6,999 | 0 |
7,000-7,999 | 0 |
8,000-8,999 | 1 |
Total | 57 |
Explanation of Solution
Calculation:
Frequency:
The frequencies are calculated by using the tally mark and the range of the data is from 0 to 8,999.
- Based on the given information, the class intervals are 0-999, 1,000-1,999, 2,000-2,999, 3,000-3,999, 4,000-4,999, 5,000-5,999, 6,000-6,999, 7,000-7,999, 8,000-8,999.
- Make a tally mark for each value in the corresponding number of words spoken and continue for all values in the data.
- The number of tally marks in each class represents the frequency, f of that class.
Similarly, the frequency of remaining classes for the number of words spoken is given below:
Number of Words | Tally | Frequency |
0-999 | 4 | |
1,000-1,999 | 22 | |
2,000-2,999 | 18 | |
3,000-3,999 | 7 | |
4,000-4,999 | 4 | |
5,000-5,999 | 1 | |
6,000-6,999 | 0 | |
7,000-7,999 | 0 | |
8,000-8,999 | 1 | |
Total | 57 |
g.
Repeat parts (b) to (d), using the frequency distribution constructed in part (f).
g.
Answer to Problem 31E
Output obtained from MINITAB software for the number of words spoken is:
The relative frequency distribution for the data is:
Number of Words | Relative frequency |
0-999 | 0.070 |
1,000-1,999 | 0.386 |
2,000-2,999 | 0.316 |
3,000-3,999 | 0.123 |
4,000-4,999 | 0.070 |
5,000-5,999 | 0.018 |
6,000-6,999 | 0.000 |
7,000-7,999 | 0.000 |
8,000-8,999 | 0.018 |
Output obtained from MINITAB software for the number of words spoken is:
Explanation of Solution
Calculation:
Frequency Histogram:
Software procedure:
- Step by step procedure to draw the relative frequency histogram for the number of words spoken using MINITAB software.
- Choose Graph > Histogram.
- Choose Simple.
- Click OK.
- In Graph variables, enter the column of Number of Words.
- In Scale, Choose Y-scale Type as Frequency.
- Click OK.
- Select Edit Scale, Enter 0, 1,000, 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000, 90,00 in Positions of ticks.
- In Binning, Under Interval Type select Cutpoint and under Interval Definition select Number of intervals as 9 and Cutpoint positions as 0, 1,000, 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000, 9,000.
- In Labels, Enter 0, 1,000, 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000, 9,000 in Specified.
- Click OK.
Observation:
From the bar graph, it can be seen that maximum number of words spoken is in the interval 1,000-2,000.
Relative frequency:
Similarly, the relative frequencies for the remaining number of words spoken are obtained below:
Number of Words | Frequency | Relative frequency |
0-999 | 4 | |
1,000-1,999 | 22 | |
2,000-2,999 | 18 | |
3,000-3,999 | 7 | |
4,000-4,999 | 4 | |
5,000-5,999 | 1 | |
6,000-6,999 | 0 | |
7,000-7,999 | 0 | |
8,000-8,999 | 1 | |
Total | 57 |
Relative Frequency Histogram:
Software procedure:
- Step by step procedure to draw the relative frequency histogram for the number of words spoken using MINITAB software.
- Choose Graph > Histogram.
- Choose Simple.
- Click OK.
- In Graph variables, enter the column of Number of Words.
- In Scale, Choose Y-scale Type as Percent.
- Click OK.
- Select Edit Scale, Enter 0, 1,000, 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000 and 9,000 in Positions of ticks.
- In Binning, Under Interval Type select Cutpoint and under Interval Definition select Number of intervals as 9 and Cutpoint positions as 0, 1,000, 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000 and 9,000.
- In Labels, Enter 0, 1,000, 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000 and 9,000in Specified.
- Click OK.
Observation:
From the bar graph, it can be seen that maximum number of words spoken is in the interval 1,000-2,000.
h.
Check whether the 9 and 5 classes are reasonable or one choice is much better than the other and explain the reason.
h.
Answer to Problem 31E
Both the 5 and 9 classes are reasonable.
Explanation of Solution
Answer will vary.
The number of classes can be obtained by the following two points:
- The number of classes should be between 5 and 20.
- A larger number of classes will be appropriate for a very large data set.
Here number of classes for the histograms are 5 and 9 respectively. Thus, the number of classes are lies between 5 and 20.
Hence, the both 5 and 9 classes are reasonable.
Want to see more full solutions like this?
Chapter 2 Solutions
Essential Statistics
- 4. Suppose that P(X = 1) = P(X = -1) = 1/2, that Y = U(-1, 1) and that X and Y are independent. (a) Show, by direct computation, that X + Y = U(-2, 2). (b) Translate the result to a statement about characteristic functions. (c) Which well-known trigonometric formula did you discover?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). (b) Is it true that Qx(ah) =aQx(h)? (c) Show that, if X and Y are independent random variables, then Qx+y (h) min{Qx(h). Qy (h)). To put the concept in perspective, if X1, X2, X, are independent, identically distributed random variables, and S₁ = Z=1Xk, then there exists an absolute constant, A, such that A Qs, (h) ≤ √n Some references: [79, 80, 162, 222], and [204], Sect. 1.5.arrow_forward29 Suppose that a mound-shaped data set has a must mean of 10 and standard deviation of 2. a. About what percentage of the data should lie between 6 and 12? b. About what percentage of the data should lie between 4 and 6? c. About what percentage of the data should lie below 4? 91002 175/1 3arrow_forward
- 2,3, ample and rical t? the 28 Suppose that a mound-shaped data set has a mean of 10 and standard deviation of 2. a. About what percentage of the data should lie between 8 and 12? b. About what percentage of the data should lie above 10? c. About what percentage of the data should lie above 12?arrow_forward27 Suppose that you have a data set of 1, 2, 2, 3, 3, 3, 4, 4, 5, and you assume that this sample represents a population. The mean is 3 and g the standard deviation is 1.225.10 a. Explain why you can apply the empirical rule to this data set. b. Where would "most of the values" in the population fall, based on this data set?arrow_forward30 Explain how you can use the empirical rule to find out whether a data set is mound- shaped, using only the values of the data themselves (no histogram available).arrow_forward
- 5. Let X be a positive random variable with finite variance, and let A = (0, 1). Prove that P(X AEX) 2 (1-A)² (EX)² EX2arrow_forward6. Let, for p = (0, 1), and xe R. X be a random variable defined as follows: P(X=-x) = P(X = x)=p. P(X=0)= 1-2p. Show that there is equality in Chebyshev's inequality for X. This means that Chebyshev's inequality, in spite of being rather crude, cannot be improved without additional assumptions.arrow_forward4. Prove that, for any random variable X, the minimum of EIX-al is attained for a = med (X).arrow_forward
- 8. Recall, from Sect. 2.16.4, the likelihood ratio statistic, Ln, which was defined as a product of independent, identically distributed random variables with mean 1 (under the so-called null hypothesis), and the, sometimes more convenient, log-likelihood, log L, which was a sum of independent, identically distributed random variables, which, however, do not have mean log 1 = 0. (a) Verify that the last claim is correct, by proving the more general statement, namely that, if Y is a non-negative random variable with finite mean, then E(log Y) log(EY). (b) Prove that, in fact, there is strict inequality: E(log Y) < log(EY), unless Y is degenerate. (c) Review the proof of Jensen's inequality, Theorem 5.1. Generalize with a glimpse on (b).arrow_forward3. Prove that, for any random variable X, the minimum of E(X - a)² is attained for a = EX. Provedarrow_forward7. Cantelli's inequality. Let X be a random variable with finite variance, o². (a) Prove that, for x ≥ 0, P(X EX2x)≤ 02 x² +0² 202 P(|X - EX2x)<≤ (b) Find X assuming two values where there is equality. (c) When is Cantelli's inequality better than Chebyshev's inequality? (d) Use Cantelli's inequality to show that med (X) - EX ≤ o√√3; recall, from Proposition 6.1, that an application of Chebyshev's inequality yields the bound o√√2. (e) Generalize Cantelli's inequality to moments of order r 1.arrow_forward
- Holt Mcdougal Larson Pre-algebra: Student Edition...AlgebraISBN:9780547587776Author:HOLT MCDOUGALPublisher:HOLT MCDOUGALGlencoe Algebra 1, Student Edition, 9780079039897...AlgebraISBN:9780079039897Author:CarterPublisher:McGraw HillBig Ideas Math A Bridge To Success Algebra 1: Stu...AlgebraISBN:9781680331141Author:HOUGHTON MIFFLIN HARCOURTPublisher:Houghton Mifflin Harcourt