Sunday, May 25, 2014

Relative, Cumulative And Relative Cumulative Frequency Distributions

A relative frequency distribution is obtained by dividing each frequency by the number of observations and multiplying the resulting proportion by 100%. A cumulative frequency distribution contains the total number of observations whose values are less than the upper limit for each interval. It is constructed by adding the frequencies of all frequency distribution intervals up to and including the present interval. A relative cumulative frequency distribution converts all cumulative frequencies to cumulative proportions or percentages.
Table-1 displays the number of days to maturity for 40 short-term investments.
Example:
Table 1: Days to maturity 40 short-term investments.

71
64
99
55
64
89
87
65
62
38
67
70
60
69
78
39
75
56
71
51
99
68
95
86
57
53
47
50
55
81
80
98
51
36
63
66
85
79
83
70
Construct a frequency distribution.

Solution:
By using formula
To get the idea as to the number of class intervals to use, we can apply Sturges’s rule to obtain

Now let us divide the range by 8 to get some idea about the class interval width. We have
It is apparent that a class interval width of 10 will be more convenient to use, as well as more meaningful to the reader.

By using Quick Guide
A frequency distribution with 6 classes is developed. The width of each class is
Table 2: Frequency distribution of the data in Table 2.
 Table 3: Cumulative Frequency and Relative Cumulative Frequency Distributions

Class interval
Frequency

Cumulative frequency

Relative Frequency
30—39
3
3
3/40
40—49
1
4
1/40
50—59
8
12
8/40
60—69
10
22
10/40
70—79
7
29
7/40
80—89
7
36
7/40
90—99
4
40
7/40
Total
40

1
Example: Jennie Bishop, marketing director for a leading mobile phone company, obtained records of minutes used by a random sample of 110 subscribers to the company’s low-end user plan (250 peak minutes per month). Table 1 is a list of minutes used by each subscriber in the sample during one particular month. What do the data indicate?

Table 4: Mobile Phone Usage (Peak Minutes)

271
236
294
252
254
263
266
222
262
278
288
262
237
247
282
224
263
267
254
271
278
263
262
288
247
252
264
263
247
225
281
279
238
252
242
248
263
255
294
268
255
272
271
291
263
242
288
252
226
263
269
227
273
281
267
263
244
249
252
256
263
252
261
245
252
294
288
245
251
269
256
264
252
232
275
284
252
263
274
252
252
256
254
269
234
285
275
263
263
246
294
252
231
265
269
235
275
288
294
263
247
252
269
261
266
269
236
276
248
298

Solution

Table 1 by itself offers little guidance to help the marketing director develop a marketing strategy. We can find some information in Table 1: The smallest amount of peak minutes used was 222 minutes, and the maximum time used was 298 minutes. However, we will need more information than this before submitting any report to senior-level executives. To better understand what the data in Table 1 indicate, we first develop a frequency distribution.

By using formula
Number of classes is determined by

By using Quick Guide
A frequency distribution with eight classes is developed. The width of each class is


Since the smallest value is 222, one choice for the first interval is “220 but less than 230”. Subsequent intervals of equal width are added to the frequency distribution, as well as the number of calls that belong to each class. The following Table is a frequency distribution for the mobile phone data in Table 1.

Table 5
: Frequency and Relative Frequency Distribution for Mobile Phone Usage


Mobile phone usage (in minutes)
Tally Marks
Frequency
Percent
220 – 229

5
4.5
230 – 239

8
7.3
240 – 249

13
11.8
  250 – 259

22
20.0
260 – 269

32
29.1
270 – 279

13
11.8
280 – 289

10
9.1
290 – 299

7
6.4
Total

110
100

The manager may want to know mobile usage below (or above) a certain amount of time. Table 2 is a cumulative frequency distribution and a cumulative percentage distribution.

Table 6: Cumulative Frequency and Relative Cumulative Frequency Distributions for Mobile Phone Usage.

Mobile Phone Usage
(in Minutes)
Frequency
Cumulative Frequency
Cumulative %
Less than 230
5
5
4.5
Less than 240
8
13
11.8
Less than 250
13
26
23.6
Less than 260
22
48
43.6
Less than 270
32
80
72.7
Less than 280
13
93
84.5
Less than 290
10
103
93.6
Less than 300
7
110
100.0

The frequency distributions in Table 2 and Table 3 are an improvement over the original list of data in Table 1. We have at least summarized 110 observations into 8 categories and are able to tell Jennie that less than one-fourth (23.6%) of the subscribers sampled used their mobile phones within the guidelines of their plans during the month of the study. The marketing manager might suggest that an advertising campaign be initiated to promote a plan with an increase in peak minutes.

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