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Histograms, Frequency Distributions and Related Topics These are constructions that will allow us to represent large sets of data in ways that may be more.

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Presentation on theme: "Histograms, Frequency Distributions and Related Topics These are constructions that will allow us to represent large sets of data in ways that may be more."— Presentation transcript:

1 Histograms, Frequency Distributions and Related Topics These are constructions that will allow us to represent large sets of data in ways that may be more meaningful to the reader.

2 Histograms provide graphical representation of data with bars whose heights indicate the number of data in a certain range. A frequency table shows the distribution of data in classes (intervals). The classes are constructed so that each data values falls into exactly one class, and the class frequency is the number of data in the class. Histograms provide graphical representation of data with bars whose heights indicate the number of data in a certain range. A frequency table shows the distribution of data in classes (intervals). The classes are constructed so that each data values falls into exactly one class, and the class frequency is the number of data in the class.

3 How long does the 1161 mile Iditarod take? (p. 47, problem 7). 261271236244279296284299288 247256 338360341333261266287296313311307 299303277283304305288290288289297299 332330309328307328285291295298306315 310318 320333321323324327 Can you easily see what the maximum and minimum times are? Is it easy to tell how the times are distributed?

4 To find the class width, First compute: Largest value - smallest Value Desired number of classes Increase the value computed to the next highest whole, number even if the first value was a whole number. This will ensure the classes cover the data. The lower class limit of a class is the lowest data that can fit into the class, the upper class limit is the highest data value that can fit into the class. The class width is the difference between lower class limits of adjacent classes.

5 In a frequency table, divide the data range into classes equal width, compute: Largest value - smallest Value Desired number of classes Increase the value computed to the next highest whole, number even if the first value was a whole number. This will ensure the classes cover the data. The lower class limit of a class is the lowest data that can fit into the class, the upper class limit is the highest data value that can fit into the class. The class width is the difference between lower class limits of adjacent classes.

6 Class Boundaries  Class boundaries cannot belong to any class.  Class boundaries between adjacent classes are the midpoint between the upper limit of the first class, and the lower limit of the higher class.  Differences between upper and lower boundaries of a given class is the class width.  The midpoint of a class (class mark) is the average of its upper and lower boundaries, which is also the average of its upper and lower limits.  Class boundaries cannot belong to any class.  Class boundaries between adjacent classes are the midpoint between the upper limit of the first class, and the lower limit of the higher class.  Differences between upper and lower boundaries of a given class is the class width.  The midpoint of a class (class mark) is the average of its upper and lower boundaries, which is also the average of its upper and lower limits.

7 It is easier to make the histogram if the data is sorted: 236244247256261 266271277279283284 285287288 289290291295296 297298299 303304305306307 309310311313315318 320321323324327 328 330332333 338341360

8  The class width is computed as (360-236)/5 which is 24.8. Hence the class width is 25. Lower Limit Upper Limit Lower Boundary Upper Boundary MarkFrequency 236260235.5260.52484 261285260.5285.52739 286310285.5310.529825 311335310.5335.532316 336360335.5360.53483

9 Histograms A histogram is a bar graph that can be constructed using a frequency table:  Put the class boundaries on the horizontal axis  The bars have the same width and always touch and the edges of the bars are on class boundaries.  The height of the bar is the class frequency. A histogram is a bar graph that can be constructed using a frequency table:  Put the class boundaries on the horizontal axis  The bars have the same width and always touch and the edges of the bars are on class boundaries.  The height of the bar is the class frequency.

10 Histogram for Iditarod Data

11 Relative Frequencies The relative frequency of a class is f/n where f is the frequency of the class, and n is the total of all frequencies. Relative frequency tables are like frequency tables except the relative frequency is given. Relative frequency histograms are like frequency histograms except the height of the bars represent relative frequencies. The relative frequency of a class is f/n where f is the frequency of the class, and n is the total of all frequencies. Relative frequency tables are like frequency tables except the relative frequency is given. Relative frequency histograms are like frequency histograms except the height of the bars represent relative frequencies.

12 Systolic blood pressures of 50 subjects Make a histogram with 8 classes 100102104108 110 112 115116 118 120 126 128 130 132 134 136 138140 146 148152 156160190200208

13 Systolic blood pressures of 50 subjects Class Width = (208-100)/8 = 13.5, thus use 14 L. BndyU. BndyL. LimitU. LimitMarkFreq.R. Freq.C. Freq 99.5113.5100113106.5100.2010 113.5127.5114127120.5120.2422 127.5141.5128141134.5170.3439 141.5155.5142155148.550.1044 155.5169.5156169162.520.0446 169.5183.5170183176.500.0046 183.5197.5184197190.510.0247 197.5211.5198211204.530.0650

14 Frequency Histogram for Blood Pressure Data

15 Relative Frequency Histogram for Blood Pressure Data

16 Cumulative Frequencies & Ogives  The cumulative frequency of a class is the frequency of the class plus the frequencies for all previous classes.  An ogive is a line graph that displays cumulative frequencies.  The cumulative frequency of a class is the frequency of the class plus the frequencies for all previous classes.  An ogive is a line graph that displays cumulative frequencies.

17 Constructing Ogives  Make a frequency table showing class boundaries and cumulative frequencies.  For each class, put a dot over the upper class boundary at the height of the cumulative class frequency.  Place dot on horizontal axis at the lower class boundary of the first class.  Connect the dots.  Make a frequency table showing class boundaries and cumulative frequencies.  For each class, put a dot over the upper class boundary at the height of the cumulative class frequency.  Place dot on horizontal axis at the lower class boundary of the first class.  Connect the dots.

18 Ogive for Blood Pressure Data

19 (a) What number, and percentage, of winning times are under 2:07.15? (b) Estimate number, and percentage, of winning times between 2:05.15 and 2:11.15.

20 Distribution Shapes  Symmetrical  Uniform (it has a rectangular histogram)  Skewed left – the longer tail is on the left side.  Skewed right – the longer tail is on the right side.  Bimodal (the two classes with the largest frequencies are separated by at least one class)  Symmetrical  Uniform (it has a rectangular histogram)  Skewed left – the longer tail is on the left side.  Skewed right – the longer tail is on the right side.  Bimodal (the two classes with the largest frequencies are separated by at least one class)


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