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Applications continue
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Sample Case 2: Perform error recovery after entering the second value in error.
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Solution
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| | Enter: | | | See Displayed: | | |
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 CLx
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62 Σ+ 44 Σ+ 44 Σ+ (Σ–) 84 Σ+ 47 Σ+ 58 Σ+
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| 68 Σ+ 60 Σ+ 62 Σ+ 59 Σ+ 71 Σ+ 73 Σ+ | | | |
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sum of numbers
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mean
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standard deviation
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Sample Case 3: Find the sum of the squares and the number of entries in addition to the mean and standard deviation.
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Solution
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| | Enter: | | | See Displayed: | | |
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CLx
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62 Σ+ 84 Σ+ 47 Σ+ 58 Σ+ 68 Σ+
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| 60 Σ+ 62 Σ+ 59 Σ+ 71 Σ+ 73 Σ+ | | | |
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sum of numbers
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mean
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| R | | | |
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standard deviation
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| R | | | |
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sum of squares
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| R | | | |
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number of entries
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Linear Regression (Trend Line) Analysis
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Linear regression techniques are used typically for projecting events
based upon an extrapolation from a known trend. The formula uses the
constant storage location, therefore, any value stored there will be
destroyed when the final key (the one that triggers the result) is pressed. Input data must be evenly spaced and in chronological sequence. Figure 4 illustrates a trend line analysis. Information is entered as follows:
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| 1 |
Press CLx (CLEAR) to clear machine of existing data.
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| 2 |
Enter successive values, press TL after each; the entry sequence number is displayed after each entry.
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