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# Question 7
Which value causes floating-point precision issues?
- 1.0
- 2.0
- 0.1
- 0.5
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Answer
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Step 1:: Understand the concept of floating-point precision issues
Floating-point precision issues arise due to the limitations in representing decimal numbers with a finite number of bits. This can cause small discrepancies in the least significant digits.
Step 2:: Identify the potential values
In the given options, we have: - 1.0 - 2.0 - 0.1 - 0.5
Step 3:: Analyze the values
In general, decimal numbers that have a non-repeating binary representation can cause floating-point precision issues. Among the given options, 0.1 is the only number with a non-repeating binary representation.
Step 4:: Validate the analysis
In base- 2 (binary), 0.1 is equivalent to the repeating sequence 0.000111001100110011... Therefore, representing 0.1 as a floating-point number can lead to precision issues.
Final Answer
0.1 causes floating-point precision issues.
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