OCR H446 - 2.3 Algorithms - Algorithms and Programming 02

Which of the following graphs shows Constant Big-O notation?

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Which of the following graphs shows Linear Big-O notation?

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Which of the following graphs shows Polynomial Big-O notation?

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Which of the following graphs shows Exponential Big-O notation?

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Which of the following graphs shows Logarithmic Big-O notation?

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Which of the following best describes a Constant Big-O notation?

• This means that the Size of the data set does not impact the Time complexity remains the same.

• This means that Size of the data set increases so does the Time Complexity at the same rate.

• This means that as the Size of the data set increases the algorithm takes much more time to run.

• This means as algorithm takes increasingly more Time to run as the data set increases.

• This means the data set takes a decreasing amount of Time more to complete as the data set increases,

Which of the following best describes a Linear Big-O notation?

• This means that the Size of the data set does not impact the Time complexity remains the same.

• This means that Size of the data set increases so does the Time Complexity at the same rate.

• This means that as the Size of the data set increases the algorithm takes much more time to run.

• This means as algorithm takes increasingly more Time to run as the data set increases.

• This means the data set takes a decreasing amount of Time more to complete as the data set increases,

Which of the following best describes a Polynomial Big-O notation?

• This means that the Size of the data set does not impact the Time complexity remains the same.

• This means that Size of the data set increases so does the Time Complexity at the same rate.

• This means that as the Size of the data set increases the algorithm takes much more time to run.

• This means as algorithm takes increasingly more Time to run as the data set increases.

• This means the data set takes a decreasing amount of Time more to complete as the data set increases,

Which of the following best describes a Exponential Big-O notation?

• This means that the Size of the data set does not impact the Time complexity remains the same.

• This means that Size of the data set increases so does the Time Complexity at the same rate.

• This means that as the Size of the data set increases the algorithm takes much more time to run.

• This means as algorithm takes increasingly more Time to run as the data set increases.

• This means the data set takes a decreasing amount of Time more to complete as the data set increases,

Which of the following best describes a Logarithmic Big-O notation?

• This means that the Size of the data set does not impact the Time complexity remains the same.

• This means that Size of the data set increases so does the Time Complexity at the same rate.

• This means that as the Size of the data set increases the algorithm takes much more time to run.

• This means as algorithm takes increasingly more Time to run as the data set increases.

• This means the data set takes a decreasing amount of Time more to complete as the data set increases,