Question 1

What is the difference between Mean, Median, and Mode?

Accepted Answer

The Mean is the arithmetic average, calculated by adding all values and dividing by the count of values. The Median is the middle number when the dataset is sorted in ascending order. The Mode is the value that appears most frequently. Together, they represent different aspects of central tendency.

Question 2

How do you calculate a weighted average?

Accepted Answer

A weighted average assigns different levels of importance (weights) to each value in the dataset. To calculate it, multiply each value by its weight, sum those products, and then divide by the sum of all weights. For example, if a test (weight 60%) is 90 and homework (weight 40%) is 80: (90 × 0.6) + (80 × 0.4) = 54 + 32 = 86.

Question 3

How does the Grade Calculator final exam predictor work?

Accepted Answer

The Grade Calculator calculates the current weighted grade based on completed assignments. To calculate what is needed on a final exam to reach a target grade (e.g. 90%), it uses the formula: Required on Final = (Target Grade - Current Weighted Grade) / Final Exam Weight. It tells you whether that target is achievable or if it requires over 100%.

Question 4

What is a moving average and when is it used?

Accepted Answer

A moving average calculates successive averages of a subset of numbers over a specific period (k). It is widely used in finance, trading, and weather analysis to smooth out short-term fluctuations and highlight longer-term trends or cycles.

Question 5

What is the standard deviation?

Accepted Answer

Standard deviation measures the spread or dispersion of a dataset relative to its mean. A low standard deviation indicates that the data points tend to be close to the mean, whereas a high standard deviation indicates that the data points are spread out over a wider range of values.

Question 6

What is the geometric mean and how does it differ from arithmetic mean?

Accepted Answer

The arithmetic mean adds numbers together, whereas the geometric mean multiplies them and takes the nth root. The geometric mean is used for values that grow exponentially (like interest rates or population growth), as it accurately reflects compounding effects.

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