题目内容

To model data effectively, it is important to understand the underlying model that describes the data. This means that knowing the physical phenomenon or event that is being modeled is extremely important. For each of the following data/phenomena/events, describe what type of model (linear, quadratic, other) you would use to describe the underlying phenomena.Hourly temperature from 7am to 7pm

A. linear
B. quadratic
C. other

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What happens to the variance of the normal distribution as you increase the number of trials?

A. The variance increases
B. The variance decreases
C. The variance stays the same
D. Not enough information to answer the question

Try increasing the number of trials. Does the result look more like the normal distribution?

A. Yes
B. No

Experiment with the function testErrors() from the lecture code file. Try using a different probability distribution to model the errors, say random.uniform (you'll need to look at the documentation for the random module to determine the correct arguments).Do you get the same result as claimed in the lecture? Does the probability distribution for the sums approach a normal distribution?

A. Yes
B. No

Using the formula derived in this segment, compute k from the second experimental observation: m = 0.15 kg, x = 0.1015 m.Use 9.81 m/s^2 as the gravitational constant (g). Enter your answer to at least 1 decimal place of accuracy.k =______