When n is small (less than 30), how does the shape of the t distribution compare to the normal distribution then"it is flatter and wider than the normal distribution."
<h3>What is normal distribution?</h3>
The normal distribution explains a symmetrical plot of data around the mean value, with the standard deviation defining the width of the curve. It is represented graphically as "bell curve."
Some key features regarding the normal distribution are-
- The normal distribution is officially known as the Gaussian distribution, but the term "normal" was coined after scientific publications in the nineteenth century demonstrated that many natural events emerged to "deviate normally" from the mean.
- The naturalist Sir Francis Galton popularized the concept of "normal variability" as the "normal curve" in his 1889 work, Natural Inheritance.
- Even though the normal distribution is a crucial statistical concept, the applications in finance are limited because financial phenomena, such as expected stock-market returns, do not fit neatly within a normal distribution.
- In fact, prices generally follow a right-skewed log-normal distribution with fatter tails.
As a result, relying as well heavily on the a bell curve when forecasting these events can yield unreliable results.
To know more about the normal distribution, here
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Answer:
fa
Step-by-step explanation:
Y=4x-21 I’m pretty sure is the answrr.
Answer:
There are 3 because 12 divided by 4 is 3.
Step-by-step explanation:
Answer:
99% confidence interval: (0.97816,1.03184)
Step-by-step explanation:
We are given the following data set:
1.01, 0.97, 1.03, 1.04, 0.99, 0.98, 0.99, 1.01, 1.03
Formula:
where 
are data points, 
is the mean and n is the number of observations.
Sum of squares of differences = 0.00001975308642 + 0.001264197531 + 0.000597530864 + 0.001186419753 + 0.0002419753088, + 0.00065308642 + 0.0002419753088 + 0.00001975308642 + 0.000597530864 = 0.0048
Confidence interval:
Putting the values, we get,
