Answer:
9/7
Step-by-step explanation:
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Answer:
zq+u =x
Step-by-step explanation:
z=(x-u)/q
Multiply each side by q
zq = (x-u)/q *q
zq = x-u
Add u to each side
zq+u = x-u+u
zq+u =x
Outliers are data that are in a very far distance from other values in a set of data
Once an outlier is detected in a set of data, we can do the following to them:
- Discard the outlier
- Change the value of the outlier with another value within close range
- Consider the distribution given
We may have a set of data where some of the <em>values are far in distance from the majority of the data</em>. The set of such data are known as an outlier.
For example, give the set of data;
45 can be considered as an outlier since the <em>distance of data</em><em> to all other data is</em><em> large</em><em>.</em>
Once an outlier is detected in a set of data, we can do the following to them:
- Discard the outlier
- Change the value of the outlier with another value within close range
- Consider the distribution given
Learn more here: brainly.com/question/23258173
Answer:
a) E(X) = 71
b) V(X) = 20.59
Sigma = 4.538
Step-by-step explanation:
<em>The question is incomplete:</em>
<em>According to a 2010 study conducted by the Toronto-based social media analytics firm Sysomos, 71% of all tweets get no reaction. That is, these are tweets that are not replied to or retweeted (Sysomos website, January 5, 2015).
</em>
<em>
Suppose we randomly select 100 tweets.
</em>
<em>a) What is the expected number of these tweets with no reaction?
</em>
<em>b) What are the variance and standard deviation for the number of these tweets with no reaction?</em>
This can be modeled with the binomial distribution, with sample size n=100 and p=0.71, as the probability of no reaction for each individual tweet.
The expected number of these tweets with no reaction can be calcualted as the mean of the binomial random variable with these parameters:

The variance for the number of these tweets with no reaction can be calculated as the variance of the binomial distribution:

Then, the standard deviation becomes:
