Lol I don’t understand that language
Answer:
Step-by-step explanation:
<em>Key Differences Between Covariance and Correlation
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<em>The following points are noteworthy so far as the difference between covariance and correlation is concerned:
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<em>1. A measure used to indicate the extent to which two random variables change in tandem is known as covariance. A measure used to represent how strongly two random variables are related known as correlation.
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<em>2. Covariance is nothing but a measure of correlation. On the contrary, correlation refers to the scaled form of covariance.
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<em>3. The value of correlation takes place between -1 and +1. Conversely, the value of covariance lies between -∞ and +∞.
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<em>4. Covariance is affected by the change in scale, i.e. if all the value of one variable is multiplied by a constant and all the value of another variable are multiplied, by a similar or different constant, then the covariance is changed. As against this, correlation is not influenced by the change in scale.
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<em>5. Correlation is dimensionless, i.e. it is a unit-free measure of the relationship between variables. Unlike covariance, where the value is obtained by the product of the units of the two variables.
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You can find more here: http://keydifferences.com/difference-between-covariance-and-correlation.html#ixzz4qg5YbiGj
yes It has at least one set of parallel lines
Answer:
0.01024
Step-by-step explanation:
Assume marking was done at random : Hence, each of the 5 time slots have equal Chamves of being marked ;
Number of time slots, n = 5
Required to mark, number of preferred timeslot x = 2
P(x) = 2 /5 = 0.4
Probability of 0.4 that an interviewee gets one of his preferred timeslot.
Probability that each of the 5 interviewees gets one of their preferred time slots :
Using the multiplication rule of independence :
0.4 * 0.4 * 0.4 * 0.4 * 0.4 = 0.4^5 = 0.01024
0.01024 * 100% = 1.024%
