In a positive correlation, both variables increase together. An example of this is a company's profit's relationship with its sales. The greater the sales, the greater the profit.
A negative correlation is where one variable decreases with increase in the other. An example is the time taken to reach somewhere and the speed traveled at. The faster you move, the less the time.
No correlation means the two variables are not related. An example of this is as you get older, it does not mean you will get better grades.
Using combination and permutation we found out that there are 30240 ways to make varieties of pizza with 3 toppings.
Given 10 toppings
10C3 =10!/3! 7! =120
10P5 =10!/5! =30240 ways
A permutation is a process of placing objects or numbers in order. Combining is the ability to select an object or number from a group of objects or collections such that the order of the objects does not matter.
In mathematics, a combination is the selection of elements from a set with different members, so the order of selection does not matter.
The process or state of binding. Some combination: A combination of ideas. Combined: A chord is a combination of notes. Alliance of Individuals or Parties: Combinations to restrict transactions.
Learn more about combination here: brainly.com/question/11732255
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6. 5. That’s the answer hope it helps
In this question, it is given that
Marcus bought pumpkins that weigh 8 lb, 11 lb, 23 lb, and 15 lb.
And we have to find the mean weight .
To find the mean weight, we will first add all the weights, then divide them by number of pumpkins which is 4.
So the mean weight is

Therefore the mean weight is 14.25 lb .
Answer: 0.0386
Step-by-step explanation:
Given: The population of 400 tall women has a mean height
of 179.832 cm and a standard deviation
of 12.192 cm.
Let X be a random variable that represents the height of woman.
Sample size : n= 50
The probability that the mean for this sample group is above 182.88 will be :
![P(\overline{X}>182.88)\\\\=P(\dfrac{\overline{X}-\mu}{\dfrac{\sigma}{\sqrt{n}}}>\dfrac{182.88-179.832}{\dfrac{12.192}{\sqrt{50}}})\\\\ =P(Z>1.7678)\ \ \ [Z=\dfrac{\overline{X}-\mu}{\dfrac{\sigma}{\sqrt{n}}}]\\\\=1-P(Z](https://tex.z-dn.net/?f=P%28%5Coverline%7BX%7D%3E182.88%29%5C%5C%5C%5C%3DP%28%5Cdfrac%7B%5Coverline%7BX%7D-%5Cmu%7D%7B%5Cdfrac%7B%5Csigma%7D%7B%5Csqrt%7Bn%7D%7D%7D%3E%5Cdfrac%7B182.88-179.832%7D%7B%5Cdfrac%7B12.192%7D%7B%5Csqrt%7B50%7D%7D%7D%29%5C%5C%5C%5C%20%3DP%28Z%3E1.7678%29%5C%20%5C%20%5C%20%5BZ%3D%5Cdfrac%7B%5Coverline%7BX%7D-%5Cmu%7D%7B%5Cdfrac%7B%5Csigma%7D%7B%5Csqrt%7Bn%7D%7D%7D%5D%5C%5C%5C%5C%3D1-P%28Z%3C1.7678%29%5C%5C%5C%5C%3D1-0.9614%5C%20%5C%20%5C%20%5B%5Ctext%7BBy%20p-value%20table%7D%5D%5C%5C%5C%5C%3D%200.0386)
Hence, Required probability = 0.0386